Biomedical Research Publications Research Articles

The impact of sex/gender-specific funding and editorial policies on biomedical research outcomes: a cross-national analysis (2000–2021)

Reflecting sex and gender characteristics in biomedical research is critical to improving health outcomes and reducing adverse effects from medical treatments. This study investigates the impact of sex/gender-specific funding policies and journal editorial standards on the integration of sex/gender analysis in biomedical research publications. Using data from the United States, Canada, the United Kingdom, and other countries between 2000 and 2021, we assessed how these policies influenced research output in the fields of medicine and life sciences. Our findings show that countries with progressive funding policies and journals promoting sex/gender-based reporting have significantly improved research quality and publication rates. This highlights the importance of coordinated policy efforts and editorial practices in advancing integrated sex/gender research. We recommend continued global efforts from policymakers, funding bodies, and journals to embed sex/gender perspectives in scientific inquiry, ensuring more effective and equitable biomedical advancements.

An analysis of trends in the use of animal and non-animal methods in biomedical research and toxicology publications

IntroductionThere have been relatively few attempts to quantitatively assess if, and in which areas, the use of non-animal methods (NAMs) is increasing in biomedical research and importantly, how this compares to the use of live animals.MethodsWe conducted a bibliometric analysis of the relative publication of papers reporting the use of NAMs-only compared to those reporting the use of animals, even if they also reported the use of NAMs, over the period 2003 to 2022 across seven research areas (breast cancer, lung disease, blood cancer, heart disease, neurodegenerative diseases, diabetes and toxicology) and five regions (USA, China, France, Germany, United Kingdom).ResultsWe found that the relative number of publications of research using NAMs-only has been higher than animal-based research for the last 20 years for all research areas and is growing. Research areas differed in their relative publication of NAMs-only based work, with breast cancer and lung disease having consistently the highest ratio of NAMs-only to animal-based publications and heart disease, diabetes and toxicology showing the greatest change over the time period. A key period of change was 2016–18. By 2022 the UK had the highest NAMs-only to animal-based research ratio than any other country for five of the seven research areas and China the lowest for six, accounting for publication rate. Tissue and in silico-based methods were the most common of all NAMs-only publications; lab-on-a-chip and stem cell models are increasing in their use but at much lower levels and rate of increase.ConclusionWe found that proportionately the reliance on animals in these research areas is decreasing, which will be encouraging to those that support the replacement of animal experiments.

Analysis of biomedical and health research in the Eastern Mediterranean Region.

Several bibliometric analyses have been conducted in the Eastern Mediterranean Region (EMR), however, there is limited data from such analyses for the establishment of national or regional health research agenda. To assess the biomedical and health research outputs in EMR countries for 2004-2018 and their alignment with the regional strategic health priority areas identified by the WHO Regional Office for the Eastern Mediterranean. We searched and reviewed health-related articles indexed in PubMed and originating from EMR countries from 2004 to 2018 and used these as indicators of the country's total biomedical research publication level. Data from a very large collection of over 300 000 articles were weighted to EMR's contribution to the global research output. We used the mean and standard deviation to summarise the continuous variables and used frequencies and percentages to summarise the categorical variables. Biomedical research publication in the EMR increased between 2004 and 2018. Five countries - Islamic Republic of Iran (43%), Egypt (14%), Saudi Arabia (11%), Pakistan (8%), and Tunisia (6%) - contributed 82% of all the publications, while the other countries contributed less than 4%. On average, EMR contributed 2.0% of the global biomedical research publications and 3.12 publications per 100 000 population for 2004-2018. Biomedical and health research publication increased unevenly across the EMR countries during the study period. Considering the complexity of the public health challenges in the region, there is a need for multidisciplinary and holistic approaches to health research to generate evidence for policy and to improve clinical and public health outcomes.

Rummagene: massive mining of gene sets from supporting materials of biomedical research publications

Many biomedical research publications contain gene sets in their supporting tables, and these sets are currently not available for search and reuse. By crawling PubMed Central, the Rummagene server provides access to hundreds of thousands of such mammalian gene sets. So far, we scanned 5,448,589 articles to find 121,237 articles that contain 642,389 gene sets. These sets are served for enrichment analysis, free text, and table title search. Investigating statistical patterns within the Rummagene database, we demonstrate that Rummagene can be used for transcription factor and kinase enrichment analyses, and for gene function predictions. By combining gene set similarity with abstract similarity, Rummagene can find surprising relationships between biological processes, concepts, and named entities. Overall, Rummagene brings to surface the ability to search a massive collection of published biomedical datasets that are currently buried and inaccessible. The Rummagene web application is available at https://rummagene.com.

