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Research Summary – Structure, Examples and Writing Guide
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Research Summary
Definition:
A research summary is a brief and concise overview of a research project or study that highlights its key findings, main points, and conclusions. It typically includes a description of the research problem, the research methods used, the results obtained, and the implications or significance of the findings. It is often used as a tool to quickly communicate the main findings of a study to other researchers, stakeholders, or decision-makers.
Structure of Research Summary
The Structure of a Research Summary typically include:
- Introduction : This section provides a brief background of the research problem or question, explains the purpose of the study, and outlines the research objectives.
- Methodology : This section explains the research design, methods, and procedures used to conduct the study. It describes the sample size, data collection methods, and data analysis techniques.
- Results : This section presents the main findings of the study, including statistical analysis if applicable. It may include tables, charts, or graphs to visually represent the data.
- Discussion : This section interprets the results and explains their implications. It discusses the significance of the findings, compares them to previous research, and identifies any limitations or future directions for research.
- Conclusion : This section summarizes the main points of the research and provides a conclusion based on the findings. It may also suggest implications for future research or practical applications of the results.
- References : This section lists the sources cited in the research summary, following the appropriate citation style.
How to Write Research Summary
Here are the steps you can follow to write a research summary:
- Read the research article or study thoroughly: To write a summary, you must understand the research article or study you are summarizing. Therefore, read the article or study carefully to understand its purpose, research design, methodology, results, and conclusions.
- Identify the main points : Once you have read the research article or study, identify the main points, key findings, and research question. You can highlight or take notes of the essential points and findings to use as a reference when writing your summary.
- Write the introduction: Start your summary by introducing the research problem, research question, and purpose of the study. Briefly explain why the research is important and its significance.
- Summarize the methodology : In this section, summarize the research design, methods, and procedures used to conduct the study. Explain the sample size, data collection methods, and data analysis techniques.
- Present the results: Summarize the main findings of the study. Use tables, charts, or graphs to visually represent the data if necessary.
- Interpret the results: In this section, interpret the results and explain their implications. Discuss the significance of the findings, compare them to previous research, and identify any limitations or future directions for research.
- Conclude the summary : Summarize the main points of the research and provide a conclusion based on the findings. Suggest implications for future research or practical applications of the results.
- Revise and edit : Once you have written the summary, revise and edit it to ensure that it is clear, concise, and free of errors. Make sure that your summary accurately represents the research article or study.
- Add references: Include a list of references cited in the research summary, following the appropriate citation style.
Example of Research Summary
Here is an example of a research summary:
Title: The Effects of Yoga on Mental Health: A Meta-Analysis
Introduction: This meta-analysis examines the effects of yoga on mental health. The study aimed to investigate whether yoga practice can improve mental health outcomes such as anxiety, depression, stress, and quality of life.
Methodology : The study analyzed data from 14 randomized controlled trials that investigated the effects of yoga on mental health outcomes. The sample included a total of 862 participants. The yoga interventions varied in length and frequency, ranging from four to twelve weeks, with sessions lasting from 45 to 90 minutes.
Results : The meta-analysis found that yoga practice significantly improved mental health outcomes. Participants who practiced yoga showed a significant reduction in anxiety and depression symptoms, as well as stress levels. Quality of life also improved in those who practiced yoga.
Discussion : The findings of this study suggest that yoga can be an effective intervention for improving mental health outcomes. The study supports the growing body of evidence that suggests that yoga can have a positive impact on mental health. Limitations of the study include the variability of the yoga interventions, which may affect the generalizability of the findings.
Conclusion : Overall, the findings of this meta-analysis support the use of yoga as an effective intervention for improving mental health outcomes. Further research is needed to determine the optimal length and frequency of yoga interventions for different populations.
References :
- Cramer, H., Lauche, R., Langhorst, J., Dobos, G., & Berger, B. (2013). Yoga for depression: a systematic review and meta-analysis. Depression and anxiety, 30(11), 1068-1083.
- Khalsa, S. B. (2004). Yoga as a therapeutic intervention: a bibliometric analysis of published research studies. Indian journal of physiology and pharmacology, 48(3), 269-285.
- Ross, A., & Thomas, S. (2010). The health benefits of yoga and exercise: a review of comparison studies. The Journal of Alternative and Complementary Medicine, 16(1), 3-12.
Purpose of Research Summary
The purpose of a research summary is to provide a brief overview of a research project or study, including its main points, findings, and conclusions. The summary allows readers to quickly understand the essential aspects of the research without having to read the entire article or study.
Research summaries serve several purposes, including:
- Facilitating comprehension: A research summary allows readers to quickly understand the main points and findings of a research project or study without having to read the entire article or study. This makes it easier for readers to comprehend the research and its significance.
- Communicating research findings: Research summaries are often used to communicate research findings to a wider audience, such as policymakers, practitioners, or the general public. The summary presents the essential aspects of the research in a clear and concise manner, making it easier for non-experts to understand.
- Supporting decision-making: Research summaries can be used to support decision-making processes by providing a summary of the research evidence on a particular topic. This information can be used by policymakers or practitioners to make informed decisions about interventions, programs, or policies.
- Saving time: Research summaries save time for researchers, practitioners, policymakers, and other stakeholders who need to review multiple research studies. Rather than having to read the entire article or study, they can quickly review the summary to determine whether the research is relevant to their needs.
Characteristics of Research Summary
The following are some of the key characteristics of a research summary:
- Concise : A research summary should be brief and to the point, providing a clear and concise overview of the main points of the research.
- Objective : A research summary should be written in an objective tone, presenting the research findings without bias or personal opinion.
- Comprehensive : A research summary should cover all the essential aspects of the research, including the research question, methodology, results, and conclusions.
- Accurate : A research summary should accurately reflect the key findings and conclusions of the research.
- Clear and well-organized: A research summary should be easy to read and understand, with a clear structure and logical flow.
- Relevant : A research summary should focus on the most important and relevant aspects of the research, highlighting the key findings and their implications.
- Audience-specific: A research summary should be tailored to the intended audience, using language and terminology that is appropriate and accessible to the reader.
- Citations : A research summary should include citations to the original research articles or studies, allowing readers to access the full text of the research if desired.
When to write Research Summary
Here are some situations when it may be appropriate to write a research summary:
- Proposal stage: A research summary can be included in a research proposal to provide a brief overview of the research aims, objectives, methodology, and expected outcomes.
- Conference presentation: A research summary can be prepared for a conference presentation to summarize the main findings of a study or research project.
- Journal submission: Many academic journals require authors to submit a research summary along with their research article or study. The summary provides a brief overview of the study’s main points, findings, and conclusions and helps readers quickly understand the research.
- Funding application: A research summary can be included in a funding application to provide a brief summary of the research aims, objectives, and expected outcomes.
- Policy brief: A research summary can be prepared as a policy brief to communicate research findings to policymakers or stakeholders in a concise and accessible manner.
Advantages of Research Summary
Research summaries offer several advantages, including:
- Time-saving: A research summary saves time for readers who need to understand the key findings and conclusions of a research project quickly. Rather than reading the entire research article or study, readers can quickly review the summary to determine whether the research is relevant to their needs.
- Clarity and accessibility: A research summary provides a clear and accessible overview of the research project’s main points, making it easier for readers to understand the research without having to be experts in the field.
- Improved comprehension: A research summary helps readers comprehend the research by providing a brief and focused overview of the key findings and conclusions, making it easier to understand the research and its significance.
- Enhanced communication: Research summaries can be used to communicate research findings to a wider audience, such as policymakers, practitioners, or the general public, in a concise and accessible manner.
- Facilitated decision-making: Research summaries can support decision-making processes by providing a summary of the research evidence on a particular topic. Policymakers or practitioners can use this information to make informed decisions about interventions, programs, or policies.
- Increased dissemination: Research summaries can be easily shared and disseminated, allowing research findings to reach a wider audience.
Limitations of Research Summary
Limitations of the Research Summary are as follows:
- Limited scope: Research summaries provide a brief overview of the research project’s main points, findings, and conclusions, which can be limiting. They may not include all the details, nuances, and complexities of the research that readers may need to fully understand the study’s implications.
- Risk of oversimplification: Research summaries can be oversimplified, reducing the complexity of the research and potentially distorting the findings or conclusions.
- Lack of context: Research summaries may not provide sufficient context to fully understand the research findings, such as the research background, methodology, or limitations. This may lead to misunderstandings or misinterpretations of the research.
- Possible bias: Research summaries may be biased if they selectively emphasize certain findings or conclusions over others, potentially distorting the overall picture of the research.
- Format limitations: Research summaries may be constrained by the format or length requirements, making it challenging to fully convey the research’s main points, findings, and conclusions.
- Accessibility: Research summaries may not be accessible to all readers, particularly those with limited literacy skills, visual impairments, or language barriers.
About the author
Muhammad Hassan
Researcher, Academic Writer, Web developer
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- How to Write a Summary | Guide & Examples
How to Write a Summary | Guide & Examples
Published on November 23, 2020 by Shona McCombes . Revised on May 31, 2023.
Summarizing , or writing a summary, means giving a concise overview of a text’s main points in your own words. A summary is always much shorter than the original text.
There are five key steps that can help you to write a summary:
- Read the text
- Break it down into sections
- Identify the key points in each section
- Write the summary
- Check the summary against the article
Writing a summary does not involve critiquing or evaluating the source . You should simply provide an accurate account of the most important information and ideas (without copying any text from the original).
Table of contents
When to write a summary, step 1: read the text, step 2: break the text down into sections, step 3: identify the key points in each section, step 4: write the summary, step 5: check the summary against the article, other interesting articles, frequently asked questions about summarizing.
There are many situations in which you might have to summarize an article or other source:
- As a stand-alone assignment to show you’ve understood the material
- To keep notes that will help you remember what you’ve read
- To give an overview of other researchers’ work in a literature review
When you’re writing an academic text like an essay , research paper , or dissertation , you’ll integrate sources in a variety of ways. You might use a brief quote to support your point, or paraphrase a few sentences or paragraphs.
But it’s often appropriate to summarize a whole article or chapter if it is especially relevant to your own research, or to provide an overview of a source before you analyze or critique it.
In any case, the goal of summarizing is to give your reader a clear understanding of the original source. Follow the five steps outlined below to write a good summary.
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You should read the article more than once to make sure you’ve thoroughly understood it. It’s often effective to read in three stages:
- Scan the article quickly to get a sense of its topic and overall shape.
- Read the article carefully, highlighting important points and taking notes as you read.
- Skim the article again to confirm you’ve understood the key points, and reread any particularly important or difficult passages.
There are some tricks you can use to identify the key points as you read:
- Start by reading the abstract . This already contains the author’s own summary of their work, and it tells you what to expect from the article.
- Pay attention to headings and subheadings . These should give you a good sense of what each part is about.
- Read the introduction and the conclusion together and compare them: What did the author set out to do, and what was the outcome?
To make the text more manageable and understand its sub-points, break it down into smaller sections.
If the text is a scientific paper that follows a standard empirical structure, it is probably already organized into clearly marked sections, usually including an introduction , methods , results , and discussion .
Other types of articles may not be explicitly divided into sections. But most articles and essays will be structured around a series of sub-points or themes.
Now it’s time go through each section and pick out its most important points. What does your reader need to know to understand the overall argument or conclusion of the article?
Keep in mind that a summary does not involve paraphrasing every single paragraph of the article. Your goal is to extract the essential points, leaving out anything that can be considered background information or supplementary detail.
In a scientific article, there are some easy questions you can ask to identify the key points in each part.
Introduction | or problem was addressed? |
---|---|
Methods | |
Results | supported? |
Discussion/conclusion |
If the article takes a different form, you might have to think more carefully about what points are most important for the reader to understand its argument.
In that case, pay particular attention to the thesis statement —the central claim that the author wants us to accept, which usually appears in the introduction—and the topic sentences that signal the main idea of each paragraph.
Prevent plagiarism. Run a free check.
Now that you know the key points that the article aims to communicate, you need to put them in your own words.
To avoid plagiarism and show you’ve understood the article, it’s essential to properly paraphrase the author’s ideas. Do not copy and paste parts of the article, not even just a sentence or two.
The best way to do this is to put the article aside and write out your own understanding of the author’s key points.
Examples of article summaries
Let’s take a look at an example. Below, we summarize this article , which scientifically investigates the old saying “an apple a day keeps the doctor away.”
Davis et al. (2015) set out to empirically test the popular saying “an apple a day keeps the doctor away.” Apples are often used to represent a healthy lifestyle, and research has shown their nutritional properties could be beneficial for various aspects of health. The authors’ unique approach is to take the saying literally and ask: do people who eat apples use healthcare services less frequently? If there is indeed such a relationship, they suggest, promoting apple consumption could help reduce healthcare costs.
The study used publicly available cross-sectional data from the National Health and Nutrition Examination Survey. Participants were categorized as either apple eaters or non-apple eaters based on their self-reported apple consumption in an average 24-hour period. They were also categorized as either avoiding or not avoiding the use of healthcare services in the past year. The data was statistically analyzed to test whether there was an association between apple consumption and several dependent variables: physician visits, hospital stays, use of mental health services, and use of prescription medication.
Although apple eaters were slightly more likely to have avoided physician visits, this relationship was not statistically significant after adjusting for various relevant factors. No association was found between apple consumption and hospital stays or mental health service use. However, apple eaters were found to be slightly more likely to have avoided using prescription medication. Based on these results, the authors conclude that an apple a day does not keep the doctor away, but it may keep the pharmacist away. They suggest that this finding could have implications for reducing healthcare costs, considering the high annual costs of prescription medication and the inexpensiveness of apples.
However, the authors also note several limitations of the study: most importantly, that apple eaters are likely to differ from non-apple eaters in ways that may have confounded the results (for example, apple eaters may be more likely to be health-conscious). To establish any causal relationship between apple consumption and avoidance of medication, they recommend experimental research.
An article summary like the above would be appropriate for a stand-alone summary assignment. However, you’ll often want to give an even more concise summary of an article.
For example, in a literature review or meta analysis you may want to briefly summarize this study as part of a wider discussion of various sources. In this case, we can boil our summary down even further to include only the most relevant information.
Using national survey data, Davis et al. (2015) tested the assertion that “an apple a day keeps the doctor away” and did not find statistically significant evidence to support this hypothesis. While people who consumed apples were slightly less likely to use prescription medications, the study was unable to demonstrate a causal relationship between these variables.
Citing the source you’re summarizing
When including a summary as part of a larger text, it’s essential to properly cite the source you’re summarizing. The exact format depends on your citation style , but it usually includes an in-text citation and a full reference at the end of your paper.
You can easily create your citations and references in APA or MLA using our free citation generators.
APA Citation Generator MLA Citation Generator
Finally, read through the article once more to ensure that:
- You’ve accurately represented the author’s work
- You haven’t missed any essential information
- The phrasing is not too similar to any sentences in the original.
If you’re summarizing many articles as part of your own work, it may be a good idea to use a plagiarism checker to double-check that your text is completely original and properly cited. Just be sure to use one that’s safe and reliable.
If you want to know more about ChatGPT, AI tools , citation , and plagiarism , make sure to check out some of our other articles with explanations and examples.
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A summary is a short overview of the main points of an article or other source, written entirely in your own words. Want to make your life super easy? Try our free text summarizer today!
A summary is always much shorter than the original text. The length of a summary can range from just a few sentences to several paragraphs; it depends on the length of the article you’re summarizing, and on the purpose of the summary.
You might have to write a summary of a source:
- As a stand-alone assignment to prove you understand the material
- For your own use, to keep notes on your reading
- To provide an overview of other researchers’ work in a literature review
- In a paper , to summarize or introduce a relevant study
To avoid plagiarism when summarizing an article or other source, follow these two rules:
- Write the summary entirely in your own words by paraphrasing the author’s ideas.
- Cite the source with an in-text citation and a full reference so your reader can easily find the original text.
An abstract concisely explains all the key points of an academic text such as a thesis , dissertation or journal article. It should summarize the whole text, not just introduce it.
An abstract is a type of summary , but summaries are also written elsewhere in academic writing . For example, you might summarize a source in a paper , in a literature review , or as a standalone assignment.
All can be done within seconds with our free text summarizer .
Cite this Scribbr article
If you want to cite this source, you can copy and paste the citation or click the “Cite this Scribbr article” button to automatically add the citation to our free Citation Generator.
McCombes, S. (2023, May 31). How to Write a Summary | Guide & Examples. Scribbr. Retrieved August 16, 2024, from https://www.scribbr.com/working-with-sources/how-to-summarize/
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How To Write A Research Summary
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It’s a common perception that writing a research summary is a quick and easy task. After all, how hard can jotting down 300 words be? But when you consider the weight those 300 words carry, writing a research summary as a part of your dissertation, essay or compelling draft for your paper instantly becomes daunting task.
A research summary requires you to synthesize a complex research paper into an informative, self-explanatory snapshot. It needs to portray what your article contains. Thus, writing it often comes at the end of the task list.
Regardless of when you’re planning to write, it is no less of a challenge, particularly if you’re doing it for the first time. This blog will take you through everything you need to know about research summary so that you have an easier time with it.
What is a Research Summary?
A research summary is the part of your research paper that describes its findings to the audience in a brief yet concise manner. A well-curated research summary represents you and your knowledge about the information written in the research paper.
While writing a quality research summary, you need to discover and identify the significant points in the research and condense it in a more straightforward form. A research summary is like a doorway that provides access to the structure of a research paper's sections.
Since the purpose of a summary is to give an overview of the topic, methodology, and conclusions employed in a paper, it requires an objective approach. No analysis or criticism.
Research summary or Abstract. What’s the Difference?
They’re both brief, concise, and give an overview of an aspect of the research paper. So, it’s easy to understand why many new researchers get the two confused. However, a research summary and abstract are two very different things with individual purpose. To start with, a research summary is written at the end while the abstract comes at the beginning of a research paper.
A research summary captures the essence of the paper at the end of your document. It focuses on your topic, methods, and findings. More like a TL;DR, if you will. An abstract, on the other hand, is a description of what your research paper is about. It tells your reader what your topic or hypothesis is, and sets a context around why you have embarked on your research.
Getting Started with a Research Summary
Before you start writing, you need to get insights into your research’s content, style, and organization. There are three fundamental areas of a research summary that you should focus on.
- While deciding the contents of your research summary, you must include a section on its importance as a whole, the techniques, and the tools that were used to formulate the conclusion. Additionally, there needs to be a short but thorough explanation of how the findings of the research paper have a significance.
- To keep the summary well-organized, try to cover the various sections of the research paper in separate paragraphs. Besides, how the idea of particular factual research came up first must be explained in a separate paragraph.
- As a general practice worldwide, research summaries are restricted to 300-400 words. However, if you have chosen a lengthy research paper, try not to exceed the word limit of 10% of the entire research paper.
How to Structure Your Research Summary
The research summary is nothing but a concise form of the entire research paper. Therefore, the structure of a summary stays the same as the paper. So, include all the section titles and write a little about them. The structural elements that a research summary must consist of are:
It represents the topic of the research. Try to phrase it so that it includes the key findings or conclusion of the task.
The abstract gives a context of the research paper. Unlike the abstract at the beginning of a paper, the abstract here, should be very short since you’ll be working with a limited word count.
Introduction
This is the most crucial section of a research summary as it helps readers get familiarized with the topic. You should include the definition of your topic, the current state of the investigation, and practical relevance in this part. Additionally, you should present the problem statement, investigative measures, and any hypothesis in this section.
Methodology
This section provides details about the methodology and the methods adopted to conduct the study. You should write a brief description of the surveys, sampling, type of experiments, statistical analysis, and the rationality behind choosing those particular methods.
Create a list of evidence obtained from the various experiments with a primary analysis, conclusions, and interpretations made upon that. In the paper research paper, you will find the results section as the most detailed and lengthy part. Therefore, you must pick up the key elements and wisely decide which elements are worth including and which are worth skipping.
This is where you present the interpretation of results in the context of their application. Discussion usually covers results, inferences, and theoretical models explaining the obtained values, key strengths, and limitations. All of these are vital elements that you must include in the summary.
Most research papers merge conclusion with discussions. However, depending upon the instructions, you may have to prepare this as a separate section in your research summary. Usually, conclusion revisits the hypothesis and provides the details about the validation or denial about the arguments made in the research paper, based upon how convincing the results were obtained.
The structure of a research summary closely resembles the anatomy of a scholarly article . Additionally, you should keep your research and references limited to authentic and scholarly sources only.
Tips for Writing a Research Summary
The core concept behind undertaking a research summary is to present a simple and clear understanding of your research paper to the reader. The biggest hurdle while doing that is the number of words you have at your disposal. So, follow the steps below to write a research summary that sticks.
1. Read the parent paper thoroughly
You should go through the research paper thoroughly multiple times to ensure that you have a complete understanding of its contents. A 3-stage reading process helps.
a. Scan: In the first read, go through it to get an understanding of its basic concept and methodologies.
b. Read: For the second step, read the article attentively by going through each section, highlighting the key elements, and subsequently listing the topics that you will include in your research summary.
c. Skim: Flip through the article a few more times to study the interpretation of various experimental results, statistical analysis, and application in different contexts.
Sincerely go through different headings and subheadings as it will allow you to understand the underlying concept of each section. You can try reading the introduction and conclusion simultaneously to understand the motive of the task and how obtained results stay fit to the expected outcome.
2. Identify the key elements in different sections
While exploring different sections of an article, you can try finding answers to simple what, why, and how. Below are a few pointers to give you an idea:
- What is the research question and how is it addressed?
- Is there a hypothesis in the introductory part?
- What type of methods are being adopted?
- What is the sample size for data collection and how is it being analyzed?
- What are the most vital findings?
- Do the results support the hypothesis?
Discussion/Conclusion
- What is the final solution to the problem statement?
- What is the explanation for the obtained results?
- What is the drawn inference?
- What are the various limitations of the study?
3. Prepare the first draft
Now that you’ve listed the key points that the paper tries to demonstrate, you can start writing the summary following the standard structure of a research summary. Just make sure you’re not writing statements from the parent research paper verbatim.
Instead, try writing down each section in your own words. This will not only help in avoiding plagiarism but will also show your complete understanding of the subject. Alternatively, you can use a summarizing tool (AI-based summary generators) to shorten the content or summarize the content without disrupting the actual meaning of the article.
SciSpace Copilot is one such helpful feature! You can easily upload your research paper and ask Copilot to summarize it. You will get an AI-generated, condensed research summary. SciSpace Copilot also enables you to highlight text, clip math and tables, and ask any question relevant to the research paper; it will give you instant answers with deeper context of the article..
4. Include visuals
One of the best ways to summarize and consolidate a research paper is to provide visuals like graphs, charts, pie diagrams, etc.. Visuals make getting across the facts, the past trends, and the probabilistic figures around a concept much more engaging.
5. Double check for plagiarism
It can be very tempting to copy-paste a few statements or the entire paragraphs depending upon the clarity of those sections. But it’s best to stay away from the practice. Even paraphrasing should be done with utmost care and attention.
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6. Religiously follow the word count limit
You need to have strict control while writing different sections of a research summary. In many cases, it has been observed that the research summary and the parent research paper become the same length. If that happens, it can lead to discrediting of your efforts and research summary itself. Whatever the standard word limit has been imposed, you must observe that carefully.
7. Proofread your research summary multiple times
The process of writing the research summary can be exhausting and tiring. However, you shouldn’t allow this to become a reason to skip checking your academic writing several times for mistakes like misspellings, grammar, wordiness, and formatting issues. Proofread and edit until you think your research summary can stand out from the others, provided it is drafted perfectly on both technicality and comprehension parameters. You can also seek assistance from editing and proofreading services , and other free tools that help you keep these annoying grammatical errors at bay.
8. Watch while you write
Keep a keen observation of your writing style. You should use the words very precisely, and in any situation, it should not represent your personal opinions on the topic. You should write the entire research summary in utmost impersonal, precise, factually correct, and evidence-based writing.
9. Ask a friend/colleague to help
Once you are done with the final copy of your research summary, you must ask a friend or colleague to read it. You must test whether your friend or colleague could grasp everything without referring to the parent paper. This will help you in ensuring the clarity of the article.
Once you become familiar with the research paper summary concept and understand how to apply the tips discussed above in your current task, summarizing a research summary won’t be that challenging. While traversing the different stages of your academic career, you will face different scenarios where you may have to create several research summaries.
In such cases, you just need to look for answers to simple questions like “Why this study is necessary,” “what were the methods,” “who were the participants,” “what conclusions were drawn from the research,” and “how it is relevant to the wider world.” Once you find out the answers to these questions, you can easily create a good research summary following the standard structure and a precise writing style.
