Show that you understand the current state of research on your topic.
The length of a research proposal can vary quite a bit. A bachelor’s or master’s thesis proposal can be just a few pages, while proposals for PhD dissertations or research funding are usually much longer and more detailed. Your supervisor can help you determine the best length for your work.
One trick to get started is to think of your proposal’s structure as a shorter version of your thesis or dissertation , only without the results , conclusion and discussion sections.
Download our research proposal template
Writing a research proposal can be quite challenging, but a good starting point could be to look at some examples. We’ve included a few for you below.
Like your dissertation or thesis, the proposal will usually have a title page that includes:
The first part of your proposal is the initial pitch for your project. Make sure it succinctly explains what you want to do and why.
Your introduction should:
To guide your introduction , include information about:
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As you get started, it’s important to demonstrate that you’re familiar with the most important research on your topic. A strong literature review shows your reader that your project has a solid foundation in existing knowledge or theory. It also shows that you’re not simply repeating what other people have already done or said, but rather using existing research as a jumping-off point for your own.
In this section, share exactly how your project will contribute to ongoing conversations in the field by:
Following the literature review, restate your main objectives . This brings the focus back to your own project. Next, your research design or methodology section will describe your overall approach, and the practical steps you will take to answer your research questions.
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To finish your proposal on a strong note, explore the potential implications of your research for your field. Emphasize again what you aim to contribute and why it matters.
For example, your results might have implications for:
Last but not least, your research proposal must include correct citations for every source you have used, compiled in a reference list . To create citations quickly and easily, you can use our free APA citation generator .
Some institutions or funders require a detailed timeline of the project, asking you to forecast what you will do at each stage and how long it may take. While not always required, be sure to check the requirements of your project.
Here’s an example schedule to help you get started. You can also download a template at the button below.
Download our research schedule template
Research phase | Objectives | Deadline |
---|---|---|
1. Background research and literature review | 20th January | |
2. Research design planning | and data analysis methods | 13th February |
3. Data collection and preparation | with selected participants and code interviews | 24th March |
4. Data analysis | of interview transcripts | 22nd April |
5. Writing | 17th June | |
6. Revision | final work | 28th July |
If you are applying for research funding, chances are you will have to include a detailed budget. This shows your estimates of how much each part of your project will cost.
Make sure to check what type of costs the funding body will agree to cover. For each item, include:
To determine your budget, think about:
If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.
Methodology
Statistics
Research bias
Once you’ve decided on your research objectives , you need to explain them in your paper, at the end of your problem statement .
Keep your research objectives clear and concise, and use appropriate verbs to accurately convey the work that you will carry out for each one.
I will compare …
A research aim is a broad statement indicating the general purpose of your research project. It should appear in your introduction at the end of your problem statement , before your research objectives.
Research objectives are more specific than your research aim. They indicate the specific ways you’ll address the overarching aim.
A PhD, which is short for philosophiae doctor (doctor of philosophy in Latin), is the highest university degree that can be obtained. In a PhD, students spend 3–5 years writing a dissertation , which aims to make a significant, original contribution to current knowledge.
A PhD is intended to prepare students for a career as a researcher, whether that be in academia, the public sector, or the private sector.
A master’s is a 1- or 2-year graduate degree that can prepare you for a variety of careers.
All master’s involve graduate-level coursework. Some are research-intensive and intend to prepare students for further study in a PhD; these usually require their students to write a master’s thesis . Others focus on professional training for a specific career.
Critical thinking refers to the ability to evaluate information and to be aware of biases or assumptions, including your own.
Like information literacy , it involves evaluating arguments, identifying and solving problems in an objective and systematic way, and clearly communicating your ideas.
The best way to remember the difference between a research plan and a research proposal is that they have fundamentally different audiences. A research plan helps you, the researcher, organize your thoughts. On the other hand, a dissertation proposal or research proposal aims to convince others (e.g., a supervisor, a funding body, or a dissertation committee) that your research topic is relevant and worthy of being conducted.
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. & George, T. (2023, November 21). How to Write a Research Proposal | Examples & Templates. Scribbr. Retrieved June 27, 2024, from https://www.scribbr.com/research-process/research-proposal/
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There are six steps to writing a standard abstract. (1) Begin with a broad statement about your topic. Then, (2) state the problem or knowledge gap related to this topic that your study explores. After that, (3) describe what specific aspect of this problem you investigated, and (4) briefly explain how you went about doing this. After that, (5) describe the most meaningful outcome(s) of your study. Finally, (6) close your abstract by explaining the broad implication(s) of your findings.
In this article, I present step-by-step guidelines for writing an abstract for an academic paper. These guidelines are fo llowed by an example of a full abstract that follows these guidelines and a few fill-in-the-blank templates that you can use to write your own abstract.
The basic structure of an abstract is illustrated below.
A standard abstract starts with a very general statement and becomes more specific with each sentence that follows until once again making a broad statement about the study’s implications at the end. Altogether, a standard abstract has six functions, which are described in detail below.
The first sentence of your abstract should briefly describe a problem that is of interest to your readers. When writing this first sentence, you should think about who comprises your target audience and use terms that will appeal to this audience. If your opening sentence is too broad, it might lose the attention of potential readers because they will not know if your study is relevant to them.
Too broad : Maintaining an ideal workplace environment has a positive effect on employees.
The sentence above is so broad that it will not grab the reader’s attention. While it gives the reader some idea of the area of study, it doesn’t provide any details about the author’s topic within their research area. This can be fixed by inserting some keywords related to the topic (these are underlined in the revised example below).
Improved : Keeping the workplace environment at an ideal temperature positively affects the overall health of employees.
The revised sentence is much better, as it expresses two points about the research topic—namely, (i) what aspect of workplace environment was studied, (ii) what aspect of employees was observed. The mention of these aspects of the research will draw the attention of readers who are interested in them.
After describing your topic in the first sentence, you can then explain what aspect of this topic has motivated your research. Often, authors use this part of the abstract to describe the research gap that they identified and aimed to fill. These types of sentences are often characterized by the use of words such as “however,” “although,” “despite,” and so on.
However, a comprehensive understanding of how different workplace bullying experiences are associated with absenteeism is currently lacking.
The above example is typical of a sentence describing the problem that a study intends to tackle. The author has noticed that there is a gap in the research, and they briefly explain this gap here.
Although it has been established that quantity and quality of sleep can affect different types of task performance and personal health, the interactions between sleep habits and workplace behaviors have received very little attention.
The example above illustrates a case in which the author has accomplished two tasks with one sentence. The first part of the sentence (up until the comma) mentions the general topic that the research fits into, while the second part (after the comma) describes the general problem that the research addresses.