A systematic review of retractions in biomedical research publications: reasons for retractions and their citations in Indian affiliations

Retractions of peer-reviewed biomedical journal articles with Indian authorship have been on the rise for many years. Our study aimed to investigate the reason behind these retractions, namely plagiarism, falsification, fabrication, duplicate publication, author conflicts, ethical issues, fake peer-reviews, and data-related issues, besides providing year-wise trends regarding retraction, authorship, impact factor, and citations. We retrieved retracted publications with Indian affiliations indexed in MEDLINE between 1 January 1990 to 31 December 2021. During this period a total of 619 papers from 372 different journals with median values (interquartile range) pertaining to impact factor [3.2 (1.5, 5.2)], retraction time [24 (10, 51)] months, pre-retraction citations [4 (1, 12)], and post-retraction citations [4 (2, 12)] were retracted. While retractions still account for a small fraction of all publications (0.1%), the overall rate of retractions, that is, the number of retractions relative to the number of newly published journal articles in a given year, has been increasing. The reasons for retractions included plagiarism (27%), falsification and fabrication (26%), duplicate publication (21%), erroneous data (12%), authorship issues (4%), fake-peer reviews (3%), and ethical and funding issues (2%). We have analysed these reasons separately and compared them with each other. Besides a spurt in retraction due to plagiarism, instances of falsification have been escalating over the past decade. Half of the papers retracted on grounds of falsification were published by repeat offender authors in high-impact journals. Furthermore, 82% of retracted papers continued to accumulate citations even after the release of the journal retraction notices. The increase in retractions raises concerns over research quality as well as the wastage of scientific resources, which is especially pressing considering the present environment of scarce funding. The problem of retractions due to reasons such as plagiarism, duplicate publication, authorship issues, and, ethical issues as well as post-retraction citations can be mitigated by educating and raising awareness on publication ethics and responsible research conduct of researchers and journal publishers. Retractions due to fabrication, falsification, and fake peer reviews are more challenging to difficult to address and require further research for the identification of effective solutions.

Predicting substantive biomedical citations without full text

Insights from biomedical citation networks can be used to identify promising avenues for accelerating research and its downstream bench-to-bedside translation. Citation analysis generally assumes that each citation documents substantive knowledge transfer that informed the conception, design, or execution of the main experiments. Citations may exist for other reasons. In this paper, we take advantage of late-stage citations added during peer review because these are less likely to represent substantive knowledge flow. Using a large, comprehensive feature set of open access data, we train a predictive model to identify late-stage citations. The model relies only on the title, abstract, and citations to previous articles but not the full-text or future citations patterns, making it suitable for publications as soon as they are released, or those behind a paywall (the vast majority). We find that high prediction scores identify late-stage citations that were likely added during the peer review process as well as those more likely to be rhetorical, such as journal self-citations added during review. Our model conversely gives low prediction scores to early-stage citations and citation classes that are known to represent substantive knowledge transfer. Using this model, we find that US federally funded biomedical research publications represent 30% of the predicted early-stage (and more likely to be substantive) knowledge transfer from basic studies to clinical research, even though these comprise only 10% of the literature. This is a threefold overrepresentation in this important type of knowledge flow.

Publications of Biomedical Research: Evolving Landscape and Constant Themes

The field of biomedical research publications has undergone significant changes in the last few years. The COVID pandemic catapulted forward an era of virtual scientific conferences, for which technological tools were quickly developed and established to enable display of conference presentations and posters on digital platforms. Although conferences have returned to in-person attendance, most still use a “hybrid” format, enabling virtual participation and on-demand access to digital conference materials. On the front of biomedical publishing by scholarly journals, there is a similar trend toward digital content beyond the traditional 2D format. Many journals have embraced digital enhancements of journal articles to extend the reach to a wider audience. Examples include video or audio abstracts, infographic summaries, plain language summaries, and social media posts, to name a few.

Deep learning to refine the identification of high-quality clinical research articles from the biomedical literature: Performance evaluation