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Top 7 Research Summary Templates with Samples and Examples
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Kavesh Malhotra
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Turning complex research into a compelling summary is like having a superpower in the vast world of information. A well-crafted research summary isn't just a data crunch; it's a strategic tool. Research shows that concise summaries enhance understanding. Studies reveal that audiences retained 50% more information when presented with well-structured summaries.
Imagine condensing your extensive research into a single page that instantly captivates the reader's attention and highlights the core of your findings. Whether presenting a market research proposal, diving into clinical medicine research, or outlining a project research proposal, a smartly crafted research statement can make your work convenient, accessible, and impactful.
In this blog, we'll guide you through a curated selection of seven Research Summary Templates, each a gem in its own right.
Why Choose Research Summary Templates?
"Efficiency is the soul of every impactful presentation."
- Time-Saving Marvels: These presets are your express pass to creating professional, impactful presentations that save you so much time and energy that would otherwise be spent making a summary from scratch!
- Customizable Frameworks: Tailor each layout to suit your unique research, maintaining flexibility while leveraging a solid starting point.
- Visual Appeal: The slides are not just functional; they are visually engaging, ensuring that your research paper doesn't just get read but leaves a lasting impression.
Let’s begin exploring these templates!
Template 1: Market Research Proposal One-Page Summary Presentation Report Infographic PPT PDF Document
This preset is a game-changer for presenting market research proposals concisely. It encapsulates your research's key aspects in a one-page summary, making a compelling case for readers. It includes details about the project name, researcher's information, and project research proposal details like background, objectives, methodology, and outcomes. Visual elements and a well-organized structure enhance readability, effectively communicating your market insights. Download this preset that transforms your market research proposal into a concise yet comprehensive summary, guiding your stakeholders through the essentials.
![Market Research Proposal One Page Summary Market Research Proposal One Page Summary](https://www.slideteam.net/wp/wp-content/uploads/2023/11/Market-Research-Proposal-One-Page-Summary.png)
DOWNLOAD NOW
Template 2: Executive Summary Clinical Medicine Research Company Profile
For clinical medicine researchers, this layout provides a succinct yet comprehensive overview. The executive summary format communicates vital information, making it ideal for quickly understanding the research's significance. The slide depicts the company outline, critical statistics, and financial overview. The significant facts covered are the employee count, number of regulatory approvals, global market share, revenue CAGR, total revenue, and market capitalization. Elevate your clinical medicine research with an executive summary that encapsulates the essence of your findings and the potential impact on the medical landscape.
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Template 3: Sample Research Paper Outline in One-Page Summary Report
This structure streamlines your detailed research paper into a digestible one-page summary. It breaks down the research paper's structure, ensuring the audience grasps vital points efficiently. It encapsulates five main sections: introduction, issue, literature review, recommendations, and conclusion. The easy-to-follow format makes it a valuable tool for presenting a complex research statement. Download this layout that transforms your detailed research paper into a one-page summary wonder, clearly presenting the structure and key points.
![Sample Research Paper Outline in One Page Summary Sample Research Paper Outline in One Page Summary](https://www.slideteam.net/wp/wp-content/uploads/2023/11/Sample-Research-Paper-Outline-in-One-Page-Summary.png)
Template 4: One-Page Summary for Business Excellence Models Research Paper
Condense your exploration of business excellence models into a single, impactful page. This slide highlights the introduction, executive summary , company background, financial information, business excellence model used, key findings and insights, and conclusion, presenting them aesthetically pleasing. It's perfect for delivering the essence of your business excellence research with clarity and brevity. Condense your exploration of business excellence models into a single page, making your insights accessible and actionable.
![One Page Summary for Business Excellence Models Research Paper One Page Summary for Business Excellence Models Research Paper](https://www.slideteam.net/wp/wp-content/uploads/2023/11/One-Page-Summary-for-Business-Excellence-Models-Research-Paper.png)
Template 5: One-Page Project Research Proposal Summary Presentation
Efficiently communicate the crux of your project research proposal with this preset. It highlights crucial components of your project research like objectives, study design, budget, project milestones and durations, etc. The one-page summary format ensures that your proposal's key elements are prominently featured. Visual elements enhance engagement, ensuring that key stakeholders swiftly grasp your project's significance. Download this layout and make it an excellent choice for a compelling project research presentation.
![One Page Project Research Proposal Summary One Page Project Research Proposal Summary](https://www.slideteam.net/wp/wp-content/uploads/2023/11/One-Page-Project-Research-Proposal-Summary.png)
Template 6: One-Page Research Paper Summary on Business Ethics and Corruption
Navigate the complex landscape of business ethics and corruption research with this template. It condenses your research paper into a one-page summary , focusing on crucial ethical considerations:
- Introduction of the concept
- sources of corruption in businesses
- The legislative framework
- Principals of ethics
- Conclusion and
- Customer viewpoint
Clear visuals and a cohesive layout ensure that your insights on ethics and corruption are communicated effectively, giving your research statement the attention it deserves. Download this one-page summary , ensuring readers grasp your project's significance swiftly.
![One Page Research Paper Summary on Business Ethics and Corruption One Page Research Paper Summary on Business Ethics and Corruption](https://www.slideteam.net/wp/wp-content/uploads/2023/11/One-Page-Research-Paper-Summary-on-Business-Ethics-and-Corruption.png)
Template 7: Research Statement One Page Summary with Future Goals
Craft a compelling narrative of your research journey, culminating in a one-page summary with future goals. This presentation seamlessly integrates your research statement with a forward-looking perspective. It offers an overview of past and future research approaches and future goals to be achieved, along with a visual flowchart presenting your project research proposal , research activity, and other written content. Download this powerful tool for presenting your research's impact and future directions.
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Conclusion: Your Research, Your Way
In the world of academia, business, or healthcare, your research is a cornerstone of progress. Ensure it's not just buried in volumes of data but presented in a way that captivates and communicates. Explore the above research summary templates and transform your research journey into a resonant narrative. Furthermore, dive into the past with our top history research proposal examples , complete with templates and samples for your historical research endeavors.
Remember, brevity is not just appreciated in a world saturated with information; it's often indispensable. So, here , you can streamline your project research proposals with our top 7 one-page templates for compelling and concise presentations.
Craft your research summary with care, and let your findings shine!
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Research Summary Structure, Samples, Writing Steps, and Useful Suggestions
Updated 24 Jul 2024
What is a Research Summary and Why Is It Important?
A research summary is a type of paper designed to provide a brief overview of a given study - typically, an article from a peer-reviewed academic journal. It is a frequent type of task encountered in US colleges and universities, both in humanitarian and exact sciences, which is due to how important it is to teach students to properly interact with and interpret scientific literature and in particular, academic papers, which are the key way through which new ideas, theories, and evidence are presented to experts in many fields of knowledge. A research summary typically preserves the structure/sections of the article it focuses on. Get the grades you want with our professional research paper helper .
How to Write a Research Summary – Typical Steps
Follow these clear steps to help avoid typical mistakes and productivity bottlenecks, allowing for a more efficient through your writing process:
- Skim the article in order to get a rough idea of the content covered in each section and to understand the relative importance of content, for instance, how important different lines of evidence are (this helps you understand which sections you should focus on more when reading in detail). Make sure you understand the task and your professor's requirements before reading the article. In this step, you can also decide whether to write a summary by yourself or ask for a cheap research paper writing service instead.
- Analyze and understand the topic and article. Writing a summary of a research paper involves becoming very familiar with the topic – sometimes, it is impossible to understand the content without learning about the current state of knowledge, as well as key definitions, concepts, models. This is often performed while reading the literature review. As for the paper itself, understanding it means understanding analysis questions, hypotheses, listed evidence, how strongly this evidence supports the hypotheses, as well as analysis implications. Keep in mind that only a deep understanding allows one to efficiently and accurately summarize the content.
- Make notes as you read. You could highlight or summarize each paragraph with a brief sentence that would record the key idea delivered in it (obviously, some paragraphs deserve more attention than others). However, be careful not to engage in extensive writing while still reading. This is important because, while reading, you might realize that some sections you initially considered important might actually be less important compared to information that follows. As for underlining or highlighting – do these only with the most important evidence, otherwise, there is little use in “coloring” everything without distinction.
- Assemble a draft by bringing together key evidence and notes from each paragraph/ section. Make sure that all elements characteristic of a research summary are covered (as detailed below).
- Find additional literature for forming or supporting your critical view (this is if your critical view/position is required), for instance, judgments about limitations of the study or contradictory evidence.
Read Also: Criminal Justice Research Topics To Impress Your Teacher
Research Summary Structure
The research summary format resembles that found in the original paper (just a concise version of it). Content from all sections should be covered and reflected upon, regardless of whether corresponding headings are present or not. Key structural elements of any research summary are as follows:
- Title – it announces the exact topic/area of analysis and can even be formulated to briefly announce key finding(s) or argument(s) delivered.
- Abstract – this is a very concise and comprehensive description of the study, present virtually in any academic article (the length varies greatly, typically within 100-500 words). Unlike an academic article, your research summary is expected to have a much shorter abstract.
- Introduction – this is an essential part of any research summary which provides necessary context (the literature review) that helps introduce readers to the subject by presenting the current state of the investigation, an important concept or definition, etc. This section might also describe the subject’s importance (or might not, for instance, when it is self-evident). Finally, an introduction typically lists investigation questions and hypotheses advanced by authors, which are normally mentioned in detail in any research summary (obviously, doing this is only possible after identifying these elements in the original paper).
- Methodology – regardless of its location, this section details experimental methods or data analysis methods used (e.g. types of experiments, surveys, sampling, or statistical analysis). In a research summary, many of these details would have to be omitted; hence, it is important to understand what is most important to mention.
- Results section – this section lists in detail evidence obtained from all experiments with some primary data analysis, conclusions, observations, and primary interpretations being made. It is typically the largest section of any analysis paper, so, it has to be concisely rewritten, which implies understanding which content is worth omitting and worth keeping.
- Discussion – this is where results are being discussed in the context of current knowledge among experts. This section contains interpretations of results, theoretical models explaining the observed results, study strengths and especially limitations, complementary future exploration to be undertaken, conclusions, etc. All these are important elements that need to be conveyed in a summary.
- Conclusion – in the original article, this section could be absent or merged with “Discussion”. Specific research summary instructions might require this to be a standalone section. In a conclusion, hypotheses are revisited and validated or denied, based on how convincing the evidence is (key lines of evidence could be highlighted).
- References – this section is for mentioning those cited works directly in your summary – obviously, one has to provide appropriate citations at least for the original article (this often suffices). Mentioning other works might be relevant when your critical opinion is also required (supported with new unrelated evidence).
Note that if you need some model research summary papers done before you start writing yourself (this will help familiarize you with essay structure and various sections), you could simply recruit our company by following the link provided below.
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Research Summary Writing Tips
Below is a checklist of useful research paper tips worth considering when writing research summaries:
- Make sure you are always aware of the bigger picture/ direction. You need to keep in mind a complete and coherent picture of the story delivered by the original article. It might be helpful to reread or scan it quickly to remind yourself of the declared goals, hypotheses, key evidence, and conclusions – this awareness offers a constant sense of direction, which ensures that no written sentence is out of context. It is useful doing this even after you have written a fourth, a third, or half of the paper (to make sure no deviation occurs).
- Consider writing a detailed research outline before writing the draft – it might be of great use when structuring your paper. A research summary template is also very likely to help you structure your paper.
- Sketch the main elements of the conclusion before writing it. Do this for a number of reasons: validate/invalidate hypotheses; enumerate key evidence supporting or invalidating them, list potential implications; mention the subject’s importance; mention study limitations and future directions for research. In order to include them all, it is useful having them written down and handy.
- Consider writing the introduction and discussion last. It makes sense to first list hypotheses, goals, questions, and key results. Latter, information contained in the introduction and discussion can be adapted as needed (for instance, to match a preset word count limit). Also, on the basis of already written paragraphs, you can easily generate your discussion with the help of a conclusion tool ; it works online and is absolutely free of charge. Apart from this, follow a natural order.
- Include visuals – you could summarize a lot of text using graphs or charts while simultaneously improving readability.
- Be very careful not to plagiarize. It is very tempting to “borrow” or quote entire phrases from an article, provided how well-written these are, but you need to summarize your paper without plagiarizing at all (forget entirely about copy-paste – it is only allowed to paraphrase and even this should be done carefully). The best way to stay safe is by formulating your own thoughts from scratch.
- Keep your word count in check. You don’t want your summary to be as long as the original paper (just reformulated). In addition, you might need to respect an imposed word count limit, which requires being careful about how much you write for each section.
- Proofread your work for grammar, spelling, wordiness, and formatting issues (feel free to use our convert case tool for titles, headings, subheadings, etc.).
- Watch your writing style – when summarizing content, it should be impersonal, precise, and purely evidence-based. A personal view/attitude should be provided only in the critical section (if required).
- Ask a colleague to read your summary and test whether he/she could understand everything without reading the article – this will help ensure that you haven’t skipped some important content, explanations, concepts, etc.
For additional information on formatting, structure, and for more writing tips, check out these research paper guidelines on our website. Remember that we cover most research papers writing services you can imagine and can offer help at various stages of your writing project, including proofreading, editing, rewriting for plagiarism elimination, and style adjustment.
Research Summary Example 1
Below are some defining elements of a sample research summary written from an imaginary article.
Title – “The probability of an unexpected volcanic eruption in Yellowstone” Introduction – this section would list those catastrophic consequences hitting our country in case of a massive eruption and the importance of analyzing this matter. Hypothesis – An eruption of the Yellowstone supervolcano would be preceded by intense precursory activity manifesting a few weeks up to a few years in advance. Results – these could contain a report of statistical data from multiple volcanic eruptions happening worldwide looking specifically at activity that preceded these events (in particular, how early each type of activity was detected). Discussion and conclusion – Given that Yellowstone is continuously monitored by scientists and that signs of an eruption are normally detected much in advance and at least a few days in advance, the hypothesis is confirmed. This could find application in creating emergency plans detailing an organized evacuation campaign and other response measures.
Research Summary Example 2
Below is another sample sketch, also from an imaginary article.
Title – “The frequency of extreme weather events in US in 2000-2008 as compared to the ‘50s” Introduction – Weather events bring immense material damage and cause human victims. Hypothesis – Extreme weather events are significantly more frequent nowadays than in the ‘50s Results – these could list the frequency of several categories of extreme events now and then: droughts and associated fires, massive rainfall/snowfall and associated floods, hurricanes, tornadoes, arctic cold waves, etc. Discussion and conclusion – Several types of extreme events indeed became significantly more frequent recently, confirming this hypothesis. This increasing frequency correlates reliably with rising CO2 levels in atmosphere and growing temperatures worldwide and in the absence of another recent major global change that could explain a higher frequency of disasters but also knowing how growing temperature disturbs weather patterns, it is natural to assume that global warming (CO2) causes this increase in frequency. This, in turn, suggests that this increased frequency of disasters is not a short-term phenomenon but is here to stay until we address CO2 levels.
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Let Professionals Help With Your Research Summary
Writing a research summary has its challenges, but becoming familiar with its structure (i.e. the structure of an article), understanding well the article that needs to be summarized, and adhering to recommended guidelines will help the process go smoothly.
Simply create your account in a few clicks, place an order by uploading your instructions, and upload or indicate the article requiring a summary and choose a preferred writer for this task (according to experience, rating, bidding price). Our transparent system puts you in control, allowing you to set priorities as you wish (to our knowledge, few competitors have something equivalent in place). Obviously, we can help with many other essay types such as critical thinking essay, argumentative essay, etc. In particular, the research paper definition article on our website highlights a few popular paper types we work with.
Another unique advantage is that we allow and encourage you to communicate directly with your writer (if you wish) guiding his or her work – feel free to request partial drafts, to clarify potential issues you worry about, or even to revise papers as often as needed (for free) until you achieve a satisfactory result. We’ve implemented a system where money is released to writers only after students are fully satisfied with what they get. If you feel like giving it a try, it’s easy and worry-free! Just follow the link below.
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Writing a Summary – Explanation & Examples
Published by Alvin Nicolas at October 17th, 2023 , Revised On October 17, 2023
In a world bombarded with vast amounts of information, condensing and presenting data in a digestible format becomes invaluable. Enter summaries.
A summary is a brief and concise account of the main points of a larger body of work. It distils complex ideas, narratives, or data into a version that is quicker to read and easier to understand yet still retains the essence of the original content.
Importance of Summaries
The importance of summarising extends far beyond just making reading more manageable. In academic settings, summaries aid students in understanding and retaining complex materials, from textbook chapters to research articles. They also serve as tools to showcase one’s grasp of the subject in essays and reports.
In professional arenas, summaries are pivotal in business reports, executive briefings, and even emails where key points need to be conveyed quickly to decision-makers. Meanwhile, summarising skills come into play in our personal lives when we relay news stories to friends, recap a movie plot, or even scroll through condensed news or app notifications on our smartphones.
Why Do We Write Summaries?
In our modern information age, the sheer volume of content available can be overwhelming. From detailed research papers to comprehensive news articles, the quest for knowledge is often met with lengthy and complex resources. This is where the power of a well-crafted summary comes into play. But what drives us to create or seek out summaries? Let’s discuss.
Makes Important Things Easy to Remember
At the heart of summarisation is the goal to understand. A well-written summary aids in digesting complex material. By distilling larger works into their core points, we reinforce the primary messages, making them easier to remember. This is especially crucial for students who need to retain knowledge for exams or professionals prepping for a meeting based on a lengthy report.
Simplification of Complex Topics
Not everyone is an expert in every field. Often, topics come laden with jargon, intricate details, and nuanced arguments. Summaries act as a bridge, translating this complexity into accessible and straightforward content. This is especially beneficial for individuals new to a topic or those who need just the highlights without the intricacies.
Aid in Researching and Understanding Diverse Sources
Researchers, writers, and academics often wade through many sources when working on a project. This involves finding sources of different types, such as primary or secondary sources , and then understanding their content. Sifting through each source in its entirety can be time-consuming. Summaries offer a streamlined way to understand each source’s main arguments or findings, making synthesising information from diverse materials more efficient.
Condensing Information for Presentation or Sharing
In professional settings, there is often a need to present findings, updates, or recommendations to stakeholders. An executive might not have the time to go through a 50-page report, but they would certainly appreciate a concise summary highlighting the key points. Similarly, in our personal lives, we often summarise movie plots, book stories, or news events when sharing with friends or family.
Characteristics of a Good Summary
Crafting an effective summary is an art. It’s more than just shortening a piece of content; it is about capturing the essence of the original work in a manner that is both accessible and true to its intent. Let’s explore the primary characteristics that distinguish a good summary from a mediocre one:
Conciseness
At the core of a summary is the concept of brevity. But being concise doesn’t mean leaving out vital information. A good summary will:
- Eliminate superfluous details or repetitive points.
- Focus on the primary arguments, events, or findings.
- Use succinct language without compromising the message.
Objectivity
Summarising is not about infusing personal opinions or interpretations. A quality summary will:
- Stick to the facts as presented in the original content.
- Avoid introducing personal biases or perspectives.
- Represent the original author’s intent faithfully.
A summary is meant to simplify and make content accessible. This is only possible if the summary itself is easy to understand. Ensuring clarity involves:
- Avoiding jargon or technical terms unless they are essential to the content. If they are used, they should be clearly defined.
- Structuring sentences in a straightforward manner.
- Making sure ideas are presented in a way that even someone unfamiliar with the topic can grasp the primary points.
A jumble of ideas, no matter how concise, will not make for a good summary. Coherence ensures that there’s a logical flow to the summarised content. A coherent summary will:
- Maintain a logical sequence, often following the structure of the original content.
- Use transition words or phrases to connect ideas and ensure smooth progression.
- Group related ideas together to provide structure and avoid confusion.
Steps of Writing a Summary
The process of creating a compelling summary is not merely about cutting down content. It involves understanding, discerning, and crafting. Here is a step-by-step guide to writing a summary that encapsulates the essence of the original work:
Reading Actively
Engage deeply with the content to ensure a thorough understanding.
- Read the entire document or work first to grasp its overall intent and structure.
- On the second read, underline or highlight the standout points or pivotal moments.
- Make brief notes in the margins or on a separate sheet, capturing the core ideas in your own words.
Identifying the Main Idea
Determine the backbone of the content, around which all other details revolve.
- Ask yourself: “What is the primary message or theme the author wants to convey?”
- This can often be found in the title, introduction, or conclusion of a piece.
- Frame the main idea in a clear and concise statement to guide your summary.
List Key Supporting Points
Understand the pillars that uphold the main idea, providing evidence or depth to the primary message.
- Refer back to the points you underlined or highlighted during your active reading.
- Note major arguments, evidence, or examples that the author uses to back up the main idea.
- Prioritise these points based on their significance to the main idea.
Draft the Summary
Convert your understanding into a condensed, coherent version of the original.
- Start with a statement of the main idea.
- Follow with the key supporting points, maintaining logical order.
- Avoid including trivial details or examples unless they’re crucial to the primary message.
- Use your own words, ensuring you are not plagiarising the original content.
Fine-tune your draft to ensure clarity, accuracy, and brevity.
- Read your draft aloud to check for flow and coherence.
- Ensure that your summary remains objective, avoiding any personal interpretations or biases.
- Check the length. See if any non-essential details can be removed without sacrificing understanding if it is too lengthy.
- Ensure clarity by ensuring the language is straightforward, and the main ideas are easily grasped.
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Dos and Don’ts of Summarising Key Points
Summarising, while seemingly straightforward, comes with its nuances. Properly condensing content demands a balance between brevity and fidelity to the original work. To aid in crafting exemplary summaries, here is a guide on the essential dos and don’ts:
Use your Own Words
This ensures that you have truly understood the content and are not merely parroting it. It also prevents issues of plagiarism.
Tip: After reading the original content, take a moment to reflect on it. Then, without looking at the source, write down the main points in your own words.
Attribute Sources Properly
Giving credit is both ethical and provides context to readers, helping them trace back to the original work if needed. How to cite sources correctly is a skill every writer should master.
Tip: Use signal phrases like “According to [Author/Source]…” or “As [Author/Source] points out…” to seamlessly incorporate attributions.
Ensure Accuracy of the Summarised Content
A summary should be a reliable reflection of the original content. Distorting or misrepresenting the original ideas compromises the integrity of the summary.
Tip: After drafting your summary, cross-check with the original content to ensure all key points are represented accurately and ensure you are referencing credible sources .
Avoid Copy-Pasting Chunks of Original Content
This not only raises plagiarism concerns but also shows a lack of genuine engagement with the material.
Tip: If a particular phrase or sentence from the original is pivotal and cannot be reworded without losing its essence, use block quotes , quotation marks, and attribute the source.
Do not Inject your Personal Opinion
A summary should be an objective reflection of the source material. Introducing personal biases or interpretations can mislead readers.
Tip: Stick to the facts and arguments presented in the original content. If you find yourself writing “I think” or “In my opinion,” reevaluate the sentence.
Do not Omit Crucial Information
While a summary is meant to be concise, it shouldn’t be at the expense of vital details that are essential to understanding the original content’s core message.
Tip: Prioritise information. Always include the main idea and its primary supports. If you are unsure whether a detail is crucial, consider its impact on the overall message.
Examples of Summaries
Here are a few examples that will help you get a clearer view of how to write a summary.
Example 1: Summary of a News Article
Original Article: The article reports on the recent discovery of a rare species of frog in the Amazon rainforest. The frog, named the “Emerald Whisperer” due to its unique green hue and the soft chirping sounds it makes, was found by a team of researchers from the University of Texas. The discovery is significant as it offers insights into the biodiversity of the region, and the Emerald Whisperer might also play a pivotal role in understanding the ecosystem balance.
Summary: Researchers from the University of Texas have discovered a unique frog, termed the “Emerald Whisperer,” in the Amazon rainforest. This finding sheds light on the region’s biodiversity and underscores the importance of the frog in ecological studies.
Example 2: Summary of a Research Paper
Original Paper: In a study titled “The Impact of Urbanisation on Bee Populations,” researchers conducted a year-long observation on bee colonies in three urban areas and three rural areas. Using specific metrics like colony health, bee productivity, and population size, the study found that urban environments saw a 30% decline in bee populations compared to rural settings. The research attributes this decline to factors like pollution, reduced green spaces, and increased temperatures in urban areas.
Summary: A study analysing the effects of urbanisation on bee colonies found a significant 30% decrease in bee populations in urban settings compared to rural areas. The decline is linked to urban factors such as pollution, diminished greenery, and elevated temperatures.