After describing the general problem that motivated your research, the next sentence should express the specific aspect of the problem that you investigated. Sentences of this type are often indicated by the use of phrases like “the purpose of this research is to,” “this paper is intended to,” or “this work aims to.”
Uninformative : However, a comprehensive understanding of how different workplace bullying experiences are associated with absenteeism is currently lacking. The present article aimed to provide new insights into the relationship between workplace bullying and absenteeism .
The second sentence in the above example is a mere rewording of the first sentence. As such, it adds nothing to the abstract. The second sentence should be more specific than the preceding one.
Improved : However, a comprehensive understanding of how different workplace bullying experiences are associated with absenteeism is currently lacking. The present article aimed to define various subtypes of workplace bullying and determine which subtypes tend to lead to absenteeism .
The second sentence of this passage is much more informative than in the previous example. This sentence lets the reader know exactly what they can expect from the full research article.
In this part of your abstract, you should attempt to describe your study’s methodology in one or two sentences. As such, you must be sure to include only the most important information about your method. At the same time, you must also be careful not to be too vague.
Too vague : We conducted multiple tests to examine changes in various factors related to well-being.
This description of the methodology is too vague. Instead of merely mentioning “tests” and “factors,” the author should note which specific tests were run and which factors were assessed.
Improved : Using data from BHIP completers, we conducted multiple one-way multivariate analyses of variance and follow-up univariate t-tests to examine changes in physical and mental health, stress, energy levels, social satisfaction, self-efficacy, and quality of life.
This sentence is very well-written. It packs a lot of specific information about the method into a single sentence. Also, it does not describe more details than are needed for an abstract.
This is the most important part of the abstract—the other sentences in the abstract are there to explain why this one is relevant. When writing this sentence, imagine that someone has asked you, “What did you find in your research?” and that you need to answer them in one or two sentences.
Too vague : Consistently poor sleepers had more health risks and medical conditions than consistently optimal sleepers.
This sentence is okay, but it would be helpful to let the reader know which health risks and medical conditions were related to poor sleeping habits.
Improved : Consistently poor sleepers were more likely than consistently optimal sleepers to suffer from chronic abdominal pain, and they were at a higher risk for diabetes and heart disease.
This sentence is better, as the specific health conditions are named.
Most abstracts end with a short sentence that explains the main takeaway(s) that you want your audience to gain from reading your paper. Often, this sentence is addressed to people in power (e.g., employers, policymakers), and it recommends a course of action that such people should take based on the results.
Too broad : Employers may wish to make use of strategies that increase employee health.
This sentence is too broad to be useful. It does not give employers a starting point to implement a change.
Improved : Employers may wish to incorporate sleep education initiatives as part of their overall health and wellness strategies.
This sentence is better than the original, as it provides employers with a starting point—specifically, it invites employers to look up information on sleep education programs.
The abstract produced here is from a paper published in Electronic Commerce Research and Applications . I have made slight alterations to the abstract so that this example fits the guidelines given in this article.
(1) Gamification can strengthen enjoyment and productivity in the workplace. (2) Despite this, research on gamification in the work context is still limited. (3) In this study, we investigated the effect of gamification on the workplace enjoyment and productivity of employees by comparing employees with leadership responsibilities to those without leadership responsibilities. (4) Work-related tasks were gamified using the habit-tracking game Habitica, and data from 114 employees were gathered using an online survey. (5) The results illustrated that employees without leadership responsibilities used work gamification as a trigger for self-motivation, whereas employees with leadership responsibilities used it to improve their health. (6) Work gamification positively affected work enjoyment for both types of employees and positively affected productivity for employees with leadership responsibilities. (7) Our results underline the importance of taking work-related variables into account when researching work gamification.
In Sentence (1), the author makes a broad statement about their topic. Notice how the nouns used (“gamification,” “enjoyment,” “productivity”) are quite general while still indicating the focus of the paper. The author uses Sentence (2) to very briefly state the problem that the research will address.
In Sentence (3), the author explains what specific aspects of the problem mentioned in Sentence (2) will be explored in the present work. Notice that the mention of leadership responsibilities makes Sentence (3) more specific than Sentence (2). Sentence (4) gets even more specific, naming the specific tools used to gather data and the number of participants.
Sentences (5) and (6) are similar, with each sentence describing one of the study’s main findings. Then, suddenly, the scope of the abstract becomes quite broad again in Sentence (7), which mentions “work-related variables” instead of a specific variable and “researching” instead of a specific kind of research.
Copy and paste any of the paragraphs below into a word processor. Then insert the appropriate information to produce an abstract for your research paper.
Researchers have established that [Make a broad statement about your area of research.] . However, [Describe the knowledge gap that your paper addresses.] . The goal of this paper is to [Describe the purpose of your paper.] . The achieve this goal, we [Briefly explain your methodology.] . We found that [Indicate the main finding(s) of your study; you may need two sentences to do this.] . [Provide a broad implication of your results.] .
It is well-understood that [Make a broad statement about your area of research.] . Despite this, [Describe the knowledge gap that your paper addresses.] . The current research aims to [Describe the purpose of your paper.] . To accomplish this, we [Briefly explain your methodology.] . It was discovered that [Indicate the main finding(s) of your study; you may need two sentences to do this.] . [Provide a broad implication of your results.] .
Extensive research indicates that [Make a broad statement about your area of research.] . Nevertheless, [Describe the knowledge gap that your paper addresses.] . The present work is intended to [Describe the purpose of your paper.] . To this end, we [Briefly explain your methodology.] . The results revealed that [Indicate the main finding(s) of your study; you may need two sentences to do this.] . [Provide a broad implication of your results.] .
How to Write a Research Paper in English: A Guide for Non-native Speakers
How to Write an Abstract Quickly
Using the Present Tense and Past Tense When Writing an Abstract
An abstract summarizes, usually in one paragraph of 300 words or less, the major aspects of the entire paper in a prescribed sequence that includes: 1) the overall purpose of the study and the research problem(s) you investigated; 2) the basic design of the study; 3) major findings or trends found as a result of your analysis; and, 4) a brief summary of your interpretations and conclusions.
Writing an Abstract. The Writing Center. Clarion University, 2009; Writing an Abstract for Your Research Paper. The Writing Center, University of Wisconsin, Madison; Koltay, Tibor. Abstracts and Abstracting: A Genre and Set of Skills for the Twenty-first Century . Oxford, UK: Chandos Publishing, 2010;
Sometimes your professor will ask you to include an abstract, or general summary of your work, with your research paper. The abstract allows you to elaborate upon each major aspect of the paper and helps readers decide whether they want to read the rest of the paper. Therefore, enough key information [e.g., summary results, observations, trends, etc.] must be included to make the abstract useful to someone who may want to examine your work.
