Impactful in disease research: a DMM year in review.
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ABSTRACT:
SUBMITTER: Hackett R
PROVIDER: S-EPMC9922873 | biostudies-literature | 2023 Jan
REPOSITORIES: biostudies-literature
Publications
Impactful in disease research: a DMM year in review.
Hackett Rachel R Patton E Elizabeth EE
Disease models & mechanisms 20230131 1
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Project description:BackgroundSince 2015, the American Delirium Society (ADS) Research Committee has conducted an annual survey of the delirium literature for presentation in its year-in-review session. Our objectives were to describe the review process used for the 2021-2022 and to summarise the selected publications.MethodsEach member of the ADS Research Committee nominated up to 6 publications considered to be the most impactful primary delirium research published from September 1, 2021, to July 31, 2022. The 24 nominated studies were divided into three categories balanced by number of articles: medical intervention trials, non-medical intervention trials, and delirium detection/basic science studies. Each ADS Research Committee member ranked all studies in their assigned category for methodological rigor and for impact, each being scored as 0-10, for a total score of 0-20. It was decided a priori to select the top three highest-scoring articles in each category for presentation, with ties adjudicated by Committee consensus.ResultsNineteen Research Committee members served as reviewers. Scores for each category were similar: medical interventions mean (standard deviation) 12.8 (1.1), non-medical interventions 13.1 (1.1), and detection/basic science 12.6 (1.0). We summarise the results of the papers presented in the 2022 ADS year-in-review session.ConclusionThe diversity of studies presented for the 2022 ADS year-in-review session illustrates the breadth of the delirium field and the growing number of clinical trials. The dissemination of publications across a broad, diverse array of journals provides further justification of the need for delirium-specific journals.
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Project description:The One Health concept has inspired a rich vein of applied research and scholarly reflection over the past decade, yet with little influence from qualitative methodologists. With this overview, we describe the underpinning assumptions, purposes, and potential pitfalls of data collection techniques and methods of data analysis in key qualitative research methodologies. Our aim is to enhance One Health collaborations involving qualitative researchers, veterinary epidemiologists, and veterinary economists. There exist several distinct traditions of qualitative research, from which we draw selectively for illustrative purposes. Notwithstanding important distinctions, we emphasize commonalities and the potential for collaborative impact. The most important commonality is a shared focus on contextualizing human behavior and experience-culturally, economically, historically, and socially. We demonstrate that in-depth attention to context can assist veterinary economists and epidemiologists in drawing lessons from the implementation of policies and programs. In other words, qualitative researchers can assist One Health teams in distilling insights from "success stories," but also from adverse events and unintended consequences. As a result, qualitative researchers can contribute to One Health research and policy discussions by formulating more accurate and contextually-relevant parameters for future quantitative studies. When performed well, qualitative methodologies can help veterinary economists and epidemiologists to develop impactful research questions, to create more accurate and contextually-relevant parameters for quantitative studies, and to develop policy recommendations and interventions that are attuned to the political and socio-cultural context of their implementation. In sketching out the properties and features of influential methodologies, we underscore the value of working with seasoned qualitative researchers to incorporate questions about "what," "how," and "why" in mixed-methods research designs.
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Project description:BackgroundAlthough publications have been increasing rapidly, the research quality has yet to improve in the field of critical care medicine (CCM) in China. This study aimed at investigating the current status of and the influential factors for impactful publications in CCM research by Chinese authors.MethodsPublications by authors with the affiliation of critical care medicine department or intensive care unit (CCM/ICU) in Chinese as well as American hospitals from 2001 to 2020 were retrieved from the Web of Science Core Collection (WoSCC) database for this bibliometric analysis. Moreover, statistical analyses to test factors affecting impactful publications by Chinese authors were performed.ResultsOf 13,487 articles retrieved by this search strategy, 6,622 were published by Chinese authors as first or corresponding authors. The annual publications by Chinese authors have been rapidly increasing from 2001 to 2020, and so did the citations to these articles. However, the proportion in the world of publications by Chinese authors was much less than that by American authors each year [M (IQR): 1.85 (9.592) vs. 27.77 (7.3), p < 0.001]. In addition, impactful articles were significantly less published by Chinese than by American authors, including articles either in journals with a high impact factor (p < 0.001) or in the top 10 journals in the field of CCM (5.4 vs 13.4%, p < 0.001), and articles with high citation frequency as well (p < 0.001). Moreover, the percentage of impactful publications by Chinese authors was likely associated with academic background and regions of the author's affiliations, funds support, public health events of COVID-19, and collaboration between authors.ConclusionOur results demonstrated that CCM research in China grew rapidly in the recent 20 years. However, the impactful publications remained limited, largely owing to the shortage of comprehensive research training, inactive collaboration, and underfunded CCM research.