Example 3: Summary of a Novel
Original Story: In the novel “Winds of Fate,” protagonist Clara is trapped in a timeless city where memories dictate reality. Throughout her journey, she encounters characters from her past, present, and imagined future. Battling her own perceptions and a menacing shadow figure, Clara seeks an elusive gateway to return to her real world. In the climax, she confronts the shadow, which turns out to be her own fear, and upon overcoming it, she finds her way back, realising that reality is subjective.
Summary: “Winds of Fate” follows Clara’s adventures in a surreal city shaped by memories. Confronting figures from various phases of her life and battling a symbolic shadow of her own fear, Clara eventually discovers that reality’s perception is malleable and subjective.
Frequently Asked Questions
How long is a summary.
A summary condenses a larger piece of content, capturing its main points and essence. It is usually one-fourth of the original content.
What is a summary?
A summary is a concise representation of a larger text or content, highlighting its main ideas and points. It distils complex information into a shorter form, allowing readers to quickly grasp the essence of the original material without delving into extensive details. Summaries prioritise clarity, brevity, and accuracy.
When should I write a summary?
Write a summary when you need to condense lengthy content for easier comprehension and recall. It’s useful in academic settings, professional reports, presentations, and research to highlight key points. Summaries aid in comparing multiple sources, preparing for discussions, and sharing essential details of extensive materials efficiently with others.
How can I summarise a source without plagiarising?
To summarise without plagiarising: Read the source thoroughly, understand its main ideas, and then write the summary in your own words. Avoid copying phrases verbatim. Attribute the source properly. Use paraphrasing techniques and cross-check your summary against the original to ensure distinctiveness while retaining accuracy. Always prioritise understanding over direct replication.
What is the difference between a summary and an abstract?
A summary condenses a text, capturing its main points from various content types like books, articles, or movies. An abstract, typically found in research papers and scientific articles, provides a brief overview of the study’s purpose, methodology, results, and conclusions. Both offer concise versions, but abstracts are more structured and specific.
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The ability to effectively incorporate multiple sources into one’s work is not just a skill, but a necessity. Whether we are talking about research papers, articles, or even simple blog posts, synthesising sources can elevate our content to a more nuanced, comprehensive, and insightful level.
From academic research to personal blogs, the bedrock of trust and credibility is often established by one simple act: source citing. Whether we are constructing a thesis for a graduate program or debunking a myth on a personal blog, providing the origins of our information bolsters our arguments and pays homage to the original creators of that knowledge.
A secondary source refers to any material that interprets, analyses, or reviews information originally presented elsewhere. Unlike primary sources, which offer direct evidence or first-hand testimony, secondary sources work on those original materials, offering commentary, critiques, and perspectives.
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When writing a summary, the goal is to compose a concise and objective overview of the original article. The summary should focus only on the article's main ideas and important details that support those ideas.
Guidelines for summarizing an article:
- State the main ideas.
- Identify the most important details that support the main ideas.
- Summarize in your own words.
- Do not copy phrases or sentences unless they are being used as direct quotations.
- Express the underlying meaning of the article, but do not critique or analyze.
- The summary should be about one third the length of the original article.
Your summary should include:
- Give an overview of the article, including the title and the name of the author.
- Provide a thesis statement that states the main idea of the article.
- Use the body paragraphs to explain the supporting ideas of your thesis statement.
- One-paragraph summary - one sentence per supporting detail, providing 1-2 examples for each.
- Multi-paragraph summary - one paragraph per supporting detail, providing 2-3 examples for each.
- Start each paragraph with a topic sentence.
- Use transitional words and phrases to connect ideas.
- Summarize your thesis statement and the underlying meaning of the article.
Adapted from "Guidelines for Using In-Text Citations in a Summary (or Research Paper)" by Christine Bauer-Ramazani, 2020
Additional Resources
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How to Write a Summary - Guide & Examples (from Scribbr.com)
Writing a Summary (from The University of Arizona Global Campus Writing Center)
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How to write a summary of a research paper (with template)
by Diana Ribeiro Last updated Jul 20, 2020 | Published on Jun 27, 2020 Writing Skills 0 comments
In our daily work as medical writers, we have to read many scholarly articles and extract the main information from them. Having a process to retrieve that information and create a short summary that you can easily access will save you precious time. That’s why I decided to guide you through my process of summarising a research article and created a handy template.
Having short summaries of academic papers is useful to create news articles, press releases, social media posts, blog articles, or curated news reports, like the one I write weekly for my newsletter subscribers .
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What’s the importance of summarising research articles?
If you don’t have a system to extract the main information from a scholarly paper, you may have to re-read it repeatedly, looking for that piece of information you know it’s there. Sure, you can use a highlighter pen to mark the main points, but sometimes what happens is that you end up with yellow walls of text. Or green. Or even a rainbow. Which may be pretty, but it’s quite useless as a retrieval system.
What also happens when you highlight text is that you end up with a diverse array of writing styles, none of them being your own. This way, when you try to write a text with information from multiple sources, you have to search for the information and write it in a consistent style.
In this article, I’ll show you how to retrieve the most relevant information from a scientific paper, how to write it in a compelling way, and how to present it in a news-worthy style that’s easily adaptable to your audience. Ready?
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Three steps to summarise a research paper
1. scan and extract the main points.
First things first, so you have to read the paper. But that doesn’t mean you have to read it from start to finish. Start by scanning the article for its main points.
Here’s the essential information to extract from the research paper you have in front of you:
- Authors, year, doi
- Study question: look in the introduction for a phrase like “the aim of this study was”
- Hypothesis tested
- Study methods: design, participants, materials, procedure, what was manipulated (independent variables), what was measured (dependent variables), how data were analysed.
- Findings: from the results section; fill this before you look at the discussion section, if possible. Write bullet points.
- Interpretation: how did the authors interpreted their findings? Use short sentences, in your own words.
After extracting the key information , revisit the article and read it more attentively, to see if you missed something. Add some notes to your summary, but take care to avoid plagiarism. Write notes in your own words. If you can’t do that at this moment, use quotation marks to indicate that your note came straight from the study. You can rewrite it later, when you have a better grasp of the study.
2. Use a journalistic approach for the first draft
Some sources advise you to keep the same structure as the scientific article, but I like to use the journalistic approach of news articles and flush out the more relevant information first, followed by the details. This is more enticing for readers, making them want to continue reading. Yes, I know that your reader may be just you, but I know I have lost myself in some of the things I’ve written, so…keep it interesting, even for a future self 😊.
This is the main information you have to put together:
Title of the article: I like to keep the original article title for the summary, because it’s easier to refer back to the original article if I need to. Sometimes I add a second title, just for me, if the article title is too obscure or long.
- 1 st paragraph: Answer the 5 W’s in 3-4 sentences.
Who? (the authors)
What? (main finding)
When and where? (journal, date of publication)
Why? (relevance)
This should be a standalone paragraph, meaning that the reader should be able to take out the main information even if they just read this paragraph.
- Subsequent paragraphs: In 2-3 paragraphs or less, provide context and more information about the research done. If you’re not sure if a detail is important or not, you can include it here and edit it out in the next step.
![](http://sektorel.online/777/templates/cheerup/res/banner1.gif)
3. Polish the rough edges
In this stage, you’re going to make a quick edit, checking for completeness and accuracy. Make sure you’ve included all the main points without repeating yourself. Double-check all the numbers. Stay focused on the research questions to avoid tangents. Avoid using jargon and the passive voice whenever possible.
Final summary
Using this approach, you’ll end up with a short summary of your article that you can use to craft other types of writing, such as press releases, news articles, social media blurbs, and many others.
The advantages of summarising research articles are that you can better understand what the article is about, and you’ll have a text written by you, so it’s easier to adapt and you avoid unintentional plagiarism.
That’s it! My guide to write a research paper summary 😊
I’ve created a handout with all the information in this blog post plus a fill-in-the-blanks template that you can use to summarise research articles, you can download it using the form below. You’ll be signed up to my mailing list, and receive a weekly roundup of news in the biomedical industry as a bonus!
If you have any comments or questions, please let me know in the comment box below.
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How to Write a Summary of a Research Paper
Last Updated: July 10, 2020 References
This article was reviewed by Annaliese Dunne and by wikiHow staff writer, Hannah Madden . Annaliese Dunne is a Middle School English Teacher. With over 10 years of teaching experience, her areas of expertise include writing and grammar instruction, as well as teaching reading comprehension. She is also an experienced freelance writer. She received her Bachelor's degree in English. This article has been viewed 28,701 times.
Writing a summary of an academic research paper is an important skill, and it shows that you understand all of the relevant information presented to you. However, writing a summary can be tough, since it requires you to be completely objective and keep any analysis or criticisms to yourself. By keeping your goal in mind as you read the paper and focusing on the key points, you can write a succinct, accurate summary of a research paper to prove that you understood the overall conclusion.
Reading the Research Paper
![sample summary of research paper Step 1 Figure out the focus of your summary.](https://www.wikihow.com/images/thumb/7/75/Write-a-Summary-of-a-Research-Paper-Step-1.jpg/v4-460px-Write-a-Summary-of-a-Research-Paper-Step-1.jpg)
- For instance, if you’re supporting an argument in your own research paper, focus on the elements that are similar to yours.
- Or, if you’re comparing and contrasting methodology, focus on the methods and the significance of the results.
![sample summary of research paper Step 2 Scan through the article to pick out important information.](https://www.wikihow.com/images/thumb/5/5b/Write-a-Summary-of-a-Research-Paper-Step-2.jpg/v4-460px-Write-a-Summary-of-a-Research-Paper-Step-2.jpg)
- You can also read the abstract of the paper as a good example of what the authors find to be important in their article.
![sample summary of research paper Step 3 Read the article fully 1 to 2 times.](https://www.wikihow.com/images/thumb/1/11/Write-a-Summary-of-a-Research-Paper-Step-3.jpg/v4-460px-Write-a-Summary-of-a-Research-Paper-Step-3.jpg)
- Depending on how long and dense the paper is, your initial reading could take you up to an hour or more.
![sample summary of research paper Step 4 Underline or highlight important information.](https://www.wikihow.com/images/thumb/4/46/Write-a-Summary-of-a-Research-Paper-Step-4.jpg/v4-460px-Write-a-Summary-of-a-Research-Paper-Step-4.jpg)
- The important information will usually be toward the end of the paper as the authors explain their findings and conclusions.
![sample summary of research paper Step 5 Take notes summarizing sections in your own words.](https://www.wikihow.com/images/thumb/0/0f/Write-a-Summary-of-a-Research-Paper-Step-5.jpg/v4-460px-Write-a-Summary-of-a-Research-Paper-Step-5.jpg)
- Writing a summary without plagiarizing, or copying the paper, is really important. Writing notes in your own words will help you get into the mindset of relaying information in your own way.
Including Relevant Information
![sample summary of research paper Step 1 Aim to report the findings, not evaluate them.](https://www.wikihow.com/images/thumb/b/b7/Write-a-Summary-of-a-Research-Paper-Step-6.jpg/v4-460px-Write-a-Summary-of-a-Research-Paper-Step-6.jpg)
- For example, “The methods used in this paper are not up to standards and require more testing to be conclusive.” is an analysis.
- ”The methods used in this paper include an in-depth survey and interview session with each candidate.” is a summary.
![sample summary of research paper Step 2 Keep your summary brief.](https://www.wikihow.com/images/thumb/5/52/Write-a-Summary-of-a-Research-Paper-Step-7.jpg/v4-460px-Write-a-Summary-of-a-Research-Paper-Step-7.jpg)
- If you’re writing a summary for class, your professor may specify how long your summary should be.
- Some summaries can even be as short as one sentence.
![sample summary of research paper Step 3 State the research question and hypothesis.](https://www.wikihow.com/images/thumb/6/6e/Write-a-Summary-of-a-Research-Paper-Step-8.jpg/v4-460px-Write-a-Summary-of-a-Research-Paper-Step-8.jpg)
- ”Environmental conditions in North Carolina pose a threat to frogs and toads.”
![sample summary of research paper Step 4 Describe the testing and analyzation methods.](https://www.wikihow.com/images/thumb/a/a0/Write-a-Summary-of-a-Research-Paper-Step-9.jpg/v4-460px-Write-a-Summary-of-a-Research-Paper-Step-9.jpg)
- For example: “According to the climate model, frog and toad populations have been decreasing at a rapid rate over the past 10 years, and are on track to decrease even further in the coming years.”
![sample summary of research paper Step 5 Talk about the results and how significant they were.](https://www.wikihow.com/images/thumb/8/8d/Write-a-Summary-of-a-Research-Paper-Step-10.jpg/v4-460px-Write-a-Summary-of-a-Research-Paper-Step-10.jpg)
- For example: “Smith and Herman (2008) argue that by decreasing greenhouse gases, frog and toad populations could reach historical levels within 20 years, and the climate model projections support that statement.”
- You can add in the authors and year of publication at any time during your summary.
![sample summary of research paper Step 6 Edit your summary for accuracy and flow.](https://www.wikihow.com/images/thumb/7/70/Write-a-Summary-of-a-Research-Paper-Step-11.jpg/v4-460px-Write-a-Summary-of-a-Research-Paper-Step-11.jpg)
- If you have time, try reading your summary to someone who hasn’t read the original paper and see if they understand the key points of the article.
Expert Q&A
- Make sure you fully understand the paper before you start writing the summary. Thanks Helpful 2 Not Helpful 0
- Plagiarism can have serious consequences in the academic world, so make sure you’re writing your summary in your own words. [12] X Research source Thanks Helpful 0 Not Helpful 0
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- ↑ https://writingcenter.uconn.edu/wp-content/uploads/sites/593/2014/06/How_to_Summarize_a_Research_Article1.pdf
- ↑ https://www.ufv.ca/media/assets/academic-success-centre/handouts/Summarizing-a-Scholarly-Journal-Article-rev2018.pdf
- ↑ https://integrity.mit.edu/handbook/academic-writing/summarizing
- ↑ https://writingcenter.unc.edu/tips-and-tools/summary-using-it-wisely/
- ↑ https://davidson.libguides.com/c.php?g=349327&p=2361763
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An executive summary is a thorough overview of a research report or other type of document that synthesizes key points for its readers, saving them time and preparing them to understand the study's overall content. It is a separate, stand-alone document of sufficient detail and clarity to ensure that the reader can completely understand the contents of the main research study. An executive summary can be anywhere from 1-10 pages long depending on the length of the report, or it can be the summary of more than one document [e.g., papers submitted for a group project].
Bailey, Edward, P. The Plain English Approach to Business Writing . (New York: Oxford University Press, 1997), p. 73-80 Todorovic, Zelimir William and Marietta Wolczacka Frye. “Writing Effective Executive Summaries: An Interdisciplinary Examination.” In United States Association for Small Business and Entrepreneurship. Conference Proceedings . (Decatur, IL: United States Association for Small Business and Entrepreneurship, 2009): pp. 662-691.
Importance of a Good Executive Summary
Although an executive summary is similar to an abstract in that they both summarize the contents of a research study, there are several key differences. With research abstracts, the author's recommendations are rarely included, or if they are, they are implicit rather than explicit. Recommendations are generally not stated in academic abstracts because scholars operate in a discursive environment, where debates, discussions, and dialogs are meant to precede the implementation of any new research findings. The conceptual nature of much academic writing also means that recommendations arising from the findings are distributed widely and not easily or usefully encapsulated. Executive summaries are used mainly when a research study has been developed for an organizational partner, funding entity, or other external group that participated in the research . In such cases, the research report and executive summary are often written for policy makers outside of academe, while abstracts are written for the academic community. Professors, therefore, assign the writing of executive summaries so students can practice synthesizing and writing about the contents of comprehensive research studies for external stakeholder groups.
When preparing to write, keep in mind that:
- An executive summary is not an abstract.
- An executive summary is not an introduction.
- An executive summary is not a preface.
- An executive summary is not a random collection of highlights.
Christensen, Jay. Executive Summaries Complete The Report. California State University Northridge; Clayton, John. "Writing an Executive Summary that Means Business." Harvard Management Communication Letter (July 2003): 2-4; Keller, Chuck. "Stay Healthy with a Winning Executive Summary." Technical Communication 41 (1994): 511-517; Murphy, Herta A., Herbert W. Hildebrandt, and Jane P. Thomas. Effective Business Communications . New York: McGraw-Hill, 1997; Vassallo, Philip. "Executive Summaries: Where Less Really is More." ETC.: A Review of General Semantics 60 (Spring 2003): 83-90 .
Structure and Writing Style
Writing an Executive Summary
Read the Entire Document This may go without saying, but it is critically important that you read the entire research study thoroughly from start to finish before you begin to write the executive summary. Take notes as you go along, highlighting important statements of fact, key findings, and recommended courses of action. This will better prepare you for how to organize and summarize the study. Remember this is not a brief abstract of 300 words or less but, essentially, a mini-paper of your paper, with a focus on recommendations.
Isolate the Major Points Within the Original Document Choose which parts of the document are the most important to those who will read it. These points must be included within the executive summary in order to provide a thorough and complete explanation of what the document is trying to convey.
Separate the Main Sections Closely examine each section of the original document and discern the main differences in each. After you have a firm understanding about what each section offers in respect to the other sections, write a few sentences for each section describing the main ideas. Although the format may vary, the main sections of an executive summary likely will include the following:
- An opening statement, with brief background information,
- The purpose of research study,
- Method of data gathering and analysis,
- Overview of findings, and,
- A description of each recommendation, accompanied by a justification. Note that the recommendations are sometimes quoted verbatim from the research study.
Combine the Information Use the information gathered to combine them into an executive summary that is no longer than 10% of the original document. Be concise! The purpose is to provide a brief explanation of the entire document with a focus on the recommendations that have emerged from your research. How you word this will likely differ depending on your audience and what they care about most. If necessary, selectively incorporate bullet points for emphasis and brevity. Re-read your Executive Summary After you've completed your executive summary, let it sit for a while before coming back to re-read it. Check to make sure that the summary will make sense as a separate document from the full research study. By taking some time before re-reading it, you allow yourself to see the summary with fresh, unbiased eyes.
Common Mistakes to Avoid
Length of the Executive Summary As a general rule, the correct length of an executive summary is that it meets the criteria of no more pages than 10% of the number of pages in the original document, with an upper limit of no more than ten pages [i.e., ten pages for a 100 page document]. This requirement keeps the document short enough to be read by your audience, but long enough to allow it to be a complete, stand-alone synopsis. Cutting and Pasting With the exception of specific recommendations made in the study, do not simply cut and paste whole sections of the original document into the executive summary. You should paraphrase information from the longer document. Avoid taking up space with excessive subtitles and lists, unless they are absolutely necessary for the reader to have a complete understanding of the original document. Consider the Audience Although unlikely to be required by your professor, there is the possibility that more than one executive summary will have to be written for a given document [e.g., one for policy-makers, one for private industry, one for philanthropists]. This may only necessitate the rewriting of the introduction and conclusion, but it could require rewriting the entire summary in order to fit the needs of the reader. If necessary, be sure to consider the types of audiences who may benefit from your study and make adjustments accordingly. Clarity in Writing One of the biggest mistakes you can make is related to the clarity of your executive summary. Always note that your audience [or audiences] are likely seeing your research study for the first time. The best way to avoid a disorganized or cluttered executive summary is to write it after the study is completed. Always follow the same strategies for proofreading that you would for any research paper. Use Strong and Positive Language Don’t weaken your executive summary with passive, imprecise language. The executive summary is a stand-alone document intended to convince the reader to make a decision concerning whether to implement the recommendations you make. Once convinced, it is assumed that the full document will provide the details needed to implement the recommendations. Although you should resist the temptation to pad your summary with pleas or biased statements, do pay particular attention to ensuring that a sense of urgency is created in the implications, recommendations, and conclusions presented in the executive summary. Be sure to target readers who are likely to implement the recommendations.
Bailey, Edward, P. The Plain English Approach to Business Writing . (New York: Oxford University Press, 1997), p. 73-80; Christensen, Jay. Executive Summaries Complete The Report. California State University Northridge; Executive Summaries. Writing@CSU. Colorado State University; Clayton, John. "Writing an Executive Summary That Means Business." Harvard Management Communication Letter , 2003; Executive Summary. University Writing Center. Texas A&M University; Green, Duncan. Writing an Executive Summary. Oxfam’s Research Guidelines series ; Guidelines for Writing an Executive Summary. Astia.org; Markowitz, Eric. How to Write an Executive Summary. Inc. Magazine, September, 15, 2010; Kawaski, Guy. The Art of the Executive Summary. "How to Change the World" blog; Keller, Chuck. "Stay Healthy with a Winning Executive Summary." Technical Communication 41 (1994): 511-517; The Report Abstract and Executive Summary. The Writing Lab and The OWL. Purdue University; Writing Executive Summaries. Effective Writing Center. University of Maryland; Kolin, Philip. Successful Writing at Work . 10th edition. (Boston, MA: Cengage Learning, 2013), p. 435-437; Moral, Mary. "Writing Recommendations and Executive Summaries." Keeping Good Companies 64 (June 2012): 274-278; Todorovic, Zelimir William and Marietta Wolczacka Frye. “Writing Effective Executive Summaries: An Interdisciplinary Examination.” In United States Association for Small Business and Entrepreneurship. Conference Proceedings . (Decatur, IL: United States Association for Small Business and Entrepreneurship, 2009): pp. 662-691.
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One Page Research Summary
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When it comes to doing research, a lot of people may find it difficult to get it right. That often than not, they get too frustrated to even begin the research. However, what others may not have noticed is that it is not the research that gets frustrating, but it is how to summarize the entire research into a single page. When you have done good research, you often think to yourself that this would be easy to summarize but when given a specific task to summarize to a single page, you may want to think on how you can do this. Others may think that this is too impossible to fit a research summary into a single page.
But what if I told you that there is a way for you to be able to do it? Would you believe me or would you still think it is too impossible? Don’t get me wrong, there are others who do believe it to be possible, while others do not. Why don’t you try it? How do you make a whole research summary fit into a single page ? This is why the article is the one you should be checking out right now. 6+ examples to show you how to write a one page research summary.
6+ One Page Research Summary Examples
1. one page research summary template.
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7. Formal One Page Research Summary
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What Is a One Page Research Summary?
So to start off, you may still be thinking about how impossible it is to fit a whole research in a single page. But let me tell you that it is not. But first, let us define what a one page research summary is. This is a kind of document , or an academic writing. This kind of research summary holds the information that a student or an academic person has done in order to expound on what they had learned through their research. What the research may be about often targets the readers who may also want to learn more about it. In a way, instead of having to read more than a page of research summaries, the one page research summary is going to be the best fit. This way, any important information can simply be written in a general but still a very clear and concise way . This means that regardless of the single page it is written, it still does its purpose by giving the reader the information that they need.
How to Write a One Page Research Summary?
The next agenda on your list would be to know how to write a one page research summary. Have I been able to convince you yet that it is possible to write a page research summary? If I have not, you should check these tips below. By simply following these simple steps or guides , you are going to find it easier to do a page research summary.
1. Read the Chapter and Make a Draft
The best way to begin is to make a draft while you read the chapter or the chapters you are told to summarize. The whole purpose of the draft is for you to be able to concentrate on taking out the most important information . While reading the chapter or chapters, take some time to take down your own notes and place it in the draft. That way it would be easier for you to finalize everything later on.
2. Look For the Important Information From Your Draft
Apart from reading the chapters and making the draft, seek out the important information that would support your summary and your research. Make sure to not take away any information that is connected to the previous chapters and information you took from there. Your key points should also be found in your summary or in your draft. They serve as your helping hand.
3. Begin With Your Final Output
Once you have all the information written out in your draft and placed in the correct places, it is time you write your final output. Start by writing out the summary of your research. Avoid forgetting the important facts and details that you wrote in your draft. Make sure that you are also following the APA format when writing your research. This is an academic research paper, so your format should follow the APA format in writing.
4. Proofread Your Research Summary
Proofreading your work before you submit it is always the best way to check. Check whether you have added all the information you need for your research summary. As well as checking whether or not your research summary does not go beyond a single page. If it so happens that it does, make adjustments and see to it that it does not go beyond a single page. This includes the margins of your page. So be careful.
5. Cite Your Sources
The last tip I can give you is to remember to always cite your sources. Regardless of how short or how long your research summary is, you should always cite your sources. Even if you may have to say it in your own words, you must remember that doing your research, you should also state the person or the people, the book, the article that it belongs to. Avoid plagiarism at all costs. Even if you think that the words are yours, but the idea that it belongs to is not. Cite away.
What is a one page research summary?
From the term itself, it is a document or an academic paper that gives a general but concise summary of the topic you are given for research.
Why is it important to write a single page research summary?
A lot of people prefer to have to read a single page research summary over a lot of pages. It also can minimize the time wasted to look for the answers.
Why is it important to cite your sources?