How do you know when you have enough information in your abstract? A simple rule-of-thumb is to imagine that you are another researcher doing a similar study. Then ask yourself: if your abstract was the only part of the paper you could access, would you be happy with the amount of information presented there? Does it tell the whole story about your study? If the answer is "no" then the abstract likely needs to be revised.
Farkas, David K. “A Scheme for Understanding and Writing Summaries.” Technical Communication 67 (August 2020): 45-60; How to Write a Research Abstract. Office of Undergraduate Research. University of Kentucky; Staiger, David L. “What Today’s Students Need to Know about Writing Abstracts.” International Journal of Business Communication January 3 (1966): 29-33; Swales, John M. and Christine B. Feak. Abstracts and the Writing of Abstracts . Ann Arbor, MI: University of Michigan Press, 2009.
I. Types of Abstracts
To begin, you need to determine which type of abstract you should include with your paper. There are four general types.
Critical Abstract A critical abstract provides, in addition to describing main findings and information, a judgment or comment about the study’s validity, reliability, or completeness. The researcher evaluates the paper and often compares it with other works on the same subject. Critical abstracts are generally 400-500 words in length due to the additional interpretive commentary. These types of abstracts are used infrequently.
Descriptive Abstract A descriptive abstract indicates the type of information found in the work. It makes no judgments about the work, nor does it provide results or conclusions of the research. It does incorporate key words found in the text and may include the purpose, methods, and scope of the research. Essentially, the descriptive abstract only describes the work being summarized. Some researchers consider it an outline of the work, rather than a summary. Descriptive abstracts are usually very short, 100 words or less. Informative Abstract The majority of abstracts are informative. While they still do not critique or evaluate a work, they do more than describe it. A good informative abstract acts as a surrogate for the work itself. That is, the researcher presents and explains all the main arguments and the important results and evidence in the paper. An informative abstract includes the information that can be found in a descriptive abstract [purpose, methods, scope] but it also includes the results and conclusions of the research and the recommendations of the author. The length varies according to discipline, but an informative abstract is usually no more than 300 words in length.
Highlight Abstract A highlight abstract is specifically written to attract the reader’s attention to the study. No pretense is made of there being either a balanced or complete picture of the paper and, in fact, incomplete and leading remarks may be used to spark the reader’s interest. In that a highlight abstract cannot stand independent of its associated article, it is not a true abstract and, therefore, rarely used in academic writing.
II. Writing Style
Use the active voice when possible , but note that much of your abstract may require passive sentence constructions. Regardless, write your abstract using concise, but complete, sentences. Get to the point quickly and always use the past tense because you are reporting on a study that has been completed.
Abstracts should be formatted as a single paragraph in a block format and with no paragraph indentations. In most cases, the abstract page immediately follows the title page. Do not number the page. Rules set forth in writing manual vary but, in general, you should center the word "Abstract" at the top of the page with double spacing between the heading and the abstract. The final sentences of an abstract concisely summarize your study’s conclusions, implications, or applications to practice and, if appropriate, can be followed by a statement about the need for additional research revealed from the findings.
Composing Your Abstract
Although it is the first section of your paper, the abstract should be written last since it will summarize the contents of your entire paper. A good strategy to begin composing your abstract is to take whole sentences or key phrases from each section of the paper and put them in a sequence that summarizes the contents. Then revise or add connecting phrases or words to make the narrative flow clearly and smoothly. Note that statistical findings should be reported parenthetically [i.e., written in parentheses].
Before handing in your final paper, check to make sure that the information in the abstract completely agrees with what you have written in the paper. Think of the abstract as a sequential set of complete sentences describing the most crucial information using the fewest necessary words. The abstract SHOULD NOT contain:
Abstract. Writing Center. University of Kansas; Abstract. The Structure, Format, Content, and Style of a Journal-Style Scientific Paper. Department of Biology. Bates College; Abstracts. The Writing Center. University of North Carolina; Borko, Harold and Seymour Chatman. "Criteria for Acceptable Abstracts: A Survey of Abstracters' Instructions." American Documentation 14 (April 1963): 149-160; Abstracts. The Writer’s Handbook. Writing Center. University of Wisconsin, Madison; Hartley, James and Lucy Betts. "Common Weaknesses in Traditional Abstracts in the Social Sciences." Journal of the American Society for Information Science and Technology 60 (October 2009): 2010-2018; Koltay, Tibor. Abstracts and Abstracting: A Genre and Set of Skills for the Twenty-first Century. Oxford, UK: Chandos Publishing, 2010; Procter, Margaret. The Abstract. University College Writing Centre. University of Toronto; Riordan, Laura. “Mastering the Art of Abstracts.” The Journal of the American Osteopathic Association 115 (January 2015 ): 41-47; Writing Report Abstracts. The Writing Lab and The OWL. Purdue University; Writing Abstracts. Writing Tutorial Services, Center for Innovative Teaching and Learning. Indiana University; Koltay, Tibor. Abstracts and Abstracting: A Genre and Set of Skills for the Twenty-First Century . Oxford, UK: 2010; Writing an Abstract for Your Research Paper. The Writing Center, University of Wisconsin, Madison.
Never Cite Just the Abstract!
Citing to just a journal article's abstract does not confirm for the reader that you have conducted a thorough or reliable review of the literature. If the full-text is not available, go to the USC Libraries main page and enter the title of the article [NOT the title of the journal]. If the Libraries have a subscription to the journal, the article should appear with a link to the full-text or to the journal publisher page where you can get the article. If the article does not appear, try searching Google Scholar using the link on the USC Libraries main page. If you still can't find the article after doing this, contact a librarian or you can request it from our free i nterlibrary loan and document delivery service .
by Dr. Jo Koster, Winthrop University
Humanities scholars and students aren’t usually taught to write abstracts like our friends in the natural and social sciences are. That’s because in the humanities, full pieces of discourse are preferred to short, condensed summaries. But in many cases you will NEED to write an abstract for your work—and a lot of what your colleagues in other disciplines know can help you.
Let’s start with the basic questions.
A descriptive abstract is the summary of work you have already completed or work you are proposing. It is not the same thing as the introduction to your work. The abstract should give readers a short, concise snapshot of the work as a whole—not just how it starts. Remember that the readers of your abstract will sometimes not read the paper as a whole, so in this short document you need to give them an overall picture of your work. If you are writing an abstract as a proposal for your research—in other words, as a request for permission to write a paper—the abstract serves to predict the kind of paper you hope to write.