| S-EPMC9622943 | biostudies-literature
Project description:Artificial Intelligence (AI) has become a disruptive technology, promising to grant a significant economic and strategic advantage to nations that harness its power. China, with its recent push towards AI adoption, is challenging the U.S.'s position as the global leader in this field. Given AI's massive potential, as well as the fierce geopolitical tensions between China and the U.S., several recent policies have been put in place to discourage AI scientists from migrating to, or collaborating with, the other nation. Nevertheless, the extent of talent migration and cross-border collaboration are not fully understood. Here, we analyze a dataset of over 350,000 AI scientists and 5,000,000 AI papers. We find that since 2000, China and the U.S. have led the field in terms of impact, novelty, productivity, and workforce. Most AI scientists who move to China come from the U.S., and most who move to the U.S. come from China, highlighting a notable bidirectional talent migration. Moreover, the vast majority of those moving in either direction have Asian ancestry. Upon moving, those scientists continue to collaborate frequently with those in the origin country. Although the number of collaborations between the two countries has increased since the dawn of the millennium, such collaborations continue to be relatively rare. A matching experiment reveals that the two countries have always been more impactful when collaborating than when each works without the other. These findings suggest that instead of suppressing cross-border migration and collaboration between the two nations, the science could benefit from promoting such activities.
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Project description:Our objective in this review was to determine (1) impactful research articles about CRISPR-edited stem cells, (2) factors that affected CRISPR method performance in stem cell, and (3) research design related to CRISPR-edited stem cells. Screening research papers of related topic was carried out by using the Science Citation Index Expanded (SCIE) database of the Clarivate Analytics Web of Science Core Collection updated. We screened impactful CRISPR/Cas9-edited stem cells based on total citation until 2020. The result showed the title "RNA-guided human genome engineering via Cas9" was the highest citation in stem cell research using the CRISPR method with total citation 4789 from Web of Science Core Collection until 2020. It became the most influenced paper because this was the first research using CRISPR method for modifying human cells. On the other hand, cell type, CRISPR/Cas9 delivery, and gene target affected CRISPR/Cas9 performance in stem cells. The more complex the cell structure, the more difficult for CRISPR/Cas9 to mutate the host cells. This problem could be solved by modifying the CRISPR/Cas9 delivery by liposome and SaCas9 modification. Another way was using ribonucleoprotein (RNP) as a delivery method. Then, double gene target was more difficult to execute than single gene target. Although it is difficult, CRISPR/Cas9 had the capability to target any genome region from promoter until intron. Research design used a combination of dry lab and wet lab. The dry lab is usually used for sequence analysis and gRNA design. The wet lab which consisted of in vitro and in vivo was used for gene characterization. In particular, colony selection, DNA analysis, and sequencing were important parts for in vitro research design, while DNA analysis and sequencing were crucial parts for in vivo research design. We hoped these findings could give researchers, investor, and students a guideline to conduct CRISPR-edited stem cells in the future.