Avoid any plagiarism when writing your research summary. This is the main problem and the main issue when it comes to academic papers. When you quote or state something from your research, always cite where you have taken it from or quoted it from.
This is the end of the article. Have I convinced you yet of how easy it really is to make a one page research summary? I do hope I have. As I mentioned earlier, it really is easy especially if you only have to follow the simple tips above. As well as using the examples you can download from this article. The next time you’re planning on writing a research summary, why don’t you try a one page research summary and see the difference that it makes.
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Video Transcripts: Summarizing Sources: Definition and Examples of Summary
Summarizing sources: definition and examples of summary.
Last updated 1/5/2017
Visual: The screen shows the Walden University Writing Center logo along with a pencil and notebook. “Walden University Writing Center.” “Your writing, grammar, and APA experts” appears in center of screen. The background changes to the title of the video with books in the background.
Audio: Guitar music plays.
Visual: Slide changes to the title “Summarizing Sources” and the following:
- Central thesis, argument, or purpose
- Main ideas, findings, or conclusions
Definition : An articulation of a source’s basic argument and main points.
Audio: Summary, in its simplest form, is an articulation of a source’s basic argument and main points. What this means is that it’s broad in nature. A summary doesn’t focus on one idea or fact from a source. Instead, it gives an overview of the entire source. This overview should include the source’s central thesis, argument, or purpose, as well as the source’s main ideas, findings, or conclusions. Think of this as a high-level overview of the source. Finally, you may also include the context in which the article was written. For example, you might note if an article was written in response to a government policy or refuting another study.
Visual: The slide changes to the following: What makes a strong summary?
- Balancing accuracy with concision
- High-level overview of main points
- Ensuring your voice as the author
Audio: There are a few things you can do to write a strong summary. First, your summary should be accurate. You need to make sure you are accurately representing the source and the author’s ideas in your summary. Doing so can often be a balancing act; you don’t want to include too many details, but you do need to include enough information so that you can accurately convey what the source said to your reader. Think about your summary in this way: If you were giving a colleague the gist of the article, what main points would you include to ensure he or she understood the overall points of the source?
Next, your summary should be concise. Because a summary is a high-level overview and broad in scope, a summary will be longer than a paraphrase. A paraphrase is a concise rephrasing of a particular idea or piece of information in one or at most two sentences. As a result, even a concise summary will be longer than a paraphrase, at least a couple of sentences long. However, your summary shouldn’t be too long either; most of the time you should be able to summarize a source in one paragraph. However, the length of your summary will always depend on the length of the original source and the level of detail you need based on your assignment’s guidelines.
Finally, your summary should use paraphrases, not quotes. Because summaries are a high-level overview, put the source’s information into your own words, rather than quoting the original source. Doing so will help increase the flow of your summary and ensure your voice as the author comes through. Paraphrasing rather than quoting will also help you keep your summary concise. There could be scenarios where you might want to partially quote a key phrase, but even that should be done sparingly.
Visual: The slide changes to the following:
In their research, DeBruin-Parecki and Slutzky’s (2016) studied current U.S. pre-K standards, which are meant to set up students for success in kindergarten and beyond. The authors collected quantitative and qualitative data from diverse survey respondents about pre-K learning standards. The key finding from this study was the positive viewpoint most pre-K teachers have of the national learning standards.
Audio: Let’s take a look at this sample summary. As you can see, this summary is a high-level overview of this source. It starts by introducing the source’s authors with a full citation and introducing the topic or focus of the source. It then transitions to discussing the data the authors collected, ending with the authors’ key finding.
This sample summary is accurate, concise, and includes paraphrased main ideas, the three things that make a strong summary. It accurately represents the source authors’ original ideas, while still being concise. The summary’s author also put all of these ideas into their own words.
Visual: The following are overlayed on the paragraph: “the authors” or “this study”
Audio: The final note I want to make here is about citations. It’s important to cite the source in the first sentence of the summary. In subsequent sentences, the citation isn’t necessarily required, although it is important to ensure the reader knows you’re continuing to discuss the same source. This might mean using phrases like “the authors” or “this study”, but you may also include citations in each of these sentences too.
If you’re not sure whether you should cite the source in each sentence in a summary, be sure to ask your instructor.
- Annotated bibliographies
- Compare/contrast essays
- Explicit requests
- Part of note taking
- Synthesizing or paraphrasing sources
- Literature reviews
- Graduate writing
Audio: Alright, so now that you know what a summary is and how to write a strong summary, when should you use a summary? Students most commonly summarize sources in annotated bibliographies and compare/contrast essays. However, you may also find that an assignment prompt or course instructor asks you to summarize as part of another assignment. You may also use summarizing as one of your note-taking and reading strategies; summarizing a source is a great way to ensure you understand and can re-articulate what a source is saying.
It is important to note that summarizing usually isn’t appropriate if you’re being asked to synthesize or paraphrase a source; this is particularly true in a literature review and generally in graduate writing. While summarizing particularly important sources initially or in the note taking stage may make sense in these cases, you don’t want to rely on summarizing extensively.
Visual: Slide changes to display the following: Questions? E-mail [email protected] .
- Previous Page: Summarizing Sources: The Process of Summarizing
- Next Page: Summarizing Sources: Incorporating Citations Into Summaries
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How to Write a Research Proposal: (with Examples & Templates)
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Table of Contents
Before conducting a study, a research proposal should be created that outlines researchers’ plans and methodology and is submitted to the concerned evaluating organization or person. Creating a research proposal is an important step to ensure that researchers are on track and are moving forward as intended. A research proposal can be defined as a detailed plan or blueprint for the proposed research that you intend to undertake. It provides readers with a snapshot of your project by describing what you will investigate, why it is needed, and how you will conduct the research.
Your research proposal should aim to explain to the readers why your research is relevant and original, that you understand the context and current scenario in the field, have the appropriate resources to conduct the research, and that the research is feasible given the usual constraints.
This article will describe in detail the purpose and typical structure of a research proposal , along with examples and templates to help you ace this step in your research journey.
What is a Research Proposal ?
A research proposal¹ ,² can be defined as a formal report that describes your proposed research, its objectives, methodology, implications, and other important details. Research proposals are the framework of your research and are used to obtain approvals or grants to conduct the study from various committees or organizations. Consequently, research proposals should convince readers of your study’s credibility, accuracy, achievability, practicality, and reproducibility.
With research proposals , researchers usually aim to persuade the readers, funding agencies, educational institutions, and supervisors to approve the proposal. To achieve this, the report should be well structured with the objectives written in clear, understandable language devoid of jargon. A well-organized research proposal conveys to the readers or evaluators that the writer has thought out the research plan meticulously and has the resources to ensure timely completion.
Purpose of Research Proposals
A research proposal is a sales pitch and therefore should be detailed enough to convince your readers, who could be supervisors, ethics committees, universities, etc., that what you’re proposing has merit and is feasible . Research proposals can help students discuss their dissertation with their faculty or fulfill course requirements and also help researchers obtain funding. A well-structured proposal instills confidence among readers about your ability to conduct and complete the study as proposed.
Research proposals can be written for several reasons:³
- To describe the importance of research in the specific topic
- Address any potential challenges you may encounter
- Showcase knowledge in the field and your ability to conduct a study
- Apply for a role at a research institute
- Convince a research supervisor or university that your research can satisfy the requirements of a degree program
- Highlight the importance of your research to organizations that may sponsor your project
- Identify implications of your project and how it can benefit the audience
What Goes in a Research Proposal?
Research proposals should aim to answer the three basic questions—what, why, and how.
The What question should be answered by describing the specific subject being researched. It should typically include the objectives, the cohort details, and the location or setting.
The Why question should be answered by describing the existing scenario of the subject, listing unanswered questions, identifying gaps in the existing research, and describing how your study can address these gaps, along with the implications and significance.
The How question should be answered by describing the proposed research methodology, data analysis tools expected to be used, and other details to describe your proposed methodology.
Research Proposal Example
Here is a research proposal sample template (with examples) from the University of Rochester Medical Center. 4 The sections in all research proposals are essentially the same although different terminology and other specific sections may be used depending on the subject.
![sample summary of research paper Research Proposal Template](https://pp-blog.paperpal.com/wp-content/uploads/2024/07/Research-proposal-Template-1-2_page-00011-scaled.jpg)
Structure of a Research Proposal
If you want to know how to make a research proposal impactful, include the following components:¹
1. Introduction
This section provides a background of the study, including the research topic, what is already known about it and the gaps, and the significance of the proposed research.
2. Literature review
This section contains descriptions of all the previous relevant studies pertaining to the research topic. Every study cited should be described in a few sentences, starting with the general studies to the more specific ones. This section builds on the understanding gained by readers in the Introduction section and supports it by citing relevant prior literature, indicating to readers that you have thoroughly researched your subject.
3. Objectives
Once the background and gaps in the research topic have been established, authors must now state the aims of the research clearly. Hypotheses should be mentioned here. This section further helps readers understand what your study’s specific goals are.
4. Research design and methodology
Here, authors should clearly describe the methods they intend to use to achieve their proposed objectives. Important components of this section include the population and sample size, data collection and analysis methods and duration, statistical analysis software, measures to avoid bias (randomization, blinding), etc.
5. Ethical considerations
This refers to the protection of participants’ rights, such as the right to privacy, right to confidentiality, etc. Researchers need to obtain informed consent and institutional review approval by the required authorities and mention this clearly for transparency.
6. Budget/funding
Researchers should prepare their budget and include all expected expenditures. An additional allowance for contingencies such as delays should also be factored in.
7. Appendices
This section typically includes information that supports the research proposal and may include informed consent forms, questionnaires, participant information, measurement tools, etc.
8. Citations
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Important Tips for Writing a Research Proposal
Writing a research proposal begins much before the actual task of writing. Planning the research proposal structure and content is an important stage, which if done efficiently, can help you seamlessly transition into the writing stage. 3,5
The Planning Stage
- Manage your time efficiently. Plan to have the draft version ready at least two weeks before your deadline and the final version at least two to three days before the deadline.
- What is the primary objective of your research?
- Will your research address any existing gap?
- What is the impact of your proposed research?
- Do people outside your field find your research applicable in other areas?
- If your research is unsuccessful, would there still be other useful research outcomes?
The Writing Stage
- Create an outline with main section headings that are typically used.
- Focus only on writing and getting your points across without worrying about the format of the research proposal , grammar, punctuation, etc. These can be fixed during the subsequent passes. Add details to each section heading you created in the beginning.
- Ensure your sentences are concise and use plain language. A research proposal usually contains about 2,000 to 4,000 words or four to seven pages.
- Don’t use too many technical terms and abbreviations assuming that the readers would know them. Define the abbreviations and technical terms.
- Ensure that the entire content is readable. Avoid using long paragraphs because they affect the continuity in reading. Break them into shorter paragraphs and introduce some white space for readability.
- Focus on only the major research issues and cite sources accordingly. Don’t include generic information or their sources in the literature review.
- Proofread your final document to ensure there are no grammatical errors so readers can enjoy a seamless, uninterrupted read.
- Use academic, scholarly language because it brings formality into a document.
- Ensure that your title is created using the keywords in the document and is neither too long and specific nor too short and general.
- Cite all sources appropriately to avoid plagiarism.
- Make sure that you follow guidelines, if provided. This includes rules as simple as using a specific font or a hyphen or en dash between numerical ranges.
- Ensure that you’ve answered all questions requested by the evaluating authority.
Key Takeaways
Here’s a summary of the main points about research proposals discussed in the previous sections:
- A research proposal is a document that outlines the details of a proposed study and is created by researchers to submit to evaluators who could be research institutions, universities, faculty, etc.
- Research proposals are usually about 2,000-4,000 words long, but this depends on the evaluating authority’s guidelines.
- A good research proposal ensures that you’ve done your background research and assessed the feasibility of the research.
- Research proposals have the following main sections—introduction, literature review, objectives, methodology, ethical considerations, and budget.
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Frequently Asked Questions
Q1. How is a research proposal evaluated?
A1. In general, most evaluators, including universities, broadly use the following criteria to evaluate research proposals . 6
- Significance —Does the research address any important subject or issue, which may or may not be specific to the evaluator or university?
- Content and design —Is the proposed methodology appropriate to answer the research question? Are the objectives clear and well aligned with the proposed methodology?
- Sample size and selection —Is the target population or cohort size clearly mentioned? Is the sampling process used to select participants randomized, appropriate, and free of bias?
- Timing —Are the proposed data collection dates mentioned clearly? Is the project feasible given the specified resources and timeline?
- Data management and dissemination —Who will have access to the data? What is the plan for data analysis?
Q2. What is the difference between the Introduction and Literature Review sections in a research proposal ?
A2. The Introduction or Background section in a research proposal sets the context of the study by describing the current scenario of the subject and identifying the gaps and need for the research. A Literature Review, on the other hand, provides references to all prior relevant literature to help corroborate the gaps identified and the research need.
Q3. How long should a research proposal be?
A3. Research proposal lengths vary with the evaluating authority like universities or committees and also the subject. Here’s a table that lists the typical research proposal lengths for a few universities.
Arts programs | 1,000-1,500 | |
University of Birmingham | Law School programs | 2,500 |
PhD | 2,500 | |
2,000 | ||
Research degrees | 2,000-3,500 |
Q4. What are the common mistakes to avoid in a research proposal ?
A4. Here are a few common mistakes that you must avoid while writing a research proposal . 7
- No clear objectives: Objectives should be clear, specific, and measurable for the easy understanding among readers.
- Incomplete or unconvincing background research: Background research usually includes a review of the current scenario of the particular industry and also a review of the previous literature on the subject. This helps readers understand your reasons for undertaking this research because you identified gaps in the existing research.
- Overlooking project feasibility: The project scope and estimates should be realistic considering the resources and time available.
- Neglecting the impact and significance of the study: In a research proposal , readers and evaluators look for the implications or significance of your research and how it contributes to the existing research. This information should always be included.
- Unstructured format of a research proposal : A well-structured document gives confidence to evaluators that you have read the guidelines carefully and are well organized in your approach, consequently affirming that you will be able to undertake the research as mentioned in your proposal.
- Ineffective writing style: The language used should be formal and grammatically correct. If required, editors could be consulted, including AI-based tools such as Paperpal , to refine the research proposal structure and language.
Thus, a research proposal is an essential document that can help you promote your research and secure funds and grants for conducting your research. Consequently, it should be well written in clear language and include all essential details to convince the evaluators of your ability to conduct the research as proposed.
This article has described all the important components of a research proposal and has also provided tips to improve your writing style. We hope all these tips will help you write a well-structured research proposal to ensure receipt of grants or any other purpose.
References
- Sudheesh K, Duggappa DR, Nethra SS. How to write a research proposal? Indian J Anaesth. 2016;60(9):631-634. Accessed July 15, 2024. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5037942/
- Writing research proposals. Harvard College Office of Undergraduate Research and Fellowships. Harvard University. Accessed July 14, 2024. https://uraf.harvard.edu/apply-opportunities/app-components/essays/research-proposals
- What is a research proposal? Plus how to write one. Indeed website. Accessed July 17, 2024. https://www.indeed.com/career-advice/career-development/research-proposal
- Research proposal template. University of Rochester Medical Center. Accessed July 16, 2024. https://www.urmc.rochester.edu/MediaLibraries/URMCMedia/pediatrics/research/documents/Research-proposal-Template.pdf
- Tips for successful proposal writing. Johns Hopkins University. Accessed July 17, 2024. https://research.jhu.edu/wp-content/uploads/2018/09/Tips-for-Successful-Proposal-Writing.pdf
- Formal review of research proposals. Cornell University. Accessed July 18, 2024. https://irp.dpb.cornell.edu/surveys/survey-assessment-review-group/research-proposals
- 7 Mistakes you must avoid in your research proposal. Aveksana (via LinkedIn). Accessed July 17, 2024. https://www.linkedin.com/pulse/7-mistakes-you-must-avoid-your-research-proposal-aveksana-cmtwf/
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Molecular mimicry in multisystem inflammatory syndrome in children
- Aaron Bodansky ORCID: orcid.org/0000-0001-8943-8233 1 na1 ,
- Robert C. Mettelman ORCID: orcid.org/0000-0002-3527-5616 2 na1 ,
- Joseph J. Sabatino Jr 3 , 4 ,
- Sara E. Vazquez 5 ,
- Janet Chou 6 , 7 ,
- Tanya Novak ORCID: orcid.org/0000-0002-7115-7545 8 , 9 ,
- Kristin L. Moffitt 7 , 10 ,
- Haleigh S. Miller 5 , 11 ,
- Andrew F. Kung 5 , 11 ,
- Elze Rackaityte ORCID: orcid.org/0000-0003-3889-8082 5 ,
- Colin R. Zamecnik ORCID: orcid.org/0000-0002-9477-1388 3 , 4 ,
- Jayant V. Rajan 5 ,
- Hannah Kortbawi 5 , 12 ,
- Caleigh Mandel-Brehm 5 ,
- Anthea Mitchell 13 ,
- Chung-Yu Wang 13 ,
- Aditi Saxena 13 ,
- Kelsey Zorn ORCID: orcid.org/0000-0003-1227-2137 5 ,
- David J. L. Yu 14 ,
- Mikhail V. Pogorelyy 2 ,
- Walid Awad 2 ,
- Allison M. Kirk ORCID: orcid.org/0000-0002-4286-3678 2 ,
- James Asaki 15 ,
- John V. Pluvinage ORCID: orcid.org/0000-0002-9607-2783 4 ,
- Michael R. Wilson ORCID: orcid.org/0000-0002-8705-5084 3 , 4 ,
- Laura D. Zambrano 16 ,
- Angela P. Campbell ORCID: orcid.org/0000-0002-2576-482X 16 ,
- Overcoming COVID-19 Network Investigators ,
- Paul G. Thomas ORCID: orcid.org/0000-0001-7955-0256 2 na2 ,
- Adrienne G. Randolph 7 , 8 , 9 na2 ,
- Mark S. Anderson ORCID: orcid.org/0000-0002-3093-4758 14 , 17 na2 &
- Joseph L. DeRisi ORCID: orcid.org/0000-0002-4611-9205 5 , 13 na2
Nature volume 632 , pages 622–629 ( 2024 ) Cite this article
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- Autoimmunity
- Autoinflammatory syndrome
- Immune tolerance
- Inflammation
- Viral infection
Multisystem inflammatory syndrome in children (MIS-C) is a severe, post-infectious sequela of SARS-CoV-2 infection 1 , 2 , yet the pathophysiological mechanism connecting the infection to the broad inflammatory syndrome remains unknown. Here we leveraged a large set of samples from patients with MIS-C to identify a distinct set of host proteins targeted by patient autoantibodies including a particular autoreactive epitope within SNX8, a protein involved in regulating an antiviral pathway associated with MIS-C pathogenesis. In parallel, we also probed antibody responses from patients with MIS-C to the complete SARS-CoV-2 proteome and found enriched reactivity against a distinct domain of the SARS-CoV-2 nucleocapsid protein. The immunogenic regions of the viral nucleocapsid and host SNX8 proteins bear remarkable sequence similarity. Consequently, we found that many children with anti-SNX8 autoantibodies also have cross-reactive T cells engaging both the SNX8 and the SARS-CoV-2 nucleocapsid protein epitopes. Together, these findings suggest that patients with MIS-C develop a characteristic immune response to the SARS-CoV-2 nucleocapsid protein that is associated with cross-reactivity to the self-protein SNX8, demonstrating a mechanistic link between the infection and the inflammatory syndrome, with implications for better understanding a range of post-infectious autoinflammatory diseases.
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Diverse functional autoantibodies in patients with COVID-19
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SARS-CoV-2 immune repertoire in MIS-C and pediatric COVID-19
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Immunology of SARS-CoV-2 infection in children
Children with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections typically have mild disease 3 , 4 , but can develop a rare life-threatening post-infectious complication known as MIS-C 1 , 2 . MIS-C presents with a distinctive inflammatory signature indicative of altered innate immune responses 5 , 6 , including dysregulation of the mitochondrial antiviral signalling (MAVS) protein pathway 7 . Aberrant adaptive immunity is also involved, with multiple MIS-C-associated autoantibodies reported 8 , 9 , 10 , 11 , 12 . Furthermore, T cell signatures have also been associated with development of MIS-C 13 , 14 , 15 , 16 , which are accompanied by autoimmune-associated B cell expansions 8 . Some autoimmune diseases have been shown to involve tandem cross-reactive B cell and T cell responses. In multiple sclerosis, for example, cross-reactive B cells and T cells have been shown to respond to Epstein–Barr virus protein (EBNA1) and antigens in the human nervous system 17 , 18 , 19 . Decades of research into paraneoplastic autoimmune encephalitis has also demonstrated that autoreactive B cells and T cells can cause disease through coordinated targeting of a shared intracellular antigen and, in certain cases, a shared epitope 20 , 21 , 22 , 23 , 24 , 25 , 26 . Despite intense interest, a pathophysiological link between SARS-CoV-2 and MIS-C remains enigmatic, and identification of disease-specific autoantigens remains incompletely explored. Here children previously infected with SARS-CoV-2 with ( n = 199) and without ( n = 45) MIS-C were enrolled and comprehensively evaluated for differential autoreactivity to the entire human and SARS-CoV-2 proteome. Patients with MIS-C were found to have both cross-reactive antibodies and T cells targeting an epitope motif shared by the viral nucleocapsid protein and human SNX8, a protein involved in MAVS antiviral function 27 . These findings suggest that many cases of MIS-C may be triggered by molecular mimicry and could provide a framework for identifying potential cross-reactive epitopes in other autoimmune and inflammatory diseases with predicted viral triggers such as Kawasaki disease 28 , type 1 diabetes mellitus (T1DM) 29 and multiple sclerosis.
Patients with MIS-C have a distinct set of autoreactivities
To explore the hypothesis that MIS-C is driven by an autoreactive process, we evaluated the proteome-wide autoantibody profiles of children with MIS-C ( n = 199) and children convalescing following asymptomatic or mild SARS-CoV-2 infection without MIS-C ( n = 45, hereafter referred to as ‘at-risk controls’) using our custom phage immunoprecipitation and sequencing (PhIP-seq) 30 library, which has previously been used to define novel autoimmune syndromes and markers of disease for various conditions 12 , 24 , 25 , 31 , 32 , 33 . Given the inherently heterogeneous nature of antibody repertoires among individuals 34 , the identification of disease-associated autoreactive antigens requires the use of large numbers of cases and controls 12 . To minimize spurious hits, this study includes substantially more patients with MIS-C and controls than similar, previously published studies 8 , 9 , 10 , 12 (Fig. 1a ). Clinical characteristics of this cohort are described in Extended Data Table 1 .
![sample summary of research paper figure 1](https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41586-024-07722-4/MediaObjects/41586_2024_7722_Fig1_HTML.png)
a , Design of the PhIP-seq experiment comparing patients with MIS-C ( n = 199) and at-risk controls ( n = 45; children with SARS-CoV-2 infection at least 5 weeks before sample collection without symptoms of MIS-C). Schematics in panel a were created using BioRender ( https://www.biorender.com ). b , Venn diagram highlighting the number of autoantigens identified with statistically significant PhIP-seq enrichment (‘enrichment set’: grey circle; P < 0.01 on one-sided Kolmogorov–Smirnov test with false discovery rate correction) and autoantigens identified, which contribute to a logistic regression classifier of MIS-C relative to at-risk controls (‘classifier set’: purple circle). There are 35 autoantigens present in both the classifier set and the enrichment set (pink; union of the Venn diagram) of which 30 are exclusive to MIS-C and referred to as the ‘MIS-C set’ (no two controls have low reactivity as defined by the fold-change (FC) signal over the mean of protein A/G beads only (FC > mock-IP) of 3 or greater, and no single control has high reactivity defined as FC > mock-IP greater than 10). LR, logistic regression. c , Receiver operating characteristic curve for the logistic regression classifier showing upper and lower bounds of performance through 1,000 iterations. d , Bar plots with error bars showing logistic regression coefficients for the top 10 autoantigens across 1,000 iterations. The whiskers extend to 1.5 times the interquartile range (IQR) from the quartiles. The boxes represent the IQR, and the centre lines represent the median. e , Hierarchically clustered (Pearson) heatmap showing the PhIP-seq enrichment (FC > mock-IP) for the 30 autoantigens in the MIS-C set in each patient with MIS-C and each at-risk plasma control.