A conference abstract is one you submit to have your paper considered for presentation at a professional conference (CURAH maintains a growing list of these opportunities ). The conference organizers will specify the length — rarely be more than 500 words (just short of two double-spaced pages). In an ideal world, you write your abstract after the actual paper is completed, but in some cases you may write an abstract for a paper you haven’t yet written—especially if the conference is some time away. Because the conference review committee will usually read the abstract and not your actual paper, you need to think of it as an independent document, aimed at that specific committee and connecting solidly with the theme of the conference. You may want to pick up phrasing from the conference title or call for papers in the abstract to reinforce this connection. Examine the call for papers carefully; it will specify the length of the abstract, special formatting requirements, whether the abstract will be published in the conference bulletin or proceedings, etc. Abstracts that do not meet the specified format are usually rejected early in the proceedings, so pay attention to each conference’s rules!
An abstract is a promissory note. That is, you are promising that you can and will produce the goods in the paper. Particularly in the case of a conference abstract, the organizers will make up a session based on the contents of the abstract. If you propose a paper that says you will use Foucault to comment on post-colonialism in Heat and Dust” and then show up with a paper on “Metaphors for Spring in A Bend in the River,” your paper may not fit the session where it was slotted, and you’ll look silly—and those organizers may not ask you back. While some divergence from the promised topic is acceptable (and probably inevitable if you haven’t written the paper when you submit the abstract), you need to produce a paper that’s within shouting distance of your original topic for the sake of keeping your promise.
Descriptive abstracts are usually only 100-250 words, so they must be pared down to the essentials. Typically, a descriptive abstract answers these questions:
Why did you choose this study or project? What did/will you do and how? What did you/do you hope to find? (For a completed work) What do your findings mean?
Which paper would you rather go hear at a conference? ‘Issues of Heteronormativity and Gender Performance In Twain’s Novels” or “Come Back to the Raft, Huck Honey”?
Your title should be informative and focused, indicating the problem and your general approach. It’s very fashionable in the humanities to have titles featuring a catchy phrase, a colon, and then an explanation of the title. While snappy titles may help your abstract be noticed, it’s really what comes after the colon that sells the abstract, so pay attention to it. “All the World’s a Ship: Race and Ethnicity in Moby Dick” catches the eye, but “Melville’s Deconstruction of Ethnicity in the ‘Midnight, Forecastle’ Episode of Moby Dick” tells readers much more specifically what you’re promising to deliver.
The abstract should begin with a clear sense of the research question you have framed. Often writers set this up as a problem: “Although some recent scholars claim to have identified Shakespeare’s lost play Cardenio, that attribution is still not accepted.
If you began with a problem, you can pose your argument as the solution: “In this paper I use the records of the Worshipful Company of Stationers, London’s chief publishing organization, to show that the play identified by Charles Hamilton in 1990 is not actually the play Shakespeare’s company mounted in 1613.” It’s perfectly legit to use “I” in sentences referring to your argument.
It always helps when you identify the theoretical or methodological school that you are using to approach your question or position yourself within an ongoing debate. This helps readers situate your ideas in the larger conversations of your discipline. For instance, “The debate among Folsom, McGann, and Stallybrass over the notion of database as a genre (PMLA 122.5, Fall 2007) suggests that….” or “Using the definition of dataclouds proposed by Johnson-Eilola (2005), I will argue that…”
“ Through analyzing Dickinson’s use of metaphor, I demonstrate that she systematically transformed Watt’s hymnal tropes as a way of asserting her own doctrinal truths. This transformation…”
Not everyone agrees how much jargon should be included in an abstract. My best advice is to add any technical terms you need, but don’t put in jargon for jargon’s sake or just to make it look like you are an expert (this especially extends to (post)modernizing your words or other typographical excrescences).
To the basic requirements of the descriptive abstract, a conference paper abstract should also include a few sentences about how the proposed paper fits in the theme of the conference. For instance, a call for papers for a session on “Science and Literature in the 19th Century” at a conference entitled “(Dis)Junctions” requested “critical works on the interaction between scientific writing and literature in the 19th century. How did scientific discoveries, theories and assumptions (for example, in medicine and psychology, but not limited to these) influence contemporaneous fiction?” If you were submitting a paper to this session, you would want to have a sentence or two about the theories you were discussing and name the particular works where you would identify their influence. If you can work the words “join” or “junction” (or “disjunction”) into your title or abstract, you’ll increase your chance of having the paper accepted, since you’re showing clearly how the paper fits the theme of the session.
Tell them your essay is a finished work (even if it’s only complete in your head!). It’s also considered good in a conference abstract to conclude with a sentence about your presentation, since the great horror of session chairs is the paper that runs far too long (or embarrassingly too short). Organizers also need to know if you need any special technology to present the paper. So a a much-appreciated professional touch is concluding passage such as, “My paper is complete and can be presented in 20 minutes. I will bring bring video clips on a portable drive but will need a computer, projector, and Internet access to show all my materials.”
Double-check your abstract to make sure it meets the length requirements. Make sure it’s edited and documented. And above all, make sure it’s submitted on time.
Here is a video version of this page, taking you from the call for papers to the finished abstract.
Check out these other guides from CURAH:
Illustrated by Ian MacInnes Thanks to Dr. Leslie Bickford for her sample abstract
I consulted and borrowed material from the following websites in preparing these suggestions:
www.unc.edu/depts/wcweb/handouts/abstracts.html www.linguistics.ucsb.edu/faculty/bucholtz/sociocultural/abstracttips.html www.academic-conferences.org/abstract-guidelines.htm ceca.icom.museum/ dbase upl/writinganabstract.pdf ling.wisc.edu/macaulay/800.abstracts.html writingcenter.unlv.edu/writing/abstract.html www.lightbluetouchpaper.org/2007/03/14/how-not-to-write-an-abstract/ webapp.comcol.umass.edu/msc/absGuidelines.aspx www.oberlin.edu/history/Honors/prospectus.html www.english.eku.edu/ma/scholarlythesis.php
A proposal paper sets out your reasoning for the study, justifies the research and explains your intended methods. Dissertations and other graduate-level research often require proposals, or you may create one to apply for grant money. An abstract summarizes the information in the proposal. An effective abstract can make the difference between a positive or negative response to the proposal.
A strong abstract touches on all the sections in the proposal, including the introduction, where you should give some information about the issue and why you chose it. While you do not want to go into detail about the problem, you need to state what issue your project will address, such as the high dropout rate for sophomores at a college. If you find you cannot focus your abstract on a single problem, your research may be too broad.