| S-EPMC8286559 | biostudies-literature
Project description: Not available
| S-EPMC11393666 | biostudies-literature
Project description:BackgroundThe evaluation of translational health research is important for various reasons such as the research impact assessment, research funding allocation, accountability, and strategic research policy formulation. The purpose of this study was to evaluate the research productivity, strength and diversity of research collaboration networks and impact of research supported by a large biomedical research centre in the United Kingdom (UK).MethodsBibliometric analysis of research publications by translational researchers affiliated with the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC) from April 2012 to March 2017.ResultsAnalysis included 2377 translational research publications that were published during the second 5-year funding period of the NIHR Oxford BRC. Author details were available for 99.75% of the publications with DOIs (2359 of 2365 with DOIs), and the number of authors per publication was median 9 (mean = 18.03, SD = 3.63, maximum = 2467 authors). Author lists also contained many consortia, groups, committees, and teams (n = 165 in total), with 1238 additional contributors, where membership was reported. The BRC co-authorship i.e., research collaboration network for these publications involved 20,229 nodes (authors, of which 1606 nodes had Oxford affiliations), and approximately 4.3 million edges (authorship linkages). Articles with a valid DOIs (2365 of 2377, 99.5%) were collectively cited more than 155,000 times and the average Field Citation Ratio was median 6.75 (geometric mean = 7.12) while the average Relative Citation Ratio was median 1.50 (geometric mean = 1.83) for the analysed publications.ConclusionsThe NIHR Oxford BRC generated substantial translational research publications and facilitated a huge collaborative network of translational researchers working in complex structures and consortia, which shows success across the whole of this BRC funding period. Further research involving continued uptake of unique persistent identifiers and the tracking of other research outputs such as clinical innovations and patents would allow a more detailed understanding of large research enterprises such as NIHR BRCs in the UK.
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Project description:On December 31st 2019, the World Health Organization China Country Office was informed of cases of pneumonia of unknown etiology detected in Wuhan City. The cause of the syndrome was a new type of coronavirus isolated on January 7th 2020 and named Severe Acute Respiratory Syndrome CoronaVirus 2 (SARS-CoV-2). SARS-CoV-2 is the cause of the coronavirus disease 2019 (COVID-19). Since January 2020 an ever increasing number of scientific works related to the new pathogen have appeared in literature. Identifying relevant research outcomes at very early stages is challenging. In this work we use COVID-19 as a use-case for investigating: (1) which tools and frameworks are mostly used for early scholarly communication; (2) to what extent altmetrics can be used to identify potential impactful research in tight (i.e. quasi-zero-day) time-windows. A literature review with rigorous eligibility criteria is performed for gathering a sample composed of scientific papers about SARS-CoV-2/COVID-19 appeared in literature in the tight time-window ranging from January 15th 2020 to February 24th 2020. This sample is used for building a knowledge graph that represents the knowledge about papers and indicators formally. This knowledge graph feeds a data analysis process which is applied for experimenting with altmetrics as impact indicators. We find moderate correlation among traditional citation count, citations on social media, and mentions on news and blogs. Additionally, correlation coefficients are not inflated by indicators associated with zero values, which are quite common at very early stages after an article has been published. This suggests there is a common intended meaning of the citational acts associated with aforementioned indicators. Then, we define a method, i.e. the Comprehensive Impact Score (CIS), that harmonises different indicators for providing a multi-dimensional impact indicator. CIS shows promising results as a tool for selecting relevant papers even in a tight time-window. Our results foster the development of automated frameworks aimed at helping the scientific community in identifying relevant work even in case of limited literature and observation time.
| S-EPMC7779112 | biostudies-literature
Project description:BackgroundTo build a Patient-Powered Research Networks (PPRN) that prioritizes the needs of its members who have inflammatory bowel diseases (IBD), we sought to better understand patients' preferences for what are the essential features that will facilitate and sustain engagement.MethodsWe conducted a two-phase qualitative study. Seven focus groups involving 62 participants with IBD were conducted (phase 1). Focus group results informed the phase 2 cognitive interviews, which included 13 phone interviews. Topics included experiences with IBD and research, PPRN engagement, patient-generated health data, and resources/tools to facilitate self-management. All focus groups and interviews were digitally recorded, transcribed verbatim, and analyzed in ATLAS.ti 7.5. Thematic categories were derived from the data, and codes were grouped into emergent themes and relationships.ResultsFour major themes emerged through inductive coding: (1) the impact of knowing; (2) participation barriers and challenges; (3) engagement and collaboration; and (4) customizable patient portal features/functionalities. Participants were motivated to participate in the PPRN because the knowledge gained from research studies would benefit both society and the individual. Main concerns included credibility of online resources, pharmaceutical industry profiting from their data, data security, and participation expectations. Participants wanted a true and equal partnership in every phase of building a PPRN. Participants felt it was important to have access to personal health records and be able to track health status and symptoms.ConclusionPartnering with participants throughout PPRN development was critical to understanding the needs and preferences of patients with IBDs and for shaping engagement strategies and the portal's design.
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