Source Data
For a given set of samples, PhIP-seq can yield dozens to thousands of differential enrichments of phage-displayed peptides. Here logistic regression machine learning was used as an initial unbiased measure of how accurately a set of differentially enriched peptides could classify people with MIS-C and controls—an approach that has been used to classify people with autoimmune polyglandular syndrome type 1 using PhIP-seq data 12 . In all, 107 proteins had logistic regression coefficients greater than zero (‘classifier set’; Fig. 1b ). As this is an unbalanced dataset with a random accuracy less than 50%, we also generated a receiver operating characteristic (ROC) curve. ROC analysis iterated 1,000 times and yielded an average area under the curve (AUC) of 0.94 (Fig. 1c ). Examination of the logistic regression coefficients associated with MIS-C revealed the largest contributions from peptides derived from the ETS repressor factor-like (ERFL), sorting nexin 8 (SNX8) and KDEL endoplasmic reticulum protein retention receptor 1 (KDELR1) coding sequences (Fig. 1d ).
In parallel, a Kolmogorov–Smirnov test was used to define a set of 661 autoreactivities statistically enriched after false discovery rate adjustment for multiple comparisons ( q < 0.01; ‘enrichment set’). To avoid false positives, the intersection of the classifier set and enrichment set were considered further. Of these 35 hits, peptides derived from 30 different proteins satisfied an additional set of conservative criteria, requiring that none was enriched (fold change over mock-immunoprecipitation (IP) of more than 3) in more than a single control, or was enriched more than 10-fold in any control (‘MIS-C set’; Fig. 1e ).
Previously reported MIS-C autoantibodies
To date, at least 34 autoantigen candidates have been reported to associate with MIS-C 8 , 9 , 10 , 12 . However, we found that only UBE3A (a ubiquitously expressed ubiquitin protein ligase) was differentially enriched in our MIS-C dataset, whereas the remaining 33 were present in a similar proportion of cases with MIS-C and at-risk controls (Extended Data Fig. 1a ). Autoreactivity to UBE3A was independently identified in this study as part of both the classifier and the enrichment sets, but was not included in the final MIS-C set due to the low positive signal present in two controls.
In addition, autoantibodies to the receptor antagonist IL-1RA have been previously reported in 13 of 21 (62%) patients with MIS-C 11 . In this cohort, anti-IL-1RA antibodies were detected by PhIP-seq ( z score > 6 over at-risk control) in six patient samples. To further examine immune reactivity to full-length IL-1RA, sera from 196 of the 199 patients in this study were used to immunoprecipitate [35S]-methionine-radiolabelled IL-1RA (radioligand-binding assay (RLBA)). Positive immunoprecipitation of IL-1RA (defined as more than 3 s.d. above mean of controls) was found in 39 of 196 (19.9%) patients with MIS-C. However, many patients with MIS-C were treated with intravenous immunoglobulin (IVIG), a blood product shown to contain autoantibodies 35 . After removing samples from patients treated with IVIG (61 remaining), the difference between samples from patients with MIS-C (5 of 61, 8.2%) and at-risk controls (1 of 45, 2.2%) was not significant ( P = 0.299; Extended Data Fig. 1b ).
MIS-C autoantigens lack tissue-specific associations with clinical phenotypes
Consistent with previous MIS-C reports 1 , 5 , this cohort was clinically heterogeneous (Extended Data Table 2 ). To determine whether specific phenotypes, including myocarditis and the requirement of vasopressors, might be associated with specific autoantigens present in the MIS-C set, tissue expression levels were assigned to each autoantigen 36 (Human Protein Atlas; https://proteinatlas.org ), including the amount of expression in cardiomyocytes and the cardiac endothelium. The PhIP-seq signal for patients with MIS-C with a particular phenotype was compared with those patients with MIS-C without the phenotype. Autoantigens with tissue specificity were not enriched in those patients with MIS-C with phenotypes involving said tissue. Similarly, autoantigens associated with myocarditis or vasopressor requirements did not correlate with increased cardiac expression (Extended Data Fig. 1c ).
Orthogonal validation of PhIP-seq autoantigens
Peptides derived from ERFL, SNX8 and KDELR1 carried the largest logistic regression coefficients in the MIS-C classifier. The PhIP-seq results were orthogonally confirmed by RLBAs using full-length ERFL, SNX8 and KDELR1 proteins. Relative to at-risk controls, samples from patients with MIS-C significantly enriched each of the three target proteins ( P < 1 × 10 −10 for ERFL, SNX8 and KDELR1), consistent with the PhIP-seq assay (Extended Data Fig. 2a ). Using only the RLBA data for these three proteins, MIS-C could be confidently classified (ROC with fivefold cross-validation; 1,000 iterations) from at-risk control sera with an AUC of 0.93, suggesting the potential for molecular diagnostic purposes (Extended Data Fig. 2b ).
As noted, IVIG was administered to 138 of the 199 patients with MIS-C before sample collection and was absent from all 45 at-risk controls. The autoreactivity to the ERFL, SNX8 and KDELR1 proteins from the 61 patients with MIS-C who had not been treated with IVIG before sample collection were compared with the at-risk controls. In contrast to IL-1RA, the differential enrichment of these three proteins remained significant ( P = 6.69 × 10 −10 , P = 6.26 × 10 −5 and P = 0.0001, respectively), suggesting that autoreactivity to ERFL, SNX8 and KDELR1 proteins was not confounded by IVIG treatment (Extended Data Fig. 2c ).
Independent MIS-C cohort validation
To further test the validity of these findings, an independent validation cohort consisting of samples from 24 different patients with MIS-C and 29 children with severe acute COVID-19 was evaluated (acquired via ongoing enrolment of the Overcoming COVID-19 study; Extended Data Table 3 ). Using RLBAs with full-length ERFL, SNX8 and KDELR1 proteins, we found that all three target proteins were significantly enriched compared with both the at-risk controls ( P = 0.00022, P = 3.68 × 10 −5 and P = 2.36 × 10 −5 , respectively) and the patients with severe acute COVID-19 ( P = 0.0066, P = 0.00735 and P = 0.00114, respectively; Extended Data Fig. 2d ). A logistic regression model, trained on the original cohort, classified MIS-C from at-risk controls with an AUC of 0.84, and from severe acute paediatric COVID-19 with an AUC of 0.78 (Extended Data Fig. 2e ). This suggests that autoreactivity to ERFL, SNX8 and KDELR1 is a significant feature of MIS-C that is separable from SARS-CoV-2 exposure and severe acute paediatric COVID-19.
MIS-C autoantibodies target a single epitope within the SNX8 protein
SNX8 is a protein that is 456 amino acids and belongs to a family of sorting nexins involved in endocytosis, endosomal sorting and signalling 37 . Publicly available expression data 36 (Human Protein Atlas) show that SNX8 is widely expressed across various tissues including the brain, heart, gastrointestinal tract, kidneys and skin, with the highest expression in undifferentiated cells and immune cells. Previous work has associated SNX8 with host defence against RNA viruses 27 . ERFL is a poorly characterized 354-amino acid protein. A survey of single-cell RNA sequencing (scRNA-seq) data 36 (Human Protein Atlas) suggests enrichment in plasma cells, B cells and T cells in some tissues. Using a Spearman correlation in principal component analysis (PCA) space based on tissue RNA-seq data 36 (Human Protein Atlas), SNX8 has the second closest expression pattern to ERFL compared with all other coding genes, with a correlation coefficient of 0.81. KDELR1 is a 212-amino acid endoplasmic reticulum–Golgi transport protein essential to lymphocyte development with low tissue expression specificity. All three proteins are predicted to be intracellular, suggesting that putative autoantibodies targeting these proteins are unlikely to be sufficient for disease pathology on their own. However, autoantibodies targeting intracellular antigens are often accompanied by autoreactive T cells specific for the protein from which that antigen was derived, and which targets cell types expressing the protein 22 , 25 , 26 , 38 . We selected SNX8 for further investigation, given its enrichment in immune cells and its putative role in regulating the MAVS pathway in response to RNA virus infection, a pathway implicated in MIS-C pathology 7 .
Full-length SNX8 is represented in this PhIP-seq library by 19 overlapping 49-mer peptides. For all but one patient sample, the peptide fragment spanning amino acid positions 25–73 was the most enriched in the PhIP-seq assay (Fig. 2a ), suggesting a common autoreactive site. A sequential alanine scan was performed to determine the minimal immunoreactive peptide sequence (Fig. 2b ; Methods ). Using samples from six individuals with MIS-C, we determined that the critical region for immunoreactivity was a nonamer spanning positions 51–59 (PSRMQMPQG). Using the wild-type 49-amino acid peptide and the version with the critical region mutated to alanine, 182 of the 199 patients with MIS-C (insufficient sample for the remaining 17) and all 45 controls were assessed for immunoreactivity using a split-luciferase-binding assay (SLBA). We found that samples from 31 of 182 (17.0%) patients with MIS-C immunoprecipitated the wild-type fragment. Of these, 29 (93.5%) failed to immunoprecipitate the mutated peptide, suggesting a common shared autoreactive epitope among nearly all of the patients with MIS-C with anti-SNX8 antibodies (Extended Data Fig. 2f ).
![sample summary of research paper figure 2](https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41586-024-07722-4/MediaObjects/41586_2024_7722_Fig2_HTML.png)
a , PhIP-seq signal (reads per 100,000) for each patient with MIS-C ( n = 199) and each at-risk control ( n = 45) across each of the 19 bacteriophage-encoded peptide fragments, which together tile the full-length SNX8 protein. b , SLBA enrichments (normalized antibody indices) for each sequential alanine mutagenesis construct. Constructs were designed with 10 amino acid alanine windows (highlighted in purple) shifted by 5 amino acids until the entire immunodominant SNX8 region (SNX8 fragment 2) was scanned. Values are averages of six separate patients with MIS-C. The identified autoantibody epitope is bounded by vertical grey dotted lines.
Patients with MIS-C have an altered antibody response to the SARS-CoV-2 nucleocapsid protein
To evaluate whether differences exist in the humoral immune response to SARS-CoV-2 infection in patients with MIS-C relative to at-risk controls, we repeated PhIP-seq with 181 of the original 199 patients with MIS-C and all 45 of the at-risk controls using a previously validated library specific for SARS-CoV-2 (ref. 39 ). To discover whether certain fragments were differentially enriched in either patients with MIS-C or at-risk controls, the enrichment of each phage encoded SARS-CoV-2 peptide (38 amino acids each) across all patients with MIS-C and at-risk controls was normalized to 48 healthy controls pre-COVID-19. Three nearly adjacent peptides derived from the SARS-CoV-2 nucleocapsid protein (fragments 5, 8 and 9) were significantly enriched (Kolmogorov–Smirnov test P < 0.0001 for each). The first peptide (fragment 5), spanning amino acids 77–114, was significantly enriched in the at-risk controls (representing the typical serological response in children), whereas the next two fragments (fragments 8 and 9), spanning amino acids 134–190, were significantly enriched in patients with MIS-C (Fig. 3a,b ). The most differentially reactive region of the SARS-CoV-2 nucleocapsid protein in patients with MIS-C (fragment 8) was termed the MIS-C-associated domain of SARS-CoV-2 (MADS). The PhIP-seq results were orthogonally confirmed using an SLBA measuring the amount of MADS peptide immunoprecipitated with samples from 16 individuals, including 11 patients with MIS-C and 5 at-risk controls (Fig. 3c ). To precisely map the minimal immunoreactive region of MADS in MIS-C samples, peptides featuring a sliding window of ten alanine residues were used as the immunoprecipitation substrate for SLBAs, run in parallel with the SNX8 alanine scanning peptides using sera from three patients with MIS-C (Fig. 3d ). The critical regions identified here in both SNX8 and MADS were highly similar, represented by the (ML)Q(ML)PQG motif (Fig. 3e ).
![sample summary of research paper figure 3](https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41586-024-07722-4/MediaObjects/41586_2024_7722_Fig3_HTML.png)
a , Relative PhIP-seq signal (FC over the mean) of 48 controls who are pre-COVID-19 (FC > pre-COVID-19) in patients with MIS-C ( n = 181) and at-risk controls ( n = 45) using a custom phage display library expressing the entire SARS-CoV-2 proteome to different regions of SARS-CoV-2. Only regions with a mean antibody signal of more than 1.5-fold above pre-COVID-19 controls are shown. Antigenicity (sum of the mean FC > pre-COVID-19 in MIS-C and at-risk controls) are represented by darker shades. The length of the bars represents the statistical difference in signal between MIS-C and at-risk controls to a particular region (−log 10 of two-sided Kolmogorov–Smirnov test P values), with upward deflections representing enrichment in MIS-C versus at-risk controls, and downward deflections representing less signal in MIS-C. The asterisk indicates the differentially reactive region of the nucleocapsid (N) protein. b , Bar plots showing the PhIP-seq signal (FC > pre-COVID-19) across the specific region of the SARS-CoV-2 nucleocapsid protein (fragments 4–9) with the most divergent response in MIS-C samples ( n = 181) relative to at-risk controls ( n = 45), compared using a two-sided Kolmogorov–Smirnov test (exact P values are shown in the figure). The amino acid sequence of the region with the highest relative enrichment in MIS-C is highlighted in green and referred to as MADS. c , Strip plots and box plots showing MADS SLBA enrichments (normalized antibody indices) in patients with MIS-C ( n = 11) relative to at-risk controls ( n = 5). d , SLBA signal (normalized antibody indices) for full sequential alanine mutagenesis scans within the same three individuals for SNX8 (left) and MADS (right). Each identified epitope is bounded by black vertical dotted lines. e , Multiple sequence alignment of SNX8 and MADS epitopes with the amino acid sequence for the similarity region shown (for the text in colour, biochemically similar is in orange, and identical is in red). For the box plots ( b , c ), the whiskers extend to 1.5 times the IQR from the quartiles. The boxes represent the IQR, and the centre lines represent the median.
Patients with MIS-C have significantly increased SNX8 autoreactive T cells
In other autoimmune diseases, autoantibodies often arise to intracellular targets, yet the final effectors of cellular destruction are autoreactive T cells 22 , 26 , 40 . Given evidence that certain subsets of MIS-C are associated with HLA 16 , and that SNX8 is an intracellular protein, we hypothesized that patients with MIS-C with anti-SNX8 antibodies may, in addition to possessing SNX8 autoreactive B cells, also possess autoreactive T cells targeting SNX8-expressing cells. To test this hypothesis, T cells from nine patients with MIS-C (eight from SNX8 autoantibody-positive patients and one who was SNX8 autoantibody negative) and ten at-risk controls (chosen randomly) were exposed to a pool of 15-mer peptides with 11-amino acid overlaps tiling the full-length human SNX8 protein. T cell activation was measured by an activation-induced marker assay, which quantifies upregulation of three cell activation markers: OX40, CD69 and CD137 (ref. 41 ). The percent of T cells activated in response to SNX8 protein was significantly higher in patients with MIS-C than in controls ( P = 0.00126). Using a positive cut-off of 3 s.d. above the mean of the controls, 7 of the 9 (78%) patients with MIS-C were positive for SNX8-expressing autoreactive T cells, whereas 0 of 10 (0%) controls met these criteria (Fig. 4a ). With respect to CD4 + and CD8 + subgroups, there was an increased signal in patients with MIS-C compared with controls, which did not meet significance ( P = 0.0711 and P = 0.0581, respectively; Extended Data Fig. 3a ). The patient with MIS-C who was seronegative for the SNX8 autoantibody was also negative for SNX8 autoreactive T cells.
![sample summary of research paper figure 4](https://media.springernature.com/lw685/springer-static/image/art%3A10.1038%2Fs41586-024-07722-4/MediaObjects/41586_2024_7722_Fig4_HTML.png)
a , Strip plots and box plots showing the distribution of T cells activated in response to either vehicle (culture media + 0.2% DMSO) or the SNX8 peptide pool (SNX8 peptide + culture media + 0.2% DMSO) in patients with MIS-C ( n = 9) and controls ( n = 10). The relative signal was compared using a two-sided Mann–Whitney U -test (exact P values are shown in the figure). The box plot whiskers extend to 1.5 times the IQR from the quartiles, the boxes represent the IQR, and the centre lines represent the median. The dashed line is 3 s.d. above the mean of the controls in the SNX8 pool condition. b , TCRdist similarity network of 48 unique, paired TCRαβ sequences ( n = 259 sequences) obtained from four patients with MIS-C. CD8 + T cells were sorted from PBMCs directly ex vivo or after 10 days of peptide expansion and staining with A*02:01 or A*02:06 HLA class I tetramers loaded with MADS (LQLPQGITL) and SNX8 (MQMPQGNPL) peptides. Each node represents a unique TCR clonotype. Edges connect nodes with a TCRdist score of less than 150. The dashed lines surround TCR similarity clusters. The node size corresponds to the T cell clone size. Nodes are coloured based on the HLA experiment type (left) or patient (right). TCRs selected for further testing are numbered TCR 1–8. The convergent node is circled in green. c , Specificity of putative cross-reactive TCRs expressed in Jurkat-76 cells by HLA-A*02:01 or HLA-A*02:06 tetramers loaded with MADS (LQLPQGITL) and SNX8 (MQMPQGNPL) peptides. Jurkat-76 (TCR-null) cells were used as tetramer background staining controls. The gate values indicate the frequency of MADS–APC + and/or SNX8–BV421 + cells as the percentage of the total PE + cells (combination staining with MADS–PE and SNX8–PE tetramers). TCRs with confirmed cross-reactivity are indicated in red. Outliers are shown. Flow plots are representative of two independent evaluations. d , Summary of TCR sequencing results of the eight TCRs tested.
HLA type A*02 is more likely to present the shared epitope
MIS-C has been associated with HLA alleles A*02, B*35 and C*04 (ref. 16 ). The Immune Epitope Database and Analysis Resource ( https://IEDB.org ) 42 was used to rank the HLA class I (HLA-I) peptide presentation likelihoods for both SNX8 and SARS-CoV-2 nucleocapsid protein with respect to the MIS-C-associated HLA alleles. The distribution of predicted HLA-I-binding scores for nucleocapsid protein and SNX8 fragments matching the (ML)Q(ML)PQG SNX8/MADS motif relative to fragments lacking a match was compared. For HLA-A*02, predicted HLA-I binding was significantly higher ( P = 8.78 × 10 −10 for nucleocapsid protein; P = 0.0112 for SNX8) for fragments containing the putative autoreactive motif. There was no statistical difference for HLA-B*35 and HLA-C*04 predictions (Extended Data Fig. 3b,c ). Of note, of the seven patients with MIS-C with SNX8 autoreactive T cells, at least five were positive for HLA-A*02 (Extended Data Fig. 3a ). To experimentally validate HLA-I-binding predictions to SNX8 and MADS peptides, we measured peptide–HLA (pHLA) monomer stability using a β2 microglobulin (β2m) fold test, which is a proxy for pHLA-binding affinity in which anti-β2m staining reports on the strength of the pHLA complex 43 . SNX8 (MQMPQGNPL) and MADS (LQLPQGITL) peptides were loaded onto unfolded HLA-A*02:01, HLA-A*02:06 or HLA-B*35:01 monomers and stained with an anti-β2m fluorescent antibody. Consistent with the IEDB rankings, both HLA-A*02 alleles bound SNX8 and MADS peptides, with HLA-A*02:06 exhibiting the highest pHLA complex stability (Extended Data Fig. 3d ).
T cells from patients with MIS-C are cross-reactive to the SNX8 and nucleocapsid protein similarity regions
Given the prediction that HLA types associated with MIS-C preferentially display peptides containing the similarity regions for both SNX8 and the SARS-CoV-2 nucleocapsid protein, we sought to determine whether cross-reactive T cells were present and whether they were associated with MIS-C. We stimulated peripheral blood mononuclear cells (PBMCs) from three patients with MIS-C and three at-risk controls with peptides from either the SNX8 similarity region (MQMPQGNPL) or the MADS similarity region (LQLPQGITL) for 7 days to enrich for CD8 + T cells reactive to these epitopes. We then built differently labelled HLA-I tetramers loaded with either the SNX8 or MADS peptides and measured binding to T cells (Extended Data Fig. 4a ). We detected cross-reactive CD8 + T cells, which bound both peptide epitopes, in all three patients with MIS-C, whereas no cross-reactive CD8 + T cells were observed in at-risk controls (Extended Data Fig. 4b ).
As SNX8-responsive T cells were observed in patients with MIS-C, we next asked whether the region of SNX8 similar to the SARS-CoV-2 MADS region was sufficient to activate patient T cells. A pool of 20 10-mer peptides with 9-amino acid overlaps centred on the target motif from SNX8 (collectively spanning amino acids 44–72) was used to stimulate PBMCs from two patients with MIS-C and four at-risk controls. Both patients with MIS-C had activation of T cells, whereas none of the four controls had T cell activation (Extended Data Fig. 4c ).
Identification of ex vivo cross-reactive T cell receptors
Having determined that patients with MIS-C, but not controls, contained putative SNX8/MADS cross-reactive CD8 + T cells, we next sought to identify T cell receptor (TCR) sequences with specificity for both the SARS-CoV-2 MADS and the host SNX8 epitopes. To do this, PBMCs were obtained during the first 72 h of hospital admission from four study participants with HLA-A*02 and confirmed MIS-C (one individual previously identified as having putative cross-reactive T cells, and three new patients). Given that MIS-C PBMCs represent a scarce resource, we chose to expand one aliquot of PBMCs from each of the four participants (distinct from our previous peptide expansion protocol; see Methods ) to maximize the chances of isolating putative cross-reactive TCRs. Although the frequency of ex vivo autoantigen-specific CD8 + T cells are extraordinarily low in peripheral blood, even for bona fide T cell-mediated autoimmune diseases such as T1DM 38 and multiple sclerosis 44 , 45 , we nevertheless utilized the remaining PBMCs from each participant for direct ex vivo analysis without previous expansion. To isolate the antigen-specific TCRs, participant cells (both ex vivo and following peptide expansion) were stained using the same tetramer-labelling strategy, which previously identified the putative cross-reactive TCRs (Extended Data Fig. 4a ); any cell exhibiting binding to at least two peptide-loaded tetramers was individually sorted and full-length paired TCRα and TCRβ sequences were determined. This resulted in 259 complete TCR sequences, comprising 30 and 18 unique T cell clones from the ex vivo and peptide expansion experiments, respectively. A complete list of TCR sequences is provided (Fig. 4 source data).
Next, we sought to validate the specificity of putative SNX8/MADS cross-reactive TCRs identified from the tetramer sorting, and further analyse features of the recovered TCRs. Because clusters of similar TCRs tend to recognize similar peptide antigens, a TCR similarity network was constructed from all 259 full-length TCR sequences using a previously established TCR distance metric (TCRdist) 46 , 47 (Fig. 4b and Extended Data Fig. 4d ). In two of the four patients, we identified unique populations of clonally expanded T cells expressing putative cross-reactive TCRs directly ex vivo, whereas each of the four patients had at least one ex vivo putative cross-reactive TCR (Fig. 4b ). To confirm the specificity of the TCRs identified in our tetramer sorting, we selected eight TCR sequences for additional validation and generated individual cell lines that stably expressed one TCR of interest (Extended Data Fig. 5a ). These Jurkat-TCR + cell lines were tetramer stained, and cross-reactivity was confirmed in three of the Jurkat-TCR + cell lines (TCR 1, 7 and 8; Fig. 4c ). Of these validated cross-reactive TCRs, two were obtained from ex vivo PBMCs from patients with MIS-C including TCR 7, which was clonally expanded. The minimum ex vivo frequency of TCR 7 alone was more than 1 in 25,000 (6 of 140,035) circulating CD8 + T cells. The two cross-reactive TCRs obtained from the ex vivo isolation were derived from the same participant, utilize the same TRAV gene ( TRAV1-2 ) with identical CDR3α sequences and clustered with three additional sequences in the TCRdist space, one of which was also clonally expanded, suggesting that this patient had an active expansion of a large cluster of SNX8/MADS cross-reactive CD8 + T cells (Fig. 4d ). Furthermore, we note a cluster of two similar TCRs obtained from ex vivo sampling of different participants (patients 2 and 4) with different HLA types (‘convergent node’; circled in green in Fig. 4b ). Although these putative cross-reactive TCRs were not evaluated further, the cluster suggests that TCR specificities to these epitopes may converge across individuals.
The remaining five Jurkat-TCR + cell lines (TCR 2–6) exhibited single specificity to the MADS tetramer with four of five coming from the peptide expansion. To evaluate possible interference between tetramers, which can arise when pHLA–TCR-binding affinities differ, Jurkat-TCR + cell lines were stained with individual tetramers. The results confirm that four of these TCRs are indeed reactive only to MADS (Extended Data Fig. 5b ). However, TCR 2, although showing strong binding preference to MADS, also bound the individual SNX8 tetramer, suggesting that the higher affinity for MADS may outcompete binding to the SNX8 tetramer in some cases. This observation is in line with the notion that autoreactive cross-reactive TCRs with lower relative affinities to autoantigens may escape thymic negative selection. Finally, because the original tetramer experiments were based on an early 2020 SARS-CoV-2 minor variant sequence (LQLPQGITL), all eight Jurkat-TCR + cell lines were also stained with HLA tetramers loaded with the SARS-CoV-2 Wuhan MADS sequence (LQLPQGTTL). In all cases, the Jurkat-TCR + cells bound the Wuhan MADS tetramer, consistent with the notion that T cells encoding these and other similar TCRs may be capable of responding to multiple SARS-CoV-2 strains (Extended Data Fig. 5c ).