A proposal identifies a reason for the project, so the abstract also needs to establish how this project fulfills a need. You may indicate how your plan differs from previous research or fills a void in past research while summarizing information included in the literature review portion of your paper. Include a brief explanation of the project's objectives, the research or other material you will rely on in the paper and in your proposed thesis.
The abstract should include some general information about the procedures for your project. Explain if you will use qualitative, quantitative or mixed measures and why. What type of sample and procedures will you use to obtain your data? Add a sentence at the end of the abstract to indicate the conclusion you expect to draw from the project and the implications of the results, which will create a sense of closure for the document. Remember, the abstract is a summary of material in the paper, so only include information in the abstract that will also appear in the actual paper.
First person point of view -- "I" and "my" -- are usually acceptable in APA proposals, but you should double check your field's style guide. After finishing a draft, revise your abstract to create concise language, keeping the abstract to a maximum of 250 words. Find examples of acceptable abstracts from your field and institution to use as models. If you write the abstract before finishing the proposal, review it once you have completed the paper to make sure the abstract summarizes the ideas you have presented. Insert a page break after the title page and place the abstract there, including the running head and page number in the header.
Kristie Sweet has been writing professionally since 1982, most recently publishing for various websites on topics like health and wellness, and education. She holds a Master of Arts in English from the University of Northern Colorado.
Reprocessing used nuclear fuel (UNF) is crucial to the completion of a closed fuel cycle and would reduce the volume of waste produced during nuclear power production. Pyroprocessing is a promising reprocessing technique as it offers pure forms of product recovery. A limiting issue with pyroprocessing, however, is the inability to monitor concentrations of chemical species inside the electrorefiner. As with many nuclear processes, safe guards and monitoring become increasingly important; therefore, development of real - time monitoring techniques for various chemical species may allow for commercialization of this recycling process [1 - 5]. The focus of the proposed research is to develop accurate diffusion coefficients for Yttrium, a fission product found in UNF, in molten salt conditions through Cyclic Voltammetry (CV). Quantification of the diffusion coefficient will allow current measurements from inside the melt to be directly related to species concentration. With the diffusion coefficients, in - situ CV would then facilitate real - time monitoring of chemical concentrations.
This project aims to analyze the social and cultural effects of the Iranian Revolution through primary source material and interviews with those directly affected by the revolution. Iran’s political seclusion and its animosity toward the West has limited the voices and perspectives available to an American audience. Moreover, the attitude of the West towards Iran since the revolution has been myopic and often marred by political perspectives. The objective of this project will be to bring those voices and stories to light, putting a greater focus on the experiences of individuals who lived through the Revolution. These stories will be presented in a digital medium (film and web) in order to bring these voices and perspectives to an American audience.
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The association of gut microbial features with type 2 diabetes (T2D) has been inconsistent due in part to the complexity of this disease and variation in study design. Even in cases in which individual microbial species have been associated with T2D, mechanisms have been unable to be attributed to these associations based on specific microbial strains. We conducted a comprehensive study of the T2D microbiome, analyzing 8,117 shotgun metagenomes from 10 cohorts of individuals with T2D, prediabetes, and normoglycemic status in the United States, Europe, Israel and China. Dysbiosis in 19 phylogenetically diverse species was associated with T2D (false discovery rate < 0.10), for example, enriched Clostridium bolteae and depleted Butyrivibrio crossotus . These microorganisms also contributed to community-level functional changes potentially underlying T2D pathogenesis, for example, perturbations in glucose metabolism. Our study identifies within-species phylogenetic diversity for strains of 27 species that explain inter-individual differences in T2D risk, such as Eubacterium rectale . In some cases, these were explained by strain-specific gene carriage, including loci involved in various mechanisms of horizontal gene transfer and novel biological processes underlying metabolic risk, for example, quorum sensing. In summary, our study provides robust cross-cohort microbial signatures in a strain-resolved manner and offers new mechanistic insights into T2D.
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Data availability.
The individual-level raw shotgun sequencing data and metadata have been deposited in the European Nucleotide Archive with accession codes PRJEB37249 , PRJEB38742 , PRJEB41311 and PRJEB46098 for the Fromentin_2022 dataset (MetaCardis); the Sequence Read Archive (SRA) under accession code ERP002469 for the Karlsson_2013 dataset; the NCBI SRA under accession numbers SRA045646 and SRA050230 for the Qin_2012 dataset (Shenzhen cohort); the China NGDC Genome Sequence Archive: HRA000020 or EGA: EGAS00001004480 for the Wu_2020 dataset; and the China Nucleotide Sequence Archive (CNSA) with the dataset identifier CNP0000175 for the Zhong_2019 dataset (Suzhou cohort). The shotgun metagenomic sequencing data from the Nurses’ Health Study II (NHSII) and Health Professionals Follow-up Study (HPFS) are publicly available at the BIOM-Mass Data Portal ( https://biom-mass.org/ ; project names: HPFS and MBS). Due to the gaining of informed consent from the participants, all of the individual-level phenotype data from NHSII and HPFS are available via a request for external collaboration and upon approval of a letter of intent and a research proposal. Details on how to request external collaboration with NHSII and HPFS can be found at https://nurseshealthstudy.org/researchers (contact principal investigator: A. H. Eliassen, email: [email protected]) and https://sites.sph.harvard.edu/hpfs/for-collaborators/ (contact principal investigator L. Mucci, email: [email protected]). The individual-level metadata in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) are archived at the National Institutes of Health repositories dbGap (study accession: phs000810.v2.p2 ) and BIOLINCC (accession number: HLB01141423a). Shotgun metagenomic sequencing data from the HCHS/SOL samples described in this study are deposited in QIITA (study ID: 11666). HCHS/SOL has established a process for the scientific community to apply for access to participant data and materials, with such requests reviewed by the project’s Steering Committee. These policies are described at https://sites.cscc.unc.edu/hchs/ (contact HCHS/SOL at [email protected]). The DIRECT-PLUS Study recruited participants in Israel and was designed as a clinical trial. That study used only baseline, pre-randomization data from the DIRECT-PLUS Study for an observational analysis. Due to gaining of informed consent from the participants, the individual-level de-identified metadata and metagenomic sequencing data in the DIRECT-PLUS Study will be available for general research purposes through a request to I. Shai (email: [email protected]) and D. D. Wang (email: [email protected]) after publication. All of the source data for creating figures and extended data figures are available as supplementary information. Source data are provided with this paper.
This study mainly relies on open-source bioinformatic tools described in detail in Methods . The analysis-specific programs are publicly available through https://github.com/DW-Group/T2D_Microbiome_Meta-analysis .