BackgroundIdentifying practice-ready evidence-based journal articles in medicine is a challenge due to the sheer volume of biomedical research publications. Newer approaches to support evidence discovery apply deep learning techniques to improve the efficiency and accuracy of classifying sound evidence. ObjectiveTo determine how well deep learning models using variants of Bidirectional Encoder Representations from Transformers (BERT) identify high-quality evidence with high clinical relevance from the biomedical literature for consideration in clinical practice. MethodsWe fine-tuned variations of BERT models (BERTBASE, BioBERT, BlueBERT, and PubMedBERT) and compared their performance in classifying articles based on methodological quality criteria. The dataset used for fine-tuning models included titles and abstracts of >160,000 PubMed records from 2012 to 2020 that were of interest to human health which had been manually labeled based on meeting established critical appraisal criteria for methodological rigor. The data was randomly divided into 80:10:10 sets for training, validating, and testing. In addition to using the full unbalanced set, the training data was randomly undersampled into four balanced datasets to assess performance and select the best performing model. For each of the four sets, one model that maintained sensitivity (recall) at ≥99% was selected and were ensembled. The best performing model was evaluated in a prospective, blinded test and applied to an established reference standard, the Clinical Hedges dataset. ResultsIn training, three of the four selected best performing models were trained using BioBERTBASE. The ensembled model did not boost performance compared with the best individual model. Hence a solo BioBERT-based model (named DL-PLUS) was selected for further testing as it was computationally more efficient. The model had high recall (>99%) and 60% to 77% specificity in a prospective evaluation conducted with blinded research associates and saved >60% of the work required to identify high quality articles. ConclusionsDeep learning using pretrained language models and a large dataset of classified articles produced models with improved specificity while maintaining >99% recall. The resulting DL-PLUS model identifies high-quality, clinically relevant articles from PubMed at the time of publication. The model improves the efficiency of a literature surveillance program, which allows for faster dissemination of appraised research.

3 - A Decade of Biomedical Research in West Africa (2005–14): A Bibliometric Analysis of the Ten Most Productive Countries in MEDLINE

The objective of this research is to determine the quantity and quality of publications in biomedical research in top-producing countries in West Africa during 2005–14 as well as the characteristics of the journals and collaborative evidence in the area. Data was drawn from MEDLINE/ PubMed and Google Scholar while the impact factors of the journals were retrieved from the SCImago Journal and Country Rank portal. Quantity of publications was measured by counting the number of publications attributable to a country while h-index was extracted to measure quality. Productivity was analysed by sorting the data according to their first authors, journals and publication dates, and analysed using MS Excel and LOTKA®. Nigeria, Ghana, Senegal, Burkina Faso and Mali had the highest number of publications. In respect of productivity, apart from Côte d’Ivoire that had an α value less than 2, indicating a higher level of productivity, all other countries had an α value greater than 2. West African Journal of Medicine is the only journal of West African origin in the list of top ten journals where the authors from the sub-region published their papers, and it ranked tenth. Nigeria and Ghana published a lot more of their research papers in local journals in comparison with other countries, but these journals have very low mean impact factors. This study reinforces the need for improved research collaboration between the big and small countries.

Impact of COVID-19 Pandemic on Biomedical Publications and Their Citation Frequency.

BackgroundThe coronavirus disease 2019 (COVID-19) pandemic has resulted in enormous related publications. However, the citation frequency of these documents and their influence on the journal impact factor (JIF) are not well examined. We aimed to evaluate the impact of COVID-19 on biomedical research publications and their citation frequency.MethodsWe searched publications on biomedical research in the Web of Science using the search terms “COVID-19,” “SARS-Cov-2,” “2019 corona*,” “corona virus disease 2019,” “coronavirus disease 2019,” “novel coronavirus infection” and “2019-ncov.” The top 200 journals were defined as those with a higher number of COVID-19 publications than other journals in 2020. The COVID-19 impact ratio was calculated as the ratio of the average number of citations per item in 2021 to the JIF for 2020.ResultsThe average number of citations for the top 200 journals in 2021, per item published in 2020, was 25.7 (range, 0–270). The average COVID-19 impact ratio was 3.84 (range, 0.26–16.58) for 197 journals that recorded the JIF for 2020. The average JIF ratio for the top 197 journals including the JIFs for 2020 and 2021 was 1.77 (range, 0.68–8.89). The COVID-19 impact ratio significantly correlated with the JIF ratio (r = 0.403, P = 0.010). Twenty-five Korean journals with a COVID-19 impact ratio > 1.5 demonstrated a higher JIF ratio (1.31 ± 0.39 vs. 1.01 ± 0.18, P < 0.001) than 33 Korean journals with a lower COVID-19 impact ratio.ConclusionCOVID-19 pandemic infection has significantly impacted the trends in biomedical research and the citation of related publications.

Gender Disparity in the Authorship of Biomedical Research Publications During the COVID-19 Pandemic: Retrospective Observational Study.