RNA expression profile of SNX8 during SARS-CoV-2 infection
As previously discussed, SNX8 is expressed across multiple tissues, but is highest in immune cells, consistent with its role in defending against RNA viruses via recruitment of MAVS 27 . To further investigate the potential impact of combined B cell and T cell autoimmunity to SNX8 following SARS-CoV-2 infection, we used scRNA-seq to analyse SNX8 expression in PBMCs from patients with severe, mild or asymptomatic SARS-CoV-2 infection or influenza infection and uninfected healthy controls 48 . Following SARS-CoV-2 infection, SNX8 had the highest mean expression in classical and non-classical monocytes and B cells (Extended Data Fig. 6a,b ) and was elevated in individuals infected with SARS-CoV-2 compared with those who were uninfected (Extended Data Fig. 6c ). Within myeloid lineage cells, SNX8 expression correlated with MAVS expression and OAS1 and OAS2 (which encode two known regulators of the MAVS pathway implicated in MIS-C pathogenesis 7 ) expression (Extended Data Fig. 6d ). Conversely, SNX8 expression is inversely correlated to SARS-CoV-2 infection severity. This follows a similar pattern to OAS1 and OAS2 . However, unlike OAS1 , OAS2 and MAVS , SNX8 is preferentially expressed during SARS-CoV-2 infection compared with influenza virus infection (Extended Data Fig. 6e ).
The SARS-CoV-2 pandemic largely spared children from severe disease. One rare but notable exception is MIS-C, an enigmatic and life-threatening syndrome. Previous studies have surfaced numerous associations, but have failed to identify a direct mechanistic link between SARS-CoV-2 and MIS-C. In this study, 199 samples from patients with MIS-C and 45 paediatric at-risk controls were analysed using customized human and SARS-CoV-2 proteome PhIP-seq libraries. Targeted follow-up experiments from these assays ultimately revealed that patients with MIS-C preferentially had antibodies targeting the epitope motif (ML)Q(ML)PQG shared by both the SARS-CoV-2 nucleocapsid protein and the human protein SNX8. Cross-reactive CD8 + T cells targeting both regions were detected in patients with MIS-C, but not in controls, suggesting that these CD8 + T cells may contribute to immune dysregulation through the inappropriate targeting of immune cells expressing SNX8. We found evidence that the (ML)Q(ML)PQG epitope motif elicits both B cell and T cell reactivity; further study of this epitope convergence is warranted.
These findings help to connect several important known aspects of MIS-C pathophysiology and draw parallels to other diseases in which exposure to a new antigen leads to autoimmunity, such as paraneoplastic autoimmune disease or cross-reactive epitopes between Epstein–Barr virus and host proteins in multiple sclerosis 17 , 18 , 19 , 22 , 26 . An expansion of T cells expressing TCRβ variable gene 11-2 ( TRBV11-2 ) has been shown in MIS-C 8 , 15 , 16 ; however, the underlying driver remains unknown. Although we did not observe an overrepresentation of TRBV11-2 in our putative cross-reactive TCR dataset, we did identify two expanded TRBV11-2 + clones ( n = 6 and n = 2) sequenced directly from ex vivo samples. Although SNX8 is a relatively understudied protein, it has been linked to the function and activity of MAVS 27 . Dysregulation of the MAVS antiviral pathway, by inborn errors of immunity, has been shown to underlie certain cases of MIS-C 7 . The most straightforward connection linking MIS-C to SNX8 may be through an inappropriate autoimmune response against tissues with elevated MAVS pathway expression. These results are the first to directly link the initial SARS-CoV-2 infection and the subsequent development of MIS-C. We propose that MIS-C may be the result of multiple uncommon events converging. The initial insult is probably the formation of a combined B cell and T cell response that preferentially targets a particular motif within the MADS region of the SARS-CoV-2 nucleocapsid protein. In a subset of individuals, these B cell and T cell responses cross-react to the self-protein SNX8. This cross-reactive motif has strong binding characteristics for the MIS-C-associated HLA-A*02 (ref. 16 ), further indicating that this may be an important risk factor in the development of MIS-C.
Using conservative criteria (3 s.d. greater than controls by targeted immunoprecipitation of the epitope-containing peptide), at least 17% of sera from patients with MIS-C are autoreactive for SNX8; however, approximately 37% of sera from patients with MIS-C yielded detectable enrichment compared with controls in the entire dataset. Because we only tested for a single epitope target, we are unable to determine the upper limits of the in vivo frequency of cross-reactive CD8 + T cells in patients with MIS-C. Our results suggest that the frequency of these cross-reactive CD8 + T cells is within the range of 1 in 10,000–100,000 CD8 + T cells. This substantially exceeds the frequency of antigen-specific autoreactive CD8 + T cells found in peripheral circulation in bona fide T cell-mediated autoimmune diseases such as T1DM 38 and multiple sclerosis 44 , 45 . Similar to T1DM, the autoreactive and cross-reactive CD8 + T cells in patients with MIS-C may be found at far greater abundance within peripheral tissues known to be affected by the disease 38 . Even accounting for these limitations, our results describe a subset of MIS-C, indicating that other mechanisms probably exist. Antibodies to ERFL are present in many children with MIS-C who do not have autoreactivity to SNX8, and ERFL has a highly similar tissue RNA expression profile as SNX8 (second-most similar among all known proteins; Human Protein Atlas) 36 . If autoreactive T cells to ERFL indeed exist, they would be predicted to engage a nearly identical set of cells and tissues. It is important to also consider that MIS-C prevalence has rapidly decreased as an increasing number of children have developed immunity through vaccination and natural SARS-CoV-2 infection. We speculate that perhaps this could be related to the strong deviation of the anti-SARS-CoV-2 immune response away from the critical MADS region of the nucleocapsid protein that we have identified, to other major epitopes such as those in the spike protein through vaccination and past infection 49 . Supporting this notion is recent CDC surveillance, which noted that more than 80% (92 of 112) of individuals with MIS-C in 2023 were in unvaccinated children (but vaccine eligible), and that the majority of children who developed MIS-C despite previous vaccination probably had waned immunity 50 .
MIS-C is complex, and more work will be required to fully understand this syndrome. The results of this study, and specifically the development of combined cross-reactive B cells and T cells, build on other notable examples of molecular mimicry; however, the mechanisms by which the presence of a cross-reactive epitope forces a break in tolerance remain unclear. Our results shed light on how one post-infectious disease (MIS-C) develops, yielding insights that may help better explain, diagnose and ultimately treat a range of additional conditions associated with infections.
Patients were recruited through the prospectively enrolling multicentre Overcoming COVID-19 and Taking on COVID-19 Together study in the USA. All patients meeting clinical criteria were included in the study, and therefore no statistical methods were used to predetermine sample size and no blinding or randomization of subjects occurred. The study was approved by the central Boston Children’s Hospital Institutional Review Board (IRB) and reviewed by IRBs of participating sites with CDC IRB reliance. A total of 292 patients consented and were enrolled into one of the following independent cohorts between 1 June 2020 and 9 September 2021: 223 patients hospitalized with MIS-C (199 in the primary discovery cohort and 24 in a separate subsequent validation cohort), 29 patients hospitalized for COVID-19 in either an intensive care or step-down unit (referred to as ‘severe acute COVID-19’ in this study) and 45 outpatients (referred to as ‘at-risk controls’ in this study) post-SARS-CoV-2 infections associated with mild or no symptoms. The demographic and clinical data are summarized in Extended Data Tables 1 – 3 . The 2020 US CDC case definition was used to define MIS-C 51 . All patients with MIS-C had positive SARS-CoV-2 serology results and/or positive SARS-CoV-2 test results by reverse transcriptase quantitative PCR. All patients with severe COVID-19 or outpatient SARS-CoV-2 infections had a positive antigen test or nucleic acid amplification test for SARS-CoV-2. For outpatients, samples were collected from 36 to 190 days after the positive test (median of 70 days after a positive test; interquartile range of 56–81 days). For use as controls in the SARS-CoV-2-specific PhIP-seq, plasma from 48 healthy, pre-COVID-19 controls were obtained as deidentified samples from the New York Blood Center. These samples were part of retention tubes collected at the time of blood donations from volunteer donors who provided informed consent for their samples to be used for research.
DNA oligomers for SLBAs
DNA coding for the desired peptides for use in SLBAs were inserted into split luciferase constructs containing a terminal HiBiT tag and synthesized (Twist Biosciences) as DNA oligomers and verified by Twist Biosciences before shipment. Constructs were amplified by PCR using the 5′- AAGCAGAGCTCGTTTAGTGAACCGTCAGA-3′ and 5′-GGCCGGCCGTTTAAACGCTGATCTT-3′ primer pair.
For SNX8, the oligomers coded for the following sequences:
EADPPASDLPTPQAIEPQAIVQQVPAPSRMQMPQGNPLLLSHTLQELLA
AAAAAAAAAATPQAIEPQAIVQQVPAPSRMQMPQGNPLLLSHTLQELLA
EADPPAAAAAAAAAAEPQAIVQQVPAPSRMQMPQGNPLLLSHTLQELLA
EADPPASDLPAAAAAAAAAAVQQVPAPSRMQMPQGNPLLLSHTLQELLA
EADPPASDLPTPQAIAAAAAAAAAAAPSRMQMPQGNPLLLSHTLQELLA
EADPPASDLPTPQAIEPQAIAAAAAAAAAAQMPQGNPLLLSHTLQELLA
EADPPASDLPTPQAIEPQAIVQQVPAAAAAAAAAANPLLLSHTLQELLA
EADPPASDLPTPQAIEPQAIVQQVPAPSRMAAAAAAAAAASHTLQELLA
EADPPASDLPTPQAIEPQAIVQQVPAPSRMQMPQGAAAAAAAAAAELLA
EADPPASDLPTPQAIEPQAIVQQVPAPSRMQMPQGNPLLLAAAAAAAAA
For SARS-CoV-2 nucleocapsid protein, the oligomers coded for the following sequences:
ATEGALNTPKDHIGTRNPANNAAIVLQLPQGTTLPKGFYAEGSRGGSQA
AAAAAAAAAADHIGTRNPANNAAIVLQLPQGTTLPKGFYAEGSRGGSQA
ATEGAAAAAAAAAAARNPANNAAIVLQLPQGTTLPKGFYAEGSRGGSQA
ATEGALNTPKAAAAAAAAAANAAIVLQLPQGTTLPKGFYAEGSRGGSQA
ATEGALNTPKDHIGTAAAAAAAAAALQLPQGTTLPKGFYAEGSRGGSQA
ATEGALNTPKDHIGTRNPANAAAAAAAAAAGTTLPKGFYAEGSRGGSQA
ATEGALNTPKDHIGTRNPANNAAIVAAAAAAAAAAKGFYAEGSRGGSQA
ATEGALNTPKDHIGTRNPANNAAIVLQLPQAAAAAAAAAAEGSRGGSQA
ATEGALNTPKDHIGTRNPANNAAIVLQLPQGTTLPAAAAAAAAAAGSQA
ATEGALNTPKDHIGTRNPANNAAIVLQLPQGTTLPKGFYAAAAAAAAAA
DNA plasmids for RLBAs
For RLBAs, DNA expression plasmids under control of a T7 promoter and with a terminal Myc–DDK tag for the desired protein were utilized. For ERFL, a custom plasmid was ordered from Twist Bioscience in which a Myc–DDK-tagged full-length ERFL sequence under a T7 promoter was inserted into the pTwist Kan High Copy Vector (Twist Bioscience). Twist Bioscience verified a sequence-perfect clone by next-generation sequencing before shipment. Upon receipt, the plasmid was sequence verified by Primordium Labs. For SNX8, a plasmid containing the Myc–DDK-tagged full-length human SNX8 under a T7 promoter was ordered from Origene (RC205847) and was sequence verified by Primordium Labs upon receipt. For KDELR1, a plasmid containing the Myc–DDK-tagged full-length human KDELR1 under a T7 promoter was ordered from Origene (RC205880) and was sequence verified by Primordium Labs upon receipt. For IL1RN, a plasmid containing the Myc–DDK-tagged full-length human IL1RN under a T7 promoter was ordered from Origene (RC218518) and was sequence verified by Primordium Labs upon receipt.
Polypeptide pools for activation-induced marker assays
To obtain polypeptides tiling the full-length SNX8 protein, 15-mer polypeptide fragments with 11-amino acid overlaps were ordered from JPT Peptide Technologies and synthesized. Together, a pool of 130 of these polypeptides (referred to as the ‘SNX8 pool’) spanned all known translated SNX8 (the full-length 465-amino acid SNX8 protein, as well as a unique region of SNX8 isoform 3). A separate pool was designed to cover primarily the region of SNX8 with similarity to the SARS-CoV-2 nucleocapsid protein in high resolution (referred to as the ‘high-resolution epitope pool’). This pool contained 20 10-mers with 9-amino acid overlaps tiling amino acids 44–72 (IVQQVPAPSRMQMPQGNPLLLSHTLQELL) of the full-length SNX8 protein. The sequence of each of these 150 polypeptides was verified by mass spectrometry and purity was calculated by high-performance liquid chromatography (HPLC).
Peptides for tetramer assays
For use in loading tetramers, three peptides were ordered from Genemed Synthesis as 9-mers. LQLPQGTTL and LQLPQGITL correspond to the region of the SARS-CoV-2 nucleocapsid protein with similarity to human SNX8 in the ancestral sequence and a minor variant, respectively. This sequence was verified by mass spectrometry and purity was calculated as 96.61% by HPLC. The other sequence, MQMPQGNPL, corresponds to the region of human SNX8 protein with similarity to the SARS-CoV-2 nucleocapsid protein. This sequence was verified by mass spectrometry and purity was calculated as 95.83% by HPLC.
Human proteome PhIP-seq
Human proteome PhIP-seq was performed following our previously published vacuum-based PhIP-seq protocol 12 ( https://www.protocols.io/view/scaled-high-throughput-vacuum-phip-protocol-ewov1459kvr2/v1 ).
Our human peptidome library consists of a custom-designed phage library of 731,724 unique T7 bacteriophage each presenting a different 49-amino acid peptide on its surface. Collectively, these peptides tile the entire human proteome including all known isoforms (as of 2016) with 25-amino acid overlaps. Of the phage library, 1 ml was incubated with 1 μl of human serum overnight at 4 °C and immunoprecipitated with 25 μl of 1:1 mixed protein A and protein G magnetic beads (10008D and 10009D, Thermo Fisher). These beads were than washed, and the remaining phage–antibody complexes were eluted in 1 ml of Escherichia coli (BLT5403, EMD Millipore) at 0.5–0.7 OD and amplified by growing in a 37 °C incubator. This new phage library was then re-incubated with the serum from the same individual and the previously described protocol was repeated. DNA was then extracted from the final phage library, barcoded, PCR amplified and Illumina adaptors were added. Next-generation sequencing was performed using an Illumina sequencer (Illumina) to a read depth of approximately 1 million per sample.
Human proteome PhIP-seq analysis
All human peptidome analysis (except when specifically stated otherwise) was performed at the gene level, in which all reads for all peptides mapping to the same gene were summed, and 0.5 reads were added to each gene to allow inclusion of genes with zero reads in mathematical analyses. Within each individual sample, reads were normalized by converting to the percentage of total reads. To normalize each sample against background nonspecific binding, a fold change over mock-IP was calculated by dividing the sample read percentage for each gene by the mean read percentage of the same gene for the AG bead-only controls. This fold-change signal was then used for side-by-side comparison between samples and cohorts. Fold-change values were also used to calculate z scores for each patient with MIS-C compared with controls and for each control sample by using all remaining controls. These z scores were used for the logistic-regression feature weighting. In instances of peptide-level analysis, raw reads were normalized by calculating the number of reads per 100,000 reads.
SARS-CoV-2 proteome PhIP-seq
SARS-CoV-2 proteome PhIP-seq was performed as previously described 39 . In brief, 38 amino acid fragments tiling all open reading frames from SARS-CoV-2, SARS-CoV-1 and 7 other CoVs were expressed on T7 bacteriophage with 19-amino acid overlaps. Of the phage library, 1 ml was incubated with 1 μl of human serum overnight at 4 °C and immunoprecipitated with 25 μl of 1:1 mixed protein A and protein G magnetic beads (10008D and 10009D, Thermo Fisher). Beads were washed five times on a magnetic plate using a P1000 multichannel pipette. The remaining phage–antibody complexes were eluted in 1 ml of E. coli (BLT5403, EMD Millipore) at 0.5–0.7 OD and amplified by growing in 37 °C incubator. This new phage library was then re-incubated with the serum of the same individual and the previously described protocol was repeated for a total of three rounds of immunoprecipitations. DNA was then extracted from the final phage library, barcoded, PCR amplified and Illumina adaptors were added. Next-generation sequencing was then performed using an Illumina sequencer (Illumina) to a read depth of approximately 1 million per sample.
Coronavirus proteome PhIP-seq analysis
To account for differing read depths between samples, the total number of reads for each peptide fragment was converted to the number of reads per 100,000 (RPK). To calculate normalized enrichment relative to pre-COVID-19 controls (FC > pre-COVID-19), the RPK for each peptide fragment within each sample was divided by the mean RPK of each peptide fragment among all pre-COVID-19 controls. These FC > pre-COVID-19 values were used for all subsequent analyses as described in the text and figures.
RLBAs were performed as previously described 12 , 32 . In brief, DNA plasmids containing full-length cDNA under the control of a T7 promoter for each of the validated antigens (see ‘DNA plasmids for RLBAs’ above) were verified by Primordium Labs sequencing. The respective DNA templates were used in the T7 TNT in vitro transcription/translation kit (L1170, Promega) using [35S]-methionine (NEG709A, PerkinElmer). Respective protein was column purified on Nap-5 columns (17-0853-01, GE Healthcare), and equal amounts of protein (approximately 35,000 counts per minute) were incubated overnight at 4 °C with 2.5 μl of serum or 1 μl of anti-Myc-positive control antibody (1:10 dilution; 2272S, Cell Signaling Technology). Immunoprecipitation was then performed on 25 μl of Sephadex protein A/G beads (4:1 ratio; GE17-5280-02 and GE17-0618-05, Sigma-Aldrich) in 96-well polyvinylidene difluoride filtration plates (EK-680860, Corning). After thoroughly washing, the counts per minute of immunoprecipitated protein was quantified using a 96-well Microbeta Trilux liquid scintillation plate reader (Perkin Elmer).
SLBA was performed as previously described 52 . A detailed SLBA protocol is available on protocols.io ( https://doi.org/10.17504/protocols.io.4r3l27b9pg1y/v1 ).
In brief, the DNA oligomers listed above (see ‘DNA oligomers for SLBAs’) were amplified by PCR using the primer pairs listed above (see ‘DNA oligomers for SLBAs’). Unpurified PCR product was used as input in the T7 TNT in vitro transcription/translation kit (L1170, Promega) and the Nano-Glo HiBit Lytic Detection System (N3040, Promega) was used to measure relative luciferase units of translated peptides in a luminometre. Equal amounts of protein (in the range of 2 × 10 6 –2 × 10 7 relative luciferase units) were incubated overnight with 2.5 μl patient sera or 1 μl anti-HiBit-positive control antibody (1:10 dilution; CS2006A01, Promega) at 4 °C. Immunoprecipitation was then performed on 25 µl of Sephadex protein A/G beads (1:1 ratio; GE17-5280-02 and GE17-0618-05, Sigma-Aldrich) in 96-well polyvinylidene difluoride filtration plates (EK-680860, Corning). After thoroughly washing, luminescence was measured using the Nano-Glo HiBit Lytic Detection System (N3040, Promega) in a luminometre.
Activation-induced marker assay
PBMCs were obtained from ten patients with MIS-C and ten controls for use in the activation-induced marker assay. PBMCs were thawed, washed, resuspended in serum-free RPMI medium and plated at a concentration of 1 × 10 6 cells per well in a 96-well round-bottom plate. For each individual, PBMCs were stimulated for 24 h with either the SNX8 pool (see above) at a final concentration of 1 mg ml −1 per peptide in 0.2% DMSO or a vehicle control containing 0.2% DMSO only. For four of the controls and two of the patients with MIS-C, there were sufficient PBMCs for an additional stimulation condition using the SNX8 high-resolution epitope pool (see above) also at a concentration of 1 mg ml −1 per peptide in 0.2% DMSO for 24 h. Following the stimulation, cells were washed with FACS buffer (Dulbecco’s PBS without calcium or magnesium, 0.1% sodium azide, 2 mM EDTA and 1% FBS) and stained with the following antibody panel each at 1:100 dilution for 20 min at 4 °C, and then flow cytometry analysis was immediately performed.
For the antibody panel: anti-CD3 Alexa 647 (clone OKT3, 317312, BioLegend), anti-CD4 Alexa 488 (clone OKT4, 317420, BioLegend), anti-CD8 Alexa 700 (clone SK1, 344724, BioLegend), anti-OX-40 (also known as CD134) PE-Dazzle 594 (clone ACT35, 350020, BioLegend), anti-CD69 PE (clone FN-50, 310906, BioLegend), anti-CD137 (also known as 4-1BB) BV421 (clone 4B4-1, 309820, BioLegend), anti-CD14 PerCP-Cy5 (clone HCD14, 325622, BioLegend), anti-CD16 PerCP-Cy5 (clone B73.1, 360712, BioLegend), anti-CD19 PerCP-Cy5 (clone HIB19, 302230, BioLegend) and Live/Dead Dye eFluor 506 (65-0866-14, Invitrogen).
The activation-induced marker analysis was performed using FlowJo software using the gating strategy shown in Extended Data Fig. 7a . All gates were fixed within each condition of each sample. Activated CD4 T cells were defined as those that were co-positive for OX40 and CD137. Activated CD8 T cells were defined as those that were co-positive for CD69 and CD137. Gating thresholds for activation were defined by the outer limits of signal in the vehicle controls allowing for up to two outlier cells. Frequencies were calculated as a percentage of total CD3 + cells (T cells). Two MIS-C samples had insufficient total events captured by flow cytometry (total of 5,099 and 4,919 events, respectively) and were therefore removed from analysis.
Initial tetramer assay
For the initial tetramer assay, see Extended Data Fig. 4a . PBMCs from two patients with MIS-C with HLA-A*02:01 (HLA typed from PAXgene RNAseq, one confirmed by serotyping), one patient with MIS-C with HLA-B*35:01 (HLA typed from PAXgene RNAseq) and three at-risk controls with HLA-A*02.01 (all three identified by serotyping, two of three confirmed by PAXgene RNAseq HLA typing; the other sample did not have genomic DNA available for genotyping) were thawed, washed and put into culture with media containing recombinant human IL-2 at 10 ng ml −1 in 96-well plates. The peptide fragments (details above) LQLPQGITL and MQMPQGNPL were then added to PBMCs to a final concentration of 10 mg ml −1 per peptide and incubated (37 °C at 5% CO 2 ) for 7 days.
Following the 7 days of incubation, a total of eight pHLA class I tetramers were generated from UV-photolabile biotinylated monomers, four each from HLA-A*02:01 and HLA-B*35:01 (NIH Tetramer Core). Peptides were loaded via UV peptide exchange. Tetramerization was carried out using streptavidin conjugated to fluorophores PE and APC or BV421 followed by quenching with 500 µM d -biotin, similar to our previously published methods 44 , 53 . Tetramers were then pooled together as shown below:
For the HLA-A*02:01 pool, the MADS (LQLPQGITL)-loaded PE tetramer, MADS (LQLPQGITL)-loaded APC tetramer, SNX8 (MQMPQGNPL)-loaded PE tetramer and SNX8 (MQMPQGNPL)-loaded BV421 tetramer were used, all with HLA-A*02:01 restriction.
For the HLA-B*35:01 pool, the MADS (LQLPQGITL)-loaded PE tetramer, MADS (LQLPQGITL)-loaded APC tetramer, SNX8 (MQMPQGNPL)-loaded PE tetramer and SNX8 (MQMPQGNPL)-loaded BV421 tetramer were used, all with HLA-B*35:01 restriction.
All PBMCs were then treated with 100 nM dasatinib (StemCell) for 30 min at 37 °C followed by staining (no wash step) with the respective tetramer pool corresponding to their HLA restriction (final concentration of 2–3 µg ml −1 ) for 30 min at 25 °C. Cells were then stained with the following cell-surface markers each at 1:100 dilution for 20 min, followed by immediate analysis on a flow cytometer.