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The authors thank K. Dennis for coordinating the collection and transfer of the data, and F. Bäckhed, K. Kristiansen, J. Li, H. Zhong and J. Qin for sharing their data and helping with the data transfer. The authors are indebted to the participants in the Health Professionals Follow-up Study (HPFS) and Nurses’ Health Study II (NHSII) for their continuing outstanding level of cooperation, and to the staff of the HPFS and NHSII for their valuable contributions. The authors also thank the staff and participants of the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) for their important contributions; the DIRECT-PLUS Study participants for their valuable contributions; and A. Yaskolka-Meir, G. Tsaban, A. Kaplan, H. Zelica, I. Youngster, K. Tuohy and O. Koren for their contribution to the DIRECT-PLUS Study. This work is funded by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK; R00 DK119412 and Boston Nutrition Obesity Research Center Pilot and Feasibility Program grant supported by P30 DK046200 to D.D.W.; R24 DK110499 to C.H.), National Institute of Nursing Research (R01 NR01999 to D.D.W.), National Institute on Aging (R01 AG077489 and RF1 AG083764 to D.D.W.) and National Cancer Institute (NCI; R35 CA253185 to A.T.C.). A.T.C. is an American Cancer Society Research Professor. F.W. is supported by the American Heart Association Postdoctoral Fellowship (Grant number: 897161 to F.W.). The HPFS is supported by research grants U01 CA167552 (to W.C.W.) and R01 HL035464 (to E.B.R.) from the National Institutes of Health (NIH). The Men’s Lifestyle Validation Study in HPFS was supported by U01 CA152904 (to M.J.S. and E.B.R.) from NCI. The fecal sample collection and metagenomic data sequencing in HPFS were supported by the STARR Cancer Consortium Award (I7-A714 to C.H.). NHSII was supported by U01 CA176726 from NIH and P01 CA055075 (to W.C.W.) from NCI. The fecal sample collection and metagenomic data sequencing in NHSII were supported by the R01 CA202704 (to A.T.C. and C.H.) from NCI. The HCHS/SOL is a collaborative study supported by contracts from the National Heart, Lung and Blood Institute (NHLBI) to the University of North Carolina (HHSN268201300001I/N01-HC-65233), University of Miami (HHSN268201300004I/N01-HC-65234), Albert Einstein College of Medicine (HHSN268201300002I/N01-HC-65235), University of Illinois at Chicago (HHSN268201300003I/N01-HC-65236 Northwestern University) and San Diego State University (HHSN268201300005I/N01-HC-65237). The following institutes, centers and/or offices have contributed to the HCHS/SOL through a transfer of funds to the NHLBI: National Institute on Minority Health and Health Disparities (NIMHD), National Institute on Deafness and Other Communication Disorders, National Institute of Dental and Craniofacial Research, NIDDK, National Institute of Neurological Disorders and Stroke, and NIH Institution-Office of Dietary Supplements. Additional funding for the ‘Gut Origins of Latino Diabetes’ ancillary study to HCHS/SOL was provided by R01 MD011389 (to R.C.K., R.D.B. and R.K.) from the NIMHD and the Life Course Methodology Core at Albert Einstein College of Medicine and the New York Regional Center for Diabetes Translation Research (P30 DK111022-8786 and P30 DK111022) through funds from NIDDK. Additional funding for this work was provided by R01 HL060712 (to F.B.H. and Q.Q.) from NHLBI. The DIRECT-PLUS Study was funded by grants from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) Collaborative Research Center SFB1052 ‘Obesity Mechanisms’ (SFB-1052/B11 to I.S.); Israel Ministry of Health grant 87472511 (to I.S.); Israel Ministry of Science and Technology grant 3-13604 (to I.S.); California Walnuts Commission (to I.S.) and the CABALA_DIET&HEALTH Project, which received funding from the European Union’s Horizon 2020 Programme. The funding source had no role in the design and conduct of the study; collection, management, analysis and interpretation of the data; preparation, review, or approval of the manuscript; and the decision to submit the manuscript for publication. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. The computations in this paper were run in part on the FASRC Cannon cluster supported by the FAS Division of Science Research Computing Group at Harvard University.
These authors contributed equally: Zhendong Mei, Fenglei Wang.
Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
Zhendong Mei, Danyue Dong, Yuxi Liu, Eric B. Rimm, Walter C. Willett, Frank B. Hu, Meir J. Stampfer & Dong D. Wang
Broad Institute of MIT and Harvard, Cambridge, MA, USA
Zhendong Mei, Fenglei Wang, Amrisha Bhosle, Danyue Dong, Raaj Mehta, Andrew Ghazi, Yancong Zhang, Yuxi Liu, Andrew T. Chan, Curtis Huttenhower & Dong D. Wang
Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
Fenglei Wang, Eric B. Rimm, Walter C. Willett, Frank B. Hu, Qibin Qi, Meir J. Stampfer, Iris Shai & Dong D. Wang
Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
Amrisha Bhosle, Andrew Ghazi, Yancong Zhang & Curtis Huttenhower
Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
Raaj Mehta & Andrew T. Chan
Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
Department of Chemistry and Chemical Biology, Harvard University, Cambridge, MA, USA
Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
Yuxi Liu, Eric B. Rimm, Walter C. Willett, Frank B. Hu & Meir J. Stampfer
Department of Medicine, Hebrew University and Hadassah Medical Center, Jerusalem, Israel
Ehud Rinott
Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
Institute for Minority Health Research, University of Illinois Chicago, Chicago, IL, USA
Martha Daviglus
Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, CA, USA
Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, CA, USA
Department of Computer Science and Engineering, University of California San Diego, La Jolla, CA, USA
Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
Qibin Qi, Robert D. Burk & Robert C. Kaplan
Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY, USA
Robert D. Burk
Department of Microbiology and Immunology, Albert Einstein College of Medicine, Bronx, NY, USA
Department of Obstetrics, Gynecology and Women’s Health, Albert Einstein College of Medicine, Bronx, NY, USA
Faculty of Health Sciences, The Health and Nutrition Innovative International Research Center, Ben-Gurion University of the Negev, Be′er Sheva, Israel
Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
Robert C. Kaplan
Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA
Curtis Huttenhower
Harvard Chan Microbiome in Public Health Center, Harvard T.H. Chan School of Public Health, Boston, MA, USA
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Z.M., F.W., C.H. and D.D.W. conceptualized the study. Z.M. and F.W. performed the data analysis. Z.M., F.W., C.H. and D.D.W. drafted the paper. C.H. and D.D.W. supervised the study. E.B.R, M.D., W.C.W., R.K., F.B.H., Q.Q., A.T.C., R.D.B., M.J.S., E.R., I.S., R.C.K., C.H. and D.D.W. collected the sample and data, and obtained funding. Z.M., F.W., A.B., D.D., R.M., A.G., Y.Z., Y.L., E.R., S.M., E.B.R., M.D., W.C.W., R.K., F.B.H., Q.Q., A.T.C., R.D.B., M.J.S., I.S., R.C.K., C.H., and D.D.W. discussed the results, critically reviewed the text and approved the final paper.