BackgroundGender imbalances in academia have been evident historically and persist today. For the past 60 years, we have witnessed the increase of participation of women in biomedical disciplines, showing that the gender gap is shrinking. However, preliminary evidence suggests that women, including female researchers, are disproportionately affected by the COVID-19 pandemic in terms of unequal distribution of childcare, elderly care, and other kinds of domestic and emotional labor. Sudden lockdowns and abrupt shifts in daily routines have had disproportionate consequences on their productivity, which is reflected by a sudden drop in research output in biomedical research, consequently affecting the number of female authors of scientific publications.ObjectiveThe objective of this study is to test the hypothesis that the COVID-19 pandemic has had a disproportionate adverse effect on the productivity of female researchers in the biomedical field in terms of authorship of scientific publications.MethodsThis is a retrospective observational bibliometric study. We investigated the proportion of male and female researchers who published scientific papers during the COVID-19 pandemic, using bibliometric data from biomedical preprint servers and selected Springer-Nature journals. We used the ordinary least squares regression model to estimate the expected proportions over time by correcting for temporal trends. We also used a set of statistical methods, such as the Kolmogorov-Smirnov test and regression discontinuity design, to test the validity of the results.ResultsA total of 78,950 papers from the bioRxiv and medRxiv repositories and from 62 selected Springer-Nature journals by 346,354 unique authors were analyzed. The acquired data set consisted of papers that were published between January 1, 2019, and August 2, 2020. The proportion of female first authors publishing in the biomedical field during the pandemic dropped by 9.1%, on average, across disciplines (expected arithmetic mean yest=0.39; observed arithmetic mean y=0.35; standard error of the estimate, Sest=0.007; standard error of the observation, σx=0.004). The impact was particularly pronounced for papers related to COVID-19 research, where the proportion of female scientists in the first author position dropped by 28% (yest=0.39; y=0.28; Sest=0.007; σx=0.007). When looking at the last authors, the proportion of women dropped by 7.9%, on average (yest=0.25; y=0.23; Sest=0.005; σx=0.003), while the proportion of women writing about COVID-19 as the last author decreased by 18.8% (yest=0.25; y=0.21; Sest=0.005; σx=0.007). Further, by geocoding authors’ affiliations, we showed that the gender disparities became even more apparent when disaggregated by country, up to 35% in some cases.ConclusionsOur findings document a decrease in the number of publications by female authors in the biomedical field during the global pandemic. This effect was particularly pronounced for papers related to COVID-19, indicating that women are producing fewer publications related to COVID-19 research. This sudden increase in the gender gap was persistent across the 10 countries with the highest number of researchers. These results should be used to inform the scientific community of this worrying trend in COVID-19 research and the disproportionate effect that the pandemic has had on female academics.

Softcite dataset: A dataset of software mentions in biomedical and economic research publications

AbstractSoftware contributions to academic research are relatively invisible, especially to the formalized scholarly reputation system based on bibliometrics. In this article, we introduce a gold‐standard dataset of software mentions from the manual annotation of 4,971 academic PDFs in biomedicine and economics. The dataset is intended to be used for automatic extraction of software mentions from PDF format research publications by supervised learning at scale. We provide a description of the dataset and an extended discussion of its creation process, including improved text conversion of academic PDFs. Finally, we reflect on our challenges and lessons learned during the dataset creation, in hope of encouraging more discussion about creating datasets for machine learning use.

Steps Toward Minimal Reporting Standards for Lipidomics Mass Spectrometry in Biomedical Research Publications.

Steps Toward Minimal Reporting Standards for Lipidomics Mass Spectrometry in Biomedical Research Publications.

Security in BioMedical Research publications.

Security in BioMedical Research publications.

The unfortunately long life of some retracted biomedical research publications.

In 2005 the scientific misconduct case of a noted researcher concluded with, among other things, the retraction of 10 papers. However, these articles continue to be cited at relatively high rates. The objectives of this paper are: 1) to track the retraction process of these papers, 2) to assess the impact of retraction on subsequent citation rates of these papers, and 3) to compare the citation history of these retracted articles and five other high-profile retraction cases. For objective 1, all five articles to be retracted were retracted and of the four to be corrected, two were retracted and two were corrected. Eight PubMed and journal sites were identified where retraction messages could be conveyed; the number of retraction messages averaged 3.4 ± 2.5 for these nine articles. For objective 2, an absolute "cleansing" did not occur. While it initially appears there was a relative "cleansing," as citation rates for these articles did decrease after retraction, the reductions in citation rates for these articles (-28%) were the same as those for matched nonretracted publications both by the same author (-28%) and by another investigator (-29%) over the same time frame. Relative to objective 3, the results for this case are quite different from the five other cases assessing this issue, perhaps because of this investigator's "citation inertia" as a result of the small percentage of his papers that were retracted and the large number of citations to the articles before their retraction and to all of his published articles.NEW & NOTEWORTHY The scientific misconduct and fraud case of a noted exercise physiology researcher was concluded ~15 yr ago, and one the of the results was the retraction of 10 published manuscripts. However, based on a number of comparisons to that same author's and another investigator's citation histories for similar articles, the citation histories for these retracted articles appear to not have been affected whatsoever in the subsequent 15 yr.