For the surface markers: anti-CD8 Alexa 700 (clone SK1, 357404, BioLegend), anti-CD4 PerCP-Cy5 (clone SK1, 300530, BioLegend), anti-CD14 PerCP-Cy5 (clone HCD14, 325622, BioLegend), anti-CD16 PerCP-Cy5 (clone B73.1, 360712, BioLegend), anti-CD19 PerCP-Cy5 (clone HIB19, 302230, BioLegend) and Live/Dead Dye eFluor 506 (65-0866-14, Invitrogen). Streptavidin was conjugated to PE (S866, Invitrogen), APC (S868, Invitrogen) and BV421 (405225, BioLegend).
The gating strategy is outlined in Extended Data Fig. 7b . A stringent tetramer gating strategy was used to identify cross-reactive T cells, in which CD8 + T cells were required to be triple positive for PE, APC and BV421 labels (that is, a single CD8 T cell bound to PE-conjugated LQLPQGITL and/or PE-conjugated MQMPQGNPL in addition to APC-conjugated LQLPQGITL and BV421-conjugated MQMPQGNPL).
Serotyping was performed using an anti-HLA-A2 antibody (1:100 dilution; FITC anti-human HLA-A2 antibody, clone BB7.2, 343303, BioLegend), and pertinent results are shown in Extended Data Fig. 7c .
Assembly of easYmer monomers and fold testing
For the assembly of HLA class I pHLA easYmer monomers and fold testing, see Fig. 4 . Unfolded, biotinylated easYmer monomers (Immudex) were obtained for HLA-A*02:01 and HLA-A*02:06. SARS-CoV-2 MADS (LQLPQGITL), SARS-CoV-2 Wuhan (LQLPQGTTL) and human SNX8 (MQMPQGNPL) peptides were commercially synthesized (Genscript), diluted to 1 mM in ddH 2 O or DMSO, and loaded onto each easYmer allele according to the manufacturer’s instructions at 18 °C for 48 h. Proper pHLA monomer formation and MADS and SNX8 peptide-binding strength were evaluated for each HLA using a ‘β2m fold test’ relative to negative (no peptide; unloaded monomer) and positive (strong binding peptide; CMV pp65 495–503 (NLVPMVATV)) controls as per the manufacturer’s protocol. In brief, peptide-loaded monomers with a concentration of 500 nM were serially diluted to 9 nM, 3 nM and 1 nM in dilution buffer (1× PBS with 5% glycerol; G5516, Sigma-Aldrich) and incubated with streptavidin beads (6–8 μm; SVP-60-5, Spherotech) at 37 °C for 1 h to allow binding of stable complexes to beads, then washed three times with FACS buffer (1× PBS, 0.5% BSA (A7030, Sigma-Aldrich) and 2 mM EDTA (15575-038, Thermo Fisher Scientific)). Samples were then stained with PE-conjugated anti-human β2m antibody (clone BBM.1, sc-13565, Santa Cruz Biotech) at 1:200 for 30 min at 4 °C, washed three times with FACS buffer and analysed on a 5 Laser 16UV-16V-14B-10YG-8R AURORA spectral cytometer (Cytek). pHLA-binding strength positively correlated with stability and concentration of the pHLA–β2m complex. Therefore, the geometric mean fluorescence intensity of anti-β2m staining in this assay reports on the strength of the pHLA binding compared with the positive and negative controls. We classified binding strength for each HLA and peptide combination based on the fold change in anti-β2m geometric mean fluorescence intensity over the no-peptide negative control at 9 nM. Strong binders were defined at more than 10-fold higher, moderate binders at more than 3-fold, weak binders at more than 1.5-fold and non-binders at less than 1.5-fold change over the negative control. Flow cytometry data were analysed using FlowJo version 10.7.2 software (BD Biosciences).
pHLA tetramer assembly
For the pHLA tetramer assembly, see Fig. 4 . pHLA tetramers were assembled from HLA-A*02:01 and HLA-A*02:06 easYmer monomers (Immudex) with confirmed peptide binding to SARS-CoV-2 MADS (LQLPQGITL), Wuhan (LQLPQGTTL) and SNX8 (MQMPQGNPL) peptides according to the manufacturer’s instructions. In brief, fluorochrome-conjugated streptavidin (0.2 mg ml −1 , PE, 405203, BioLegend; 0.2 mg ml −1 , APC, 405207, BioLegend; and BV421, 405226, BioLegend) was added to loaded monomers at 8 ng per 1 μl pHLA complex (500 nM) in three volumes. After each 1/3 volume addition, samples were mixed and incubated for 15 min at 4 °C in the dark. Assembled tetramers were stored at 4 °C in the dark until use.
Enhanced peptide-specific T cell expansion
For enhanced peptide-specific T cell expansion, see Fig. 4 . PBMCs from MIS-C confirmed participants with HLA-A*02:01 or HLA-A*02:06 were obtained for peptide-specific expansion according to published methods 54 before single-cell sorting of tetramer-positive T cells. On expansion day 0, PBMCs were thawed, counted and seeded onto 96-well round-bottom plates at 100,000 cells per well in 200 μl antigen-presenting cell differentiation media (X-VIVO 15 serum-free haematopoietic cell medium (04-418Q, Lonza) supplemented with human GM-CSF (1,000 IU ml −1 ; 130-095-372, Miltenyi Biotec), human IL-4 (500 IU ml −1 ; 204-IL-010, R&D Systems) and human Flt3-L (50 ng ml −1 ; 308-FKN-025, R&D Systems) final concentrations) and incubated for 24 h at 37 °C and 5% CO 2 . On day 1, 100 μl cell supernatant was replaced with 100 μl Adjuvant Solution (X-VIVO 15 supplemented with R848 (10 μM; tlrl-r848-5, InvivoGen), lipopolysaccharide ( Salmonella minnesota ; 100 ng ml −1 ; tlrl-smlps, InvivoGen) and human IL-1β (10 ng ml −1 ; 201-LB-010, R&D Systems) final concentrations) and pooled MADS (LQLPQGITL) and SNX8 (MQMPQGNPL) peptides at a final concentration of 10 μM each. No-peptide control wells were set up for each sample by adding a 1:2 dilution of DMSO in H 2 O to match the peptide volume and diluent. Cells were incubated for 24 h at 37 °C and 5% CO 2 . On days 2, 4, 7 and 9, 100 μl supernatant was replaced with 100 μl T cell expansion solution: RP-10 (RPMI 1640 (22400-089, Gibco), 10% heat-inactivated human serum AB (100-512, Gemini Bio-Products), 10 mM HEPES, 0.1 mg ml −1 gentamicin (15750-060, Thermo Fisher Scientific) and 1× GlutaMAX (35050-061, Gibco)) supplemented with human IL-2 (10 IU ml −1 ; 202-IL-050, R&D Systems), human IL-7 (10 ng ml −1 ; 207-IL-025, R&D Systems) and human IL-15 (10 ng ml −1 ; 200-15, PeproTech) final concentrations. On day 10, peptide-expanded cells from an individual participant were pooled; cells from no-peptide controls were collected separately.
Single-cell index sorting
Unexpanded PBMCs (direct ex vivo) or peptide-expanded T cells were obtained, washed in 1× PBS and treated with 100 nM dasatinib (CDS023389, Sigma-Aldrich) in 1× PBS for 30 min at 37 °C and 5% CO 2 (ref. 55 ). Cells were then pelleted and resuspended in 50 μl FACS buffer (1× PBS and 0.04% BSA) supplemented with human TruStain FcX blocking buffer (1:10 dilution; 422302, BioLegend), 500 μM d -biotin (B20656, Thermo Fisher Scientific) and a unique tetramer cocktail containing MADS–tetramer–PE (1:10 dilution), MADS–tetramer–APC (1:10 dilution), SNX8–tetramer–PE (1:10 dilution) and SNX8–tetramer–BV421 (1:10 dilution) based on participant HLA type (A*02:01 and A*02:06). Cells were incubated in the dark at 25 °C for 1 h followed by direct addition of 50 μl (100 μl total volume) of FACS supplemented with 500 μM d -biotin and an antibody cocktail containing FITC-conjugated anti-human CD3 (1:20 dilution; clone OKT3, lot B390808, 317306, BioLegend), BV605-conjugated anti-human CD8 (1:20 dilution; clone SK1, lot B371925, 344742, BioLegend), BV510-conjugated anti-human CD4 (1:20 dilution; clone OKT4, lot B375526, 317444, BioLegend), BV510-conjugated anti-human CD14 (1:20 dilution; clone 63D3, lot B390770, 367124, BioLegend), BV510-conjugated anti-human CD16 (1:20 dilution; clone 3G8, lot B372132, 302048, BioLegend), BV510-conjugated anti-human CD19 (1:20 dilution; clone HIB19, lot B390665, 302242, BioLegend) and Ghost Dye Violet 510 Viability Dye (1:400 dilution; lot D0870061322133, 13-0870-T500, Tonbo Biosciences) for 30 min in the dark at 4 °C. Cells were then pelleted, washed twice with 4 ml FACS buffer (containing 500 μM d -biotin), suspended in 500 μl FACS (containing 500 μM d -biotin) and passed through a 45-μM filter before proceeding to single-cell sorting on a Sony SY3200 cell sorter. Individual, live, BV510 dump gate (CD4, CD14, CD16 and CD19)-negative, CD3 + CD8 + T lymphocytes were gated to distinguish tetramer triple-positive cells (PE + APC + BV421 + ) as described in Extended Data Fig. 7d and sorted into individual wells of a 384-well plate loaded with Superscript VILO master mix (11754250, Thermo Fisher Scientific). After sorting, plates were centrifuged at 500 g and stored at −80 °C until processing.
Paired TCRαβ amplification and sequencing
Single-cell paired TCRα and TCRβ chain library preparation and sequencing was performed on T cells sorted into 384-well index plates as previously described 56 . In brief, after reverse transcription of cells sorted in Superscript VILO master mix, cDNA underwent two rounds of nested multiplex PCR amplification using a mix of human V-segment-specific forward primers and human TRAC and TRBC segment-specific reverse primers (see Supplementary Table 1 for primer details). Resulting TCRα and TCRβ amplicons were sequenced on an Illumina MiSeq at 2 × 150-bp read length.
All cultured cell lines were maintained at 37 °C and 5% CO 2 in a humidified incubator. HEK 293T cells (CRL-3216, American Type Culture Collection) were purchased from the American Type Culture Collection and verified commercially. HEK 293T cells were cultured in DMEM (11965-092, Gibco) supplemented with 10% FBS (16140-071, Gibco), 2 mM l -glutamine (25030-081, Gibco) and 100 U ml −1 penicillin–streptomycin (15140-122, Gibco). 2D3 Jurkat J76.7 cells 57 , 58 (TCR-null, CD8 + ) expressing an NFAT–eGFP reporter were kindly provided by F. Fujiki and were cultured in RPMI 1640 (22400-089, Gibco) supplemented with 10% FBS, 2 mM l -glutamine and 100 U ml −1 penicillin–streptomycin. All cell lines were confirmed to be mycoplasma negative during the course of experiments.
TCR repertoire analysis
TCR similarity networks were constructed as previously described 49 , 59 . In brief, to measure the distance between TCRαβ clonotypes, we used the TCRdist algorithm implementation from the CoNGA v0.1.2 Python package 47 . Further analysis was performed using the R language for statistical computing, with merging and subsetting of data performed using the dplyr v1.1.4 package. TCR similarity networks were built using stringdist v0.9.12 and igraph v2.0.3 (ref. 60 ) R packages, and visualized using gephi v0.9.7 (ref. 61 ) software.
TCR reconstruction and cloning
Full-length TCRαβ sequences were reconstructed from V/J gene usage and CDR3 sequences using Stitchr v1.0.0 (ref. 62 ) for each index-sorted T cell. TCRα and TCRβ chain sequences were modified to use murine constant regions and joined by a 2A element from thosea asigna virus (T2A). A sequence encoding mCherry was additionally appended by a 2A element from porcine teschovirus (P2A) as a fluorescent marker of transduction. The full-length gene fragment encoding TCRβ–T2A–TCRα–P2A–mCherry was synthesized and cloned commercially (Genscript) into the lentiviral vector pLVX-EF1α-IRES-Puro (631253, Takara).
Generation of TCR-expressing Jurkat cells
To generate transducing particles packaging individual TCRs of interest (Fig. 4c ), HEK 293T cells were transduced with a pLVX lentiviral vector encoding a unique TCRαβ–mCherry insert, psPAX2 packaging plasmid (plasmid #12260, Addgene) and an pMD2.G envelope plasmid (plasmid #12259, Addgene) at a ratio of 4:3:1. At 24 h and 48 h post-transfection, viral supernatants were harvested, passed through a 0.45-µm SFCA filter (723-9945, Thermo Fisher Scientific), concentrated using Lenti-X Concentrator (631232, Takara) and stored at −80 °C as single-use aliquots. To generate TCR-expressing Jurkat cell lines (Jurkat-TCR + ), 2D3 Jurkat J76.7 cells (TCR-null, CD8 + , NFAT–eGFP reporter) were seeded in a 12-well tissue-culture-treated plate at 1 × 10 6 cells per well in complete RPMI (RPMI 1640, 10% FBS, 2 mM l -glutamine, 100 U ml −1 penicillin–streptomycin) and transduced by adding concentrated lentivirus dropwise to each well. At 48–72 h post-tranduction, puromycin was added at 1 μg ml −1 and cultured for 1 week to select for transduced cells. Jurkat-TCR + cell lines were validated for the presence of correctly folded TCR on the cell surface by flow cytometry using a monoclonal antibody targeting the mouse TCRβ constant region (APC/Fire750-conjugated; clone H57-597, 109246, BioLegend; Extended Data Fig. 5a ). Flow cytometry data were collected on a custom-configured BD Fortessa using FACSDiva software (v8.0.1; Becton Dickinson) and analysed using FlowJo version 10.7.2 software (BD Biosciences).
Specificity validation of putative cross-reactive TCR sequences
The specificity of TCR-expressing Jurkat T cell lines was validated by tetramer staining using the same reagents used for single-cell sorting PBMCs (above). In brief, 1 × 10 6 Jurkat-TCR + cell lines or untransduced Jurkat J76.7 (TCR-null; background control) were washed in 1× PBS and resuspended in 50 μl FACS buffer (1× PBS and 0.04% BSA) and a unique tetramer cocktail containing MADS–tetramer–PE (1:10 dilution), MADS–tetramer–APC (1:10 dilution), SNX8–tetramer–PE (1:10 dilution) and SNX8–tetramer–BV421 (1:10 dilution) based on the restricting HLA type (A*02:01 and A*02:06). Tetramers conjugated to the Wuhan peptide sequence (LQLPQGTTL), including Wuhan–tetramer–PE (1:10 dilution) and Wuhan–tetramer–APC (1:10 dilution), were also tested. A second set of wells were set up in which each individual tetramer was used to stain cells. Cells were incubated in the dark at 25 °C for 30 min after which 50 µl of FACS buffer containing Ghost Dye Violet 510 Viability Dye (1:400 dilution; lot D0870061322133, 13-0870-T500, Tonbo Biosciences) was added for an additional 30-min incubation in the dark at 25 °C. Cells were then washed twice with 1 ml FACS buffer, suspended in 300 μl FACS and analysed by flow cytometry on a custom-configured BD Fortessa using FACSDiva software (v8.0.1; Becton Dickinson). Cell population gating and fluorescence analysis was performed using FlowJo version 10.7.2 software (BD Biosciences) as described in Extended Data Fig. 7e .
scRNA-seq analysis
To assess the cell-type specificity in a relevant disease context, we analysed SNX8 expression from a single-cell sequencing of PBMC samples from patients with severe, mild or asymptomatic COVID-19 infection, influenza virus infection and healthy controls 48 . Gene expression data from 59,572 pre-filtered cells were downloaded from the Gene Expression Omnibus database under accession GSE149689 for analysis and downstream processing with scanpy v1.10.0 (ref. 63 ). Cells with (1) less than 1,000 total counts, (2) less than 800 expressed genes, and (3) more than 3,000 expressed genes were filtered out as further quality control, leaving 42,904 cells for downstream analysis. Gene expression data were normalized to have 10,000 counts per cell and were log1p transformed. Highly variable genes were calculated using the scanpy function highly_variable_genes using Seurat flavor with the default parameters (min_mean = 0.0125, max_mean = 3, and min_disp = 0.5) 64 . Only highly variable genes were used for further analysis. The total number of counts per cell was regressed out, and the gene expression matrix was scaled using the scanpy function scale with max_value = 10. Dimensionality reduction was performed using principal components analysis with 50 principal components. Batch balanced k -nearest neighbours, implemented with scanpy’s function bbknn, was used to compute the top neighbours and normalize batch effects 65 . The batch-corrected cells were clustered using the Leiden algorithm and projected into two dimensions with uniform manifold approximation and projection for visualization. Initial cluster identity was determined by finding marker genes with differential expression analysis performed using a Student’s t -test on log1p-transformed raw counts with the scanpy function rank_genes_groups 66 , 67 .
Statistical methods
All statistical analysis was performed in Python using the Scipy Stats package unless otherwise indicated. For comparisons of distributions of PhIP-seq enrichment between two groups, a non-parametric Kolmogorov–Smirnov test was utilized. For logistic-regression feature weighting, the Scikit-learn package 68 was used, and logistic-regression classifiers were applied to z -scored PhIP-seq values from individuals with MIS-C versus at-risk controls. A liblinear solver was used with L1 regularization, and the model was evaluated using a five-fold cross-validation (four of the five for training, and one of the five for testing). For the RLBAs and SLBAs, first an antibody index was calculated as follows: (sample value – mean blank value)/(positive control antibody values – mean blank values). For the alanine mutagenesis scans, blank values of each construct were combined, and a single mean was calculated. A normalization function was then applied to the experimental samples only (excluding antibody-only controls) to create a normalized antibody index ranging from 0 to 1. Comparisons between two groups of samples were performed using a Mann–Whitney U -test. An antibody was considered to be ‘positive’ when the normalized antibody index in a sample was greater than 3 s.d. above the mean of controls. When comparing two groups of normally distributed data, a Student’s t -test was performed.
Reporting summary
Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.
Data availability
The published article includes all datasets generated or analysed as a part of this study. Individual source data are provided with associated figures (where appropriate) per the data-sharing agreement stipulated under the Ruth L. Kirschstein National Research Service Award Individual Postdoctoral Fellowship (award no. F32AI157296 to R.C.M.). Raw flow cytometry source files can be made available on reasonable request. All PhIP-seq data are publicly available via a Dryad digital repository ( https://doi.org/10.7272/Q6SJ1HVH ). Raw TCR reads are available through the NCBI Sequence Read Archive (SRA) BioProject PRJNA1110271 , with associated BioSample accession numbers SAMN41334731 , SAMN41334732 , SAMN41334730 and SAMN41334729 . Source data are provided with this paper.
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Acknowledgements
The following members of the Overcoming COVID-19 Network Investigators study group were all closely involved with the design, implementation and oversight of the Overcoming COVID-19 study, as well as collecting patient samples and data: M. Kong, H. Kelley, M. Murdock, C. Colston. K. V. Typpo, K. Irby, R. C. Sanders Jr, M. Yates, C. Smith, N. Z. Cvijanovich, M. S. Zinter, A. B. Maddux, E. Port, R. Mansour, S. Shankman, N. Baig, F. Zorensky, P. S. Espinal, B. Chatani, G. McLaughlin, K. M. Tarquinio, K. Jones, B. M. Coates, C. M. Rowan, A. G. Randolph, M. M. Newhams, S. Kucukak, T. Novak, E. R. McNamara, H. Kyung Moon, T. Kobayashi, J. Melo, S. R. Jackson, M. K. Echon Rosales, C. Young, S. R. Chen, J. Chou, R. Da Costa Aguiar, M. Gutierrez-Arcelus and M. Elkins. The Taking On COVID-19 Together team include: D. Williams, L. Williams, L. Cheng, Y. Zhang, D. Crethers, D. Morley, S. Steltz, K. Zakar, M. A. Armant, F. Ciuculescu, H. R. Flori, M. K. Dahmer, E. R. Levy, S. Behl, N. M. Drapeau, C. V. Hobbs, J. E. Schuster, A. Kietzman, S. Hill, M. L. Cullimore, R. J. McCulloh, S. J. Gertz, S. P. Schwartz, T. C. Walker, R. A. Nofziger, M. A. Staat, C. C. Rohlfs, J. C. Fitzgerald, R. Burnett, J. Bush, E. H. Mack, N. Reed, N. B. Halasa, L. L. Loftis, H. Crandall and K. K. Ampofo. Members of the US Centers for Disease Control and Prevention COVID-19 Response Team on the Overcoming COVID-19 study were L. D. Zambrano, M. M. Patel and A. P. Campbell. The authors acknowledge the New York Blood Center for contributing pre-COVID-19 healthy donor blood samples, which were used as controls for the SARS-CoV-2 library PhIP-seq. The authors acknowledge the contributions of W. Browne and S. Pleasure for their work investigating potential central nervous system-specific autoimmunity in MIS-C; T. Kharel for help designing the Python code used in the analysis; D. Blauvelt for ideas regarding the application of advanced statistics to PhIP-seq data analysis; and S. A. Schattgen for thoughtful discussion of TCR sequencing and TCR similarity network analysis and help with deposition of the TCR sequencing into the Sequence Read Archive. BioRender ( https://biorender.com ) was used to build graphics for Fig. 1a and Extended Data Fig. 4a . This work was supported by the Pediatric Scientist Development Program and the Eunice Kennedy Shriver National Institute of Child Health and Human Development (K12-HD000850 to A.B.), and the Chan Zuckerberg Biohub SF (to J.L.D. and M.S.A.). Overcoming COVID-19 Study Network enrolment, patient data and specimen collections were supported by the CDC contracts 75D30120C07725, 75D30121C10297 and 75D30122C13330 from the Centers for Disease Control and Prevention to Boston Children’s Hospital to A.G.R. and the National Institute of Allergy and Infectious Diseases (R01AI154470) to A.G.R. Patient clinical data and specimens also collected at Boston Children’s Hospital for the Taking On COVID-19 Together (TOCT) study were supported in part by the Boston Children’s Hospital Emerging Pathogens and Epidemic Response Cluster of Clinical Research Excellence and the Institutional Centers for Clinical and Translational Research to A.G.R. and K.L.M. P.G.T. is supported by the American Lebanese Syrian Associated Charities at St. Jude Children’s Research Hospital (SJCRH) and funding from the National Institute of Allergy and Infectious Diseases (5R01AI154470-03, 2R01AI136514-06, 3P01AI165077-01S1, 75N93021C00016 and U01 AI144616). R.C.M. is supported by a Ruth L. Kirschstein National Research Service Award Individual Postdoctoral Fellowship award (F32AI157296).