Correspondence to Curtis Huttenhower or Dong D. Wang .
Competing interests.
C.H. is a member of the scientific advisory board for Zoe Nutrition, Empress Therapeutics, and Seres Therapeutics. All other authors have no competing interests.
Peer review information.
Nature Medicine thanks the anonymous reviewers for their contribution to the peer review of this work. Primary Handling Editor: Sonia Muliyil, in collaboration with the Nature Medicine team.
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Extended data fig. 1 workflow..
We adjusted for the study effect by adopting a conservative meta-analysis approach in the downstream analyses. Our analyses examined the overall microbial community structure, specific microbial taxonomic and functional features, strain-specific biochemical pathways, and within-species phylogeny and gene families in a cross-cohort meta-analysis framework. This figure was created with BioRender.com .
R 2 values are calculated from permutational multivariate analysis of variance (PERMANOVA, n = 999 permutations) and indicate the variance attributable to study and batch effects.
Extended data fig. 3 comparisons in associations between microbial species and type 2 diabetes across different statistical models..
Meta-analyzed associations of individual microbial species with type 2 diabetes (T2D) phenotype from the ordinal ( a ) and binary ( b ) models. The ordinal model modeled the disease status as an ordinal variable (T2D, prediabetes, or controls) and used data from all the participants. The binary model modeled the disease status as a binary variable (T2D or controls) and used data from T2D patients and normoglycemic controls. The blue-to-red and purple-to-orange gradients represent the magnitude and direction of the associations as quantified by meta-analyzed beta coefficients from linear mixed models adjusted for age, sex, and body mass index (BMI) and further adjusted for metformin use in MaAsLin2. All the results were corrected for multiple hypothesis testing by controlling the false discovery rate (FDR) using the Benjamini–Hochberg method with a target rate of 0.10. All models included each participant’s identifier as random effects and simultaneously adjusted for covariables. ( c ) Comparisons in associations between microbial species and T2D between multivariate MaAsLin2 models with and without further adjustment for BMI and metformin use from the ordinal model. ( d ) Comparisons in associations between microbial species and T2D between multivariate MaAsLin2 models with and without further adjustment for BMI and metformin use from the binary model. Dots in the scatter plots in (c) and (d) represent meta-analyzed beta coefficients from linear mixed models adjusted for covariables in MaAsLin2. All the statistical tests were two-sided. A total of 8,117 metagenomes from 1,851 T2D patients, 2,770 individuals with prediabetes, and 2,277 normoglycemic controls were included in the analyses in (a), (b), (c), and (d). Abbreviations: BMI, body mass index; Con, control; metf, metformin use; insul, insulin use; T2D, type 2 diabetes.
( a ) Distance-based redundancy analysis (dbRDA) based on species-level Bray–Curtis dissimilarity colored by type 2 diabetes (T2D) and metformin use. The centers of the boxplot show medians with boxes indicating their inter-quartile ranges (IQRs) and upper and lower whiskers indicating 1.5 times the IQR from above the upper quartile and below the lower quartile, respectively. ( b ) Meta-analyzed and cohort-specific associations of microbial species with metformin use among T2D patients. We defined microbial signatures of metformin as those significantly associated with metformin use in T2D cases only but not associated with T2D after further adjusting for metformin use in all participants. We also identified 4 species associated with both metformin use and T2D. The centers of the error bars represent the β coefficients of the associations, and the error bars represent their standard errors (SEs). ( c ) Our modeling approach effectively accounted for the potential confounding effect of metformin use, as evidenced by the high correlation between the beta coefficients of species–T2D associations obtained in the primary analysis and those calculated in a sensitivity analysis excluding T2D patients treated with metformin. The beta coefficients in (b) and (c) represent the associations quantified by linear mixed models, adjusting for age, sex, body mass index (BMI), and metformin use where appropriate, in MaAsLin2. All the results were corrected for multiple hypothesis testing by controlling the false discovery rate (FDR) using the Benjamini–Hochberg method with a target rate of 0.10. All the analyses in (a), (b), and (c) were based on 5,114 metagenomes from 1,851 T2D patients and 2,277 normoglycemic controls. The statistical tests in (a) and (b) were two-sided. Abbreviations: Con, control; metf, metformin use; T2D, type 2 diabetes.
( a ) Comparisons in associations between microbial species and T2D in one analysis that includes all study participants and the other that excludes individuals with prevalent T2D in the Hispanic Community Health Study/Study of Latinos. ( b ) Comparisons in associations between microbial species and T2D in one analysis that includes all study participants and the other analysis that excludes insulin-treated T2D patients. The dots represent the associations quantified by linear mixed models, adjusting for age, sex, body mass index, and metformin use in MaAsLin2. Abbreviation: T2D, type 2 diabetes.
( a ) Meta-analyzed associations of individual MetaCyc pathways with circulating biomarkers of metabolic risk. ( b ) Meta-analyzed associations of individual microbial enzymes with circulating biomarkers of metabolic risk. Only pathways and enzymes listed in Fig. 3 were analyzed and presented in this figure. The blue-to-red gradients represent the magnitude and direction of the associations as quantified by meta-analyzed beta coefficients from linear mixed models adjusted for age, sex, body mass index, and metformin use in MaAsLin2. All the results were corrected for multiple hypothesis testing by controlling the false discovery rate (FDR) using the Benjamini–Hochberg method with a target rate of 0.10. Abbreviations: BMI, body mass index; HbA1c, hemoglobin A1c; HDL-C, high-density lipoprotein cholesterol; hs-CRP, high-sensitivity C-reactive protein; HOMA-B, homeostasis model assessment of β-cell function; HOMA-IR, homeostasis model assessment of insulin resistance; LDL-C, low-density lipoprotein cholesterol; TG, triglyceride.