Author information
These authors contributed equally: Aaron Bodansky, Robert C. Mettelman
These authors jointly supervised this work: Paul G. Thomas, Adrienne G. Randolph, Mark S. Anderson, Joseph L. DeRisi
Authors and Affiliations
Department of Pediatrics, Division of Critical Care, University of California San Francisco, San Francisco, CA, USA
Aaron Bodansky & Matt S. Zinter
Department of Host–Microbe Interactions, St. Jude Children’s Research Hospital, Memphis, TN, USA
Robert C. Mettelman, Mikhail V. Pogorelyy, Walid Awad, Allison M. Kirk & Paul G. Thomas
Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
Joseph J. Sabatino Jr, Colin R. Zamecnik & Michael R. Wilson
Department of Neurology, University of California San Francisco, San Francisco, CA, USA
Joseph J. Sabatino Jr, Colin R. Zamecnik, John V. Pluvinage & Michael R. Wilson
Department of Biochemistry and Biophysics, University of California San Francisco, San Francisco, CA, USA
Sara E. Vazquez, Haleigh S. Miller, Andrew F. Kung, Elze Rackaityte, Jayant V. Rajan, Hannah Kortbawi, Caleigh Mandel-Brehm, Kelsey Zorn & Joseph L. DeRisi
Division of Immunology, Department of Pediatrics, Boston, MA, USA
Department of Pediatrics, Harvard Medical School, Boston, MA, USA
Janet Chou, Kristin L. Moffitt & Adrienne G. Randolph
Department of Anesthesiology, Critical Care and Pain Medicine, Boston Children’s Hospital, Boston, MA, USA
Tanya Novak & Adrienne G. Randolph
Department of Anesthesia, Harvard Medical School, Boston, MA, USA
Department of Pediatric, Division of Infectious Diseases, Boston Children’s Hospital, Boston, MA, USA
Kristin L. Moffitt
Biological and Medical Informatics Program, University of California San Francisco, San Francisco, CA, USA
Haleigh S. Miller & Andrew F. Kung
Medical Scientist Training Program, University of California San Francisco, San Francisco, CA, USA
Hannah Kortbawi
Chan Zuckerberg Biohub SF, San Francisco, CA, USA
Anthea Mitchell, Chung-Yu Wang, Aditi Saxena & Joseph L. DeRisi
Diabetes Center, School of Medicine, University of California San Francisco, San Francisco, CA, USA
David J. L. Yu & Mark S. Anderson
Biomedical Sciences Program, University of California San Francisco, San Francisco, CA, USA
James Asaki
COVID-19 Response Team and Coronavirus and Other Respiratory Viruses Division, Centers for Disease Control and Prevention, Atlanta, GA, USA
Laura D. Zambrano & Angela P. Campbell
Department of Medicine, Division of Endocrinology and Metabolism, University of California San Francisco, San Francisco, CA, USA
Mark S. Anderson
Department of Pediatrics, Division of Critical Care Medicine, Baylor College of Medicine, Houston, TX, USA
- Laura L. Loftis
Department of Pediatrics, Division of Infectious Diseases, University of Mississippi Medical Center, Jackson, MS, USA
Charlotte V. Hobbs
Department of Pediatrics, Division of Critical Care Medicine, Emory University School of Medicine, Children’s Healthcare of Atlanta, Atlanta, GA, USA
Keiko M. Tarquinio
Department of Pediatrics, Division of Pediatric Critical Care Medicine, University of Alabama at Birmingham, Birmingham, AL, USA
Michele Kong
Department of Anesthesiology and Critical Care, Children’s Hospital of Philadelphia, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA
Julie C. Fitzgerald
Personalized Medicine and Health Outcomes Research, Nicklaus Children’s Hospital, Miami, FL, USA
Paula S. Espinal
Department of Pediatrics, University of North Carolina at Chapel Hill Children’s Hospital, Chapel Hill, NC, USA
Tracie C. Walker & Stephanie P. Schwartz
Department of Pediatrics, Division of Pediatric Critical Care, University of Utah, Primary Children’s Hospital, Salt Lake City, UT, USA
Hillary Crandall
Section of Pediatric Critical Care, Department of Pediatrics, Arkansas Children’s Hospital, Little Rock, AR, USA
Katherine Irby
Department of Pediatrics, Division of Infectious Diseases, University of Cincinnati and Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
Mary Allen Staat
Department of Pediatrics, Division of Pediatric Critical Care Medicine, Indiana University School of Medicine and Riley Hospital for Children, Indianapolis, IN, USA
Courtney M. Rowan
Department of Pediatrics, Division of Pediatric Infectious Diseases, Children’s Mercy Kansas City, Kansas City, MO, USA
Jennifer E. Schuster
Department of Pediatrics, Division of Pediatric Infectious Diseases, Vanderbilt University Medical Center, Nashville, TN, USA
Natasha B. Halasa
Department of Pediatrics, Division of Pediatric Critical Care, Cooperman Barnabas Medical Center, Livingston, NJ, USA
Shira J. Gertz
Division of Pediatric Critical Care Medicine, Medical University of South Carolina, Charleston, SC, USA
Elizabeth H. Mack
Department of Pediatrics, Section of Critical Care Medicine, University of Colorado School of Medicine and Children’s Hospital Colorado, Aurora, CO, USA
Aline B. Maddux
Division of Critical Care Medicine, UCSF Benioff Children’s Hospital Oakland, Oakland, CA, USA
Natalie Z. Cvijanovich
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Overcoming COVID-19 Network Investigators
- , Charlotte V. Hobbs
- , Keiko M. Tarquinio
- , Michele Kong
- , Julie C. Fitzgerald
- , Paula S. Espinal
- , Tracie C. Walker
- , Stephanie P. Schwartz
- , Hillary Crandall
- , Katherine Irby
- , Mary Allen Staat
- , Courtney M. Rowan
- , Jennifer E. Schuster
- , Natasha B. Halasa
- , Shira J. Gertz
- , Elizabeth H. Mack
- , Aline B. Maddux
- , Natalie Z. Cvijanovich
- & Matt S. Zinter
Contributions
A.B., R.C.M., J.J.S.Jr, S.E.V., J.C., P.G.T., A.G.R., M.S.A. and J.L.D. conceptualized the study. A.B., R.C.M., J.J.S.Jr, S.E.V., E.R., C.R.Z., A.F.K., J.V.R., J.C., P.G.T., A.G.R., M.S.A. and J.L.D. curated the methodology. A.B., R.C.M., J.J.S.Jr, S.E.V., A.M., C.-Y.W., A.S., J.V.P., D.J.L.Y., H.K., W.A., A.M.K. and C.M.-B. performed or contributed to experiments. A.B., R.C.M., J.J.S.Jr, H.S.M., A.F.K., J.A. and M.V.P. performed the formal analysis. K.Z., T.N., L.D.Z., A.P.C., A.G.R., K.L.M. and the Overcoming COVID-19 Network Investigators acquired the patient sample and clinical data. T.N., A.G.R. and the Overcoming COVID-19 Network Investigators curated the clinical data. A.B., H.S.M. and J.L.D. wrote the original draft of the manuscript. A.B., R.C.M., J.C., T.N., H.S.M., L.D.Z., A.P.C., P.G.T., A.G.R., M.R.W., M.S.A. and J.L.D. reviewed and edited the manuscript. J.C., P.G.T., A.G.R., M.S.A. and J.L.D. supervised the study.
Corresponding authors
Correspondence to Mark S. Anderson or Joseph L. DeRisi .
Ethics declarations
Competing interests.
J.L.D. reports being a founder and paid consultant for Delve Bio, Inc., and a paid consultant for the Public Health Company and Allen & Co. M.A.S. receives unrelated research funding from the National Institutes of Health, the Centers for Disease Control and Prevention, Cepheid and Merck and unrelated honoria from UpToDate, Inc. M.R.W. receives unrelated research grant funding from Roche/Genentech and Novartis, and received speaking honoraria from Genentech, Takeda, WebMD and Novartis. J.C. reports consulting fees from GLG group, payments from Elsevier for work as an Associate Editor, a patent pending for methods and compositions for treating and preventing T cell-driven diseases, payments related to participation on a Data Safety Monitoring Board or Advisory Board for Enzyvant, and is a member of the Diagnostic Laboratory Immunology Committee of the Clinical Immunology Society. M.S.Z. receives unrelated funding from the National Heart, Lung, and Blood Institute and consults for Sobi. N.B.H. reports unrelated previous grant support from Sanofi and Quidel, and current grant support from Merck. C.V.H. reports being a speaker for Biofire and a reviewer for UpToDate, Inc. and Dynamed.com. A.G.R. receives royalties as a section editor for Pediatric Critical Care Medicine UpToDate, Inc., and received honoraria for MIS-C-related Grand Round Presentations. A.G.R. is also on the medical advisor board of Families Fighting Flu and is Chair of the International Sepsis Forum, which is supported by industry and has received reagents from Illumina, Inc. P.G.T. is on the Scientific Advisory Board of Immunoscape and Shennon Bio, has received research support and personal fees from Elevate Bio, and consulted for 10X Genomics, Illumina, Pfizer, Cytoagents, Merck and JNJ. The findings and conclusions in this report are those of the authors and do not necessarily represent the views of the Centers for Disease Control and Prevention nor the National Institute of Allergy and Infectious Diseases. All other authors declare no competing interests.
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Extended data figures and tables
Extended data fig. 1 previously reported autoantigens and phenotypic associations of novel autoantigens..
a , Heatmap showing distribution of PhIP-Seq enrichments (FC > Mock-IP) of previously reported MIS-C autoantibodies in MIS-C patients ( n = 199) and at-risk controls (n = 45). (b) Stripplots and boxplots showing distribution of signal (normalized antibody index) for antibodies targeting IL-1 receptor antagonist (IL-1Ra) measured by RLBA in at-risk controls (blue; n = 45), MIS-C patient samples containing IVIG (red; n = 135), and MIS-C patient samples without IVIG (green; n = 61). Dotted line at 3 standard deviations above the mean of controls. Two-sided Mann-Whitney U testing was performed (exact P values shown in figure). c , Heatmap of P values (two-sided Kolmogorov-Smirnov testing) for differences in autoantibody enrichment for MIS-C patients ( n = 199) with versus without each clinical phenotype (numbers vary for each phenotype and are shown in Extended Data Table 2 ). Significant P values in the negative direction (in which there is increased signal in individuals without the phenotype) are masked (colored as P > 0.05). For each autoantigen, tissue RNA-sequencing data from Human Protein Atlas (Proteinatlas.org) is shown. Amount of expression in cardiac tissue in top row (Very high = nTPM >1000, High=nTPM 100-1000, Moderate=nTPM 10-100, Low=nTPM <10), and predominant tissue type in second-from-top row. Explanations of criteria for MIS-C phenotypes, and distribution of each phenotype within the cohort, can be found in Extended Data Table 2 .
Extended Data Fig. 2 Orthogonally validated autoantibodies classify MIS-C and can be epitope specific.
a , Stripplots and boxplots showing radioligand binding assay (RLBA) values (normalized antibody indices) for each of the top 3 autoantibodies identified by PhIP-Seq logistic regression in individuals with MIS-C ( n = 197 for ERFL, n = 196 for SNX8, n = 196 for KDELR1) and each at-risk control ( n = 45 for ERFL, SNX8, and KDELR1). Two-sided Mann-Whitney U testing performed (exact P values shown in figure). b , Logistic regression receiver operating characteristic (ROC) curve using RLBA values as input to distinguish MIS-C patients ( n = 196) from at-risk controls ( n = 45) iterated 1,000 times. c , Stripplots and boxplots showing RLBA enrichments (normalized antibody indices) only in those MIS-C samples without IVIG ( n = 61 for ERFL, n = 60 for SNX8, n = 60 for KDELR1) relative to at-risk controls ( n = 45 for ERFL, SNX8, and KDELR1). Two-sided Mann-Whitney U testing performed (exact P values shown in figure). d , Stripplots abd boxplots showing RLBA enrichments (normalized antibody indices) for ERFL, SNX8, and KDELR1 in an independent cohort of children with MIS-C (red; n = 24 for each RLBA) compared to children severely ill with acute COVID-19 (yellow; n = 29 for each RLBA) and at-risk controls (blue; n = 45 for each RLBA). Two-sided Mann-Whitney U testing performed (exact P values shown in figure). e , Logistic regression ROC curves for classification of the independent MIS-C cohort ( n = 24) versus at-risk controls ( n = 45) (left) and the independent MIS-C ( n = 24) cohort versus children severely ill with acute COVID-19 ( n = 29) (right). f , Paired stripplots and boxplots showing SLBA enrichments (normalized antibody indices) in MIS-C patients ( n = 182) and at-risk controls ( n = 45) for the full 49 amino acid SNX8 wild-type (WT) polypeptide fragment (lavender) relative to the same SNX8 fragment with alanine mutagenesis of the [PSRMQMPQG] epitope (white). SNX8 WT fragment SLBA values are the means of technical replicates, SNX8 epitope mutagenesis values are from a single experiment. Two-sided Mann-Whitney U testing performed (exact P values shown in figure). For all boxplots in the figure, the whiskers extend to 1.5 times the interquartile range (IQR) from the quartiles, the boxes represent the IQR, and centre lines represent the median.
Extended Data Fig. 3 HLA associations of SNX8 activated T cells and HLA binding characteristics of peptides containing SNX8/MADS shared epitope motif.
a , Stripplots and boxplots showing distribution of CD4 + , CD8 + , and total T cells which activate in response to either vehicle (culture media + 0.2% DMSO) or SNX8 peptide pool (SNX8 peptide + culture media + 0.2% DMSO) using AIM assay in MIS-C patients ( n = 9) and controls ( n = 10). Patient HLA type indicated by color of dot. HLA unpredicted means patient contained none of the MIS-C associated HLA types. Dotted line at 3 standard deviations above the mean of the SNX8 stimulated controls. Two-sided Mann-Whitney U testing was performed (exact P values shown in figure). b , Computationally predicted HLA class I presentation scores (Immune Epitope Database; IEDB.org) for each possible peptide fragment of full-length SARS-CoV-2 N protein for each of the three MIS-C associated HLA types (A*02, B*35 and C*04) relative to a reference set of HLA-types encompassing over 99% of humans. Those fragments containing the MADS similarity region “LQLPQG” in orange. Data normally distributed; two-sided t-tests were performed (exact P values shown in figure). Percent of fragments within each specific HLA type with a score greater than 0.1 (likely to be presented) shown on right. c , Identical analysis but using full length SNX8 protein rather than SARS-CoV-2 NP, and the SNX8 similarity region “MGMPQG” rather than the MADS region “LQLPQG”. Data normally distributed; two-sided t-tests were performed (exact P values shown in figure). d , HLA binding results from β2m folding assay for SARS-CoV-2 N and SNX8 peptides representative of two independent evaluations. Each peptide tested for binding in HLA-A*02:01, A*02:06, and B*35:01 class I monomers. Data presented as geometric mean fluorescence intensity (gMFI) of PE-conjugated anti-human β2m antibody staining of peptide-HLA monomers relative to negative (no peptide; unloaded HLA monomer) and positive (strong binding peptide; CMV pp65 495-503 [NLVPMVATV]) controls. For all boxplots in the figure, the whiskers extend to 1.5 times the interquartile range (IQR) from the quartiles, the boxes represent the IQR, and centre lines represent the median.
Extended Data Fig. 4 Identification, activation, and HLA restriction, of cross-reactive CD8+ T cells.
a , Gating strategy used to identify CD8 + T cells which bound to SNX8 epitope and/or MADS N protein epitope (CD8 + T cells positive for PE). Representative MIS-C patient and control showing each CD8 + T cell which bound to any tetramer (PE + ) and the relative binding of that T cell to both the SNX8 epitope (BV421 + ) and the MADS N protein epitope (APC + ) identifying cross-reactive T cells (PE + APC + BV421 + ). Schematics in panel a were created using BioRender ( https://www.biorender.com ). b , Stripplots and boxplots showing percentage of CD8 + T cells which are cross-reactive to both SNX8 and MADS in MIS-C patients ( n = 3) and controls ( n = 3). Insufficient numbers to perform robust statistical testing. c , Stripplots and boxplots showing percentage of total T cells which activate in response to either vehicle (culture media + 0.2% DMSO) or the SNX8 Epitope (SNX8 Epitope (Materials) + culture media + 0.2% DMSO) in MIS-C patients ( n = 2) and at-risk controls ( n = 4) measured by AIM assay. Insufficient numbers to perform robust statistical testing. Dotted line at 3 standard deviations above mean of SNX8 Epitope stimulated controls. d , TCRdist Similarity Network of 48 unique, paired TCRαβ sequences ( n = 259 sequences) obtained from four patients with MIS-C. CD8 + T cells were sorted from PBMCs directly ex vivo or after 10-days of peptide expansion and staining with A*02:01 or A*02:06 HLA class I tetramers loaded with MADS [LQLPQGITL] and SNX8 [MQMPQGNPL] peptides. Each node represents a unique TCR clonotype. Edges connect nodes with a TCRdist score < 150. Dashed lines surround TCR similarity clusters. Node size corresponds to T cell clone size. Nodes are colored based on HLA restriction. TCRs selected for further testing are numbered TCR #1-8. Convergent node circled green. For all boxplots in the figure, the whiskers extend to 1.5 times the interquartile range (IQR) from the quartiles, the boxes represent the IQR, and centre lines represent the median.
Extended Data Fig. 5 Evaluation of Jurkat-TCR lines.
a , Jurkat-76 cells stably expressing putative cross-reactive TCRs (#1-8) stained with anti-murine TCRβ constant region (mTCRβc). Plots depict frequency of transduced (mCherry + ) Jurkat cells with presence of surface TCR (APC/Fire 750 + ) as a percentage of total live cells. b , Jurkat-TCR + cell lines expressing putative cross-reactive TCRs #1-8 stained with individual or combination of HLA-A*02:01 or A*02:06 tetramers loaded with MADS [LQLPQGITL] and SNX8 [MQMPQGNPL] peptides. Blue contour plots indicate staining with MADS-Tetramer (PE) and MADS-Tetramer (APC); purple contour plots indicate staining with SNX8-Tetramer (PE) and SNX8-Tetramer (BV421); red indicates combined staining with a pool of MADS/SNX8-Tetramer (PE), MADS-Tetramer (APC), and SNX8-Tetramer (BV421). Plots shown are gated from total PE + cells. Plots with confirmed cross-reactive TCRs outlined in red. c , Jurkat-TCR+ cell lines expressing putative cross-reactive TCRs #1-8 stained with individual HLA-A*02:01 or A*02:06 tetramers loaded with MADS Wuhan [LQLPQGTTL] peptide. Gate values indicate frequency of MADS-APC + cells as percentage of total MADS-PE + cells. Outliers shown in contour plots. Flow plots representative of two independent evaluations.
Extended Data Fig. 6 SNX8 expression during viral infection.
a , UMAPs showing SNX8 expression in various peripheral blood cell types during SARS-CoV-2 infection. b , Mean expression and percent of cells expressing SNX8 in peripheral blood subsets during SARS-CoV-2 infection. c , Mean expression and percent of cells expressing SNX8 averaged across all peripheral blood mononuclear cells from SARS-CoV-2 infected individuals without symptoms, with mild symptoms, or with severe disease compared to uninfected controls. d , Mean expression and percent of cells expressing SNX8 , OAS1 , OAS2 , and MAVS in peripheral blood subsets during SARS-CoV-2 infection. e , Relative expression of SNX8 , OAS1 , OAS2 , and MAVS during influenza virus infection compared to different severities of SARS-CoV-2 infection.
Extended Data Fig. 7 Representative flow cytometry gating.
a , Flow cytometry gating strategy for identifying CD4 positive and CD8 positive T cells for the AIM analysis with representative activation induced marker (AIM) assay flow cytometry gating strategy measuring percent of CD4 + T cells which activate (CD137 + OX40 + ) and percent of CD8 + T cells which activate (CD137 + CD69 + ) in response to SNX8 protein. b , Flow cytometry gating strategy for the initial SNX8/MADS tetramer cross-reactivity assay (Extended Data Fig. 4a,b ) showing isolation of PE-tetramer positive CD8 positive T cells. c , Flow cytometry plots showing results of serotyping for the PBMCs used in the initial SNX8/MADS tetramer cross-reactivity assay (Extended Data Fig. 4a,b ) which did not have sufficient cells for genotyping. Shown is the 1 MIS-C patient (far left) and 3 controls (middle 3) which are positive for HLA-A*02 and were used and one control negative for HLA-A*02 (far right) which was not used. d , Index sorting strategy for patient PBMCs from ex vivo and peptide expansion experiments for TCR sequencing. Single cells were sorted from live/lineage (CD4, CD14, CD16, CD19)-negative, CD3 + CD8 + T lymphocytes positive for MADS/SNX8-Tetramer (PE) and MADS-Tetramer (APC) and/or SNX8-Tetramer (BV421). e , Flow cytometry gating strategy to evaluate putative cross-reactive Jurkat-TCRs. Gates include single, live, transduced Jurkat lymphocytes triple positive for MADS/SNX8-(PE), MADS-(APC), and SNX8-(BV421) tetramers shown in Fig. 4 .
Supplementary information
Supplementary table 1.
The complete set of primers used for the single-cell T cell receptor (TCR) sequencing by nested multiplex polymerase chain reaction (PCR).
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Bodansky, A., Mettelman, R.C., Sabatino, J.J. et al. Molecular mimicry in multisystem inflammatory syndrome in children. Nature 632 , 622–629 (2024). https://doi.org/10.1038/s41586-024-07722-4
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Research Summary. Definition: A research summary is a brief and concise overview of a research project or study that highlights its key findings, main points, and conclusions. It typically includes a description of the research problem, the research methods used, the results obtained, and the implications or significance of the findings.
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However, a research summary and abstract are two very different things with individual purpose. To start with, a research summary is written at the end while the abstract comes at the beginning of a research paper. A research summary captures the essence of the paper at the end of your document. It focuses on your topic, methods, and findings.
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How to Summarize a Research Article. Research articles use a standard format to clearly communicate information about an experiment. A research article usually has seven major sections: Title, Abstract, Introduction, Method, Results, Discussion, and References. Determine your focus. The first thing you should do is to decide why you need to ...
Writing a summary of a research paper involves becoming very familiar with the topic - sometimes, it is impossible to understand the content without learning about the current state of knowledge, as well as key definitions, concepts, models. ... Below are some defining elements of a sample research summary written from an imaginary article ...
A summary must be coherent and cogent and should make sense as a stand-alone piece of writing. It is typically 5% to 10% of the length of the original paper; however, the length depends on the length and complexity of the article and the purpose of the summary. Accordingly, a summary can be several paragraphs or pages, a single paragraph, or ...
Example 2: Summary of a Research Paper. Original Paper: In a study titled "The Impact of Urbanisation on Bee Populations," researchers conducted a year-long observation on bee colonies in three urban areas and three rural areas. Using specific metrics like colony health, bee productivity, and population size, the study found that urban ...
One-paragraph summary - one sentence per supporting detail, providing 1-2 examples for each. Multi-paragraph summary - one paragraph per supporting detail, providing 2-3 examples for each. ... Adapted from "Guidelines for Using In-Text Citations in a Summary (or Research Paper)" by Christine Bauer-Ramazani, 2020. Additional Resources.
A research paper summary is a short overview of a research paper. Generally, a research paper summary is about 300-400 words long, though with longer papers, they're usually no more than 10 percent the length of the original paper. Research paper summaries play an important role in academia.
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1. Scan and extract the main points. First things first, so you have to read the paper. But that doesn't mean you have to read it from start to finish. Start by scanning the article for its main points. Here's the essential information to extract from the research paper you have in front of you: Authors, year, doi.
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Introduction. Writing a summary or abstract teaches you how to condense information and how to read an article more effectively and with better understanding. Research articles usually contain these parts: Title/Author Information, Abstract, Introduction, Methodology, Result or Findings, Discussion or Conclusion, and References.
Some summaries can even be as short as one sentence. 3. State the research question and hypothesis. To begin your summary, start by summarizing what the authors aim to answer and what their hypothesis was. You can combine both the question and the hypothesis into one short sentence to open up your summary.
In such cases, the research report and executive summary are often written for policy makers outside of academe, while abstracts are written for the academic community. Professors, therefore, assign the writing of executive summaries so students can practice synthesizing and writing about the contents of comprehensive research studies for ...
Step 3: Get the Gist. The third and final paragraph will be the gist of your research paper. This includes the heart or the main part, the findings and the conclusion. The gist has to be a general summary of your research paper. It should have the facts that support it, the findings of your research and the hypothesis.
The executive summary briefly describes the study's key points and suggests changes, actions and implementation strategies for the business. You can use the following steps to write an executive summary for a research paper: 1. Read the entire research paper.
By simply following these simple steps or guides, you are going to find it easier to do a page research summary. 1. Read the Chapter and Make a Draft. The best way to begin is to make a draft while you read the chapter or the chapters you are told to summarize.
Course Paper Template: Downloading and Using the Template. Course Paper Template: A Tour of the Template ... In their research, DeBruin-Parecki and Slutzky's ... Audio: Let's take a look at this sample summary. As you can see, this summary is a high-level overview of this source. It starts by introducing the source's authors with a full ...
Like an abstract in a published research article, the purpose of an article summary is to give the reader a brief, structured overview of the study. To write a good summary, identify what information is important and condense that information for your reader. The better you understand a subject, the easier it is to explain it thoroughly and ...
Scholarcy's AI summarization tool is designed to generate accurate, reliable article summaries. Our summarizer tool is trained to identify key terms, claims, and findings in academic papers. These insights are turned into digestible Summary Flashcards. Scroll in the box below to see the magic ⤸. The knowledge extraction and summarization ...
Before conducting a study, a research proposal should be created that outlines researchers' plans and methodology and is submitted to the concerned evaluating organization or person. Creating a research proposal is an important step to ensure that researchers are on track and are moving forward as intended. A research proposal can be defined as a detailed plan or blueprint for the proposed ...
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Increased funding for a wall on the US-Mexico border - one of Trump's signature proposals in 2016 - is proposed in the document. Project 2025 also proposes dismantling the Department of Homeland ...
Multisystem inflammatory syndrome in children (MIS-C) is a severe, post-infectious sequela of SARS-CoV-2 infection1,2, yet the pathophysiological mechanism connecting the infection to the broad ...
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