( a ) Distribution of different P. copri subclades across geographic regions and studies. We applied MetaPhlAn taxonomic profiling based on P. copri subclade-specific marker genes to detect the presence of a subclade in metagenomes. ( b ) Comparisons in adjusted relative abundance of branched-chain amino acid (BCAA) biosynthesis pathways and enzyme encoded by P. copri subclades dominated by clade A versus other clades. The adjusted relative abundance of pathways and enzymes is estimated by anpan (ANalysis of microbial Phylogenies And geNes)’s pathway random effects models ( Methods ) with simultaneous adjustment for the abundance of P. copri subclades. The centers of the boxplot show medians of adjusted relative abundance with boxes indicating their inter-quartile ranges (IQRs) and upper and lower whiskers indicating 1.5 times the IQR from above the upper quartile and below the lower quartile, respectively. P -values were generated from two-sided t-tests based on the adjusted relative abundance. ( c ) Clade A-dominant P. copri strains in type 2 diabetes (T2D) patients were more likely to retain pathways and enzymes of branched-chain amino acid biosynthesis compared to clade A-dominant nonT2D controls. The blue and red lines, fitted by linear regression in participants with T2D and control participants separately, represent the associations between the log-transformed relative abundance of P. copri subclade and the log-transformed relative abundance of a given pathway or enzyme encoded by P. copri . The numeric values in the top left corner are posterior differences and 98% posterior intervals of differences in log-transformed pathway abundance between case–control status, as determined by mixed effects models anpan ( Methods ). This model allows us to identify microbial functions encoded by a P. copri subclade that are differentially abundant between T2D cases versus controls while controlling for its subclade-level abundance. All the analyses in (a), (b), and (c) were based on 5,114 metagenomes from 1,851 T2D patients and 2,277 normoglycemic controls.
The annotation bars represent metformin use (metf), study, body mass index (BMI), sex, age, and type 2 diabetes (T2D) status, respectively. The boxplots in the bottom represent the posterior mean of the phylogenetic effect of each phylogenetic tree leaf (metagenome) estimated by the phylogenetic generalized linear mixed models (PGLMMs) in anpan (ANalysis of microbial Phylogenies And geNes, see Methods ) with whiskers representing the 95% credible intervals of the posterior means. By applying PGLMMs, we compared two generalized linear mixed models with and without incorporating within-species phylogeny as a random effect ( Methods ). Both models were adjusted for age, sex, body mass index, metformin use, and study membership as fixed effects. We generated within-species phylogenetic trees by randomly splitting the edges based on the Euclidean similarity matrix derived from clustered sets of protein sequences (UniRef90 gene families) after dimension reduction by principal components analysis.
The line plots show the running enrichment score for the gene ontology (GO) term as the analysis ‘walks down’ the ranked list. The vertical black lines on the X-axis show where members of the GO term appear in the ranked list of UniRef90 gene families.
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Mei, Z., Wang, F., Bhosle, A. et al. Strain-specific gut microbial signatures in type 2 diabetes identified in a cross-cohort analysis of 8,117 metagenomes. Nat Med (2024). https://doi.org/10.1038/s41591-024-03067-7
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Unlocking the chemical environment of nitrogen in perovskite-type oxides †.
* Corresponding authors
a Institute of Multidisciplinary Research for Advanced Materials, Tohoku University, 2-1-1 Katahira, Aoba-ku, Sendai, Miyagi, Japan E-mail: [email protected] , [email protected]
b Advanced Institute for Materials Research (WPI-AIMR), Tohoku University, 2-1-1 Katahira, Aoba-ku, Sendai, Miyagi, Japan
c School of Environmental Science and Engineering, State Key Laboratory of Metal Matrix Composites, Shanghai Jiao Tong University, Shanghai, P. R. China
d Kyushu Synchrotron Light Research Center, 8-7 Yayoigaoka, Tosu, Saga, Japan
Nitrogen (N) doping of perovskite-type oxides is an effective method for enhancing their photocatalytic performance. Quantitative and qualitative analyses of the doped N species are essential for a deeper understanding of the catalytic activity enhancement mechanism. However, examining the N environment in perovskite-type oxides, particularly in the bulk, using conventional analytical techniques, such as X-ray photoelectron spectroscopy (XPS), is challenging. In this study, we propose a new analytical technique, advanced temperature-programmed desorption (TPD) up to 1600 °C, to complement the conventional methods. TPD can quantify all N species in bulk oxides. Moreover, it facilitates chemical speciation of N environments, such as substitutional and interstitial N species. This is verified by XPS, CHN elemental analysis, X-ray absorption spectroscopy, and in situ diffuse reflectance infrared Fourier-transform spectroscopy. This study demonstrates the feasibility of advanced TPD as a new analytical method that offers comprehensive information on the N species within N-doped oxide materials at the bulk level.
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S. Shimizu, T. Yoshii, G. Nishikawa, J. Wang, S. Yin, E. Kobayashi and H. Nishihara, Chem. Sci. , 2024, Advance Article , DOI: 10.1039/D4SC01850H
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HIV virus = Human Immunodeficiency Virus; AIDS syndrome = Acquired Immunodeficiency Syndrome. 2. Avoid Useless and Emotional Intensifiers. Really, very, quite, extremely, severely, clearly, certainly, essentially, actually: The preliminary results clearly show that the protein was absent in the fraction.
Abstracts provide a summary and preview of an academic work, such an article, research proposal, or conference presentation. Abstracts are the first part of an article that readers will see: They set expectations and help readers understand what will come next. All abstracts used in this handout are from published articles from biology ...
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Example 1. Reprocessing used nuclear fuel (UNF) is crucial to the completion of a closed fuel cycle and would reduce the volume of waste produced during nuclear power production. Pyroprocessing is a promising reprocessing technique as it offers pure forms of product recovery. A limiting issue with pyroprocessing, however, is the inability to ...
than 10,000 people and a nationally representative sample of CWSs and NTNCWSs serving 10,000 or fewer people. UCMR 5, published in 2021, includes samplingfor 29 PFAS (including the six PFAS required ... and the USDA Agricultural Research Service's Sustaining The Earth's Watersheds—Agricultural Research Database System (STEWARDS) (https ...
The sample processing and shotgun metagenomic sequencing were performed at Alkek Center for Metagenomics and Microbiome Research, Baylor College of Medicine, Houston, TX, United States.
a Institute of Multidisciplinary Research for Advanced Materials, Tohoku University, 2-1-1 Katahira, Aoba-ku, Sendai, Miyagi, Japan ... Abstract. Nitrogen (N) doping of perovskite-type oxides is an effective method for enhancing their photocatalytic performance. Quantitative and qualitative analyses of the doped N species are essential for a ...
Research Note Framing disinformation through legislation: Evidence from policy proposals in Brazil This article analyzes 62 bills introduced in the Brazilian Chamber of Deputies between 2019-2022 to understand how legislators frame disinformation into different problems and their respective solutions.