Survey of equal contributions in biomedical research publications

ABSTRACTWe conducted a cross-sectional survey of 1,540 researchers concerning their experiences with and attitudes toward the ethics of equal contribution (EC) designations in publications. Over half the respondents (58.3%) said they had been designated as an EC at least once. Although most respondents agreed that EC designations can be a useful way of promoting collaborations (81.7%) or resolving disagreements about authorship order (63.3%), a substantial proportion of respondents (38.1%) regarded these designations as useful but ethically questionable. 31.7% of respondents said EC designations are ethically questionable because ECs are difficult to define or measure and 25.9% said they are ethically questionable because people rarely contribute equally. Most respondents (71.8%) agreed that it is unfair to name two people as ECs when they have not contributed equally and that journals (73.4%), research teams (69.5%), and research institutions (63%) should develop policies concerning EC designations. Views concerning the ethics and policies of EC designations were influenced by the race/ethnicity and position of respondents but not by gender. Researchers who had been designated as ECs were less likely to regard this practice as ethically questionable than those who had not.

Impact of critical care medicine publications from intensive care department at King Abdulaziz Medical City, Riyadh in the last two decades.

Introduction :The volume and quality of biomedical research publications from an institution are considered adequate indicators of the quality of medical care in that institute. King Abdulaziz Medical City (KAMC), Riyadh, Kingdom of Saudi Arabia (KSA), is one of the oldest and most distinguished medical centers in the country.Methods:In this study, we analyzed the number of publications from the Critical Care Unit of the hospital in the past two decades, from 1996 to 2016. The research publications were evaluated on various parameters. Moreover, the impact of their study on global medicine was determined.Results:Our results indicate a steady progression in the number of publications from the institute in the past two decades. An average of 17.3 papers was published each year during this time. Out of the 283 publications from KAMC included in this study, the majority of the publications were original articles, 61 were review articles, 66 were multicenter trial studies and 28 were randomized control trials. The citation profile of the publications was good indicating global impact of the studies.Conclusion:The global impact of research as evaluated through published manuscripts in KAMC is overall good. This was deduced from both the increase in the number of publications each year and also the quality of papers as evidenced by the citation index of the papers published between 1996 and 2016.

Semi-automated fact-checking of nucleotide sequence reagents in biomedical research publications: The Seek & Blastn tool.

Nucleotide sequence reagents are verifiable experimental reagents in biomedical publications, because their sequence identities can be independently verified and compared with associated text descriptors. We have previously reported that incorrectly identified nucleotide sequence reagents are characteristic of highly similar human gene knockdown studies, some of which have been retracted from the literature on account of possible research fraud. Because of the throughput limitations of manual verification of nucleotide sequences, we developed a semi-automated fact checking tool, Seek & Blastn, to verify the targeting or non-targeting status of published nucleotide sequence reagents. From previously described and unknown corpora of 48 and 155 publications, respectively, Seek & Blastn correctly extracted 304/342 (88.9%) and 1066/1522 (70.0%) nucleotide sequences and a predicted targeting/ non-targeting status. Seek & Blastn correctly predicted the targeting/ non-targeting status of 293/304 (96.4%) and 988/1066 (92.7%) of the correctly extracted nucleotide sequences. A total of 38/39 (97.4%) or 31/79 (39.2%) Seek & Blastn predictions of incorrect nucleotide sequence reagent use were correct in the two literature corpora. Combined Seek & Blastn and manual analyses identified a list of 91 misidentified nucleotide sequence reagents, which could be built upon through future studies. In summary, incorrect nucleotide sequence reagents represent an under-recognized source of error within the biomedical literature, and fact checking tools such as Seek & Blastn may help to identify papers and manuscripts affected by these errors.

From POS tagging to dependency parsing for biomedical event extraction

BackgroundGiven the importance of relation or event extraction from biomedical research publications to support knowledge capture and synthesis, and the strong dependency of approaches to this information extraction task on syntactic information, it is valuable to understand which approaches to syntactic processing of biomedical text have the highest performance.ResultsWe perform an empirical study comparing state-of-the-art traditional feature-based and neural network-based models for two core natural language processing tasks of part-of-speech (POS) tagging and dependency parsing on two benchmark biomedical corpora, GENIA and CRAFT. To the best of our knowledge, there is no recent work making such comparisons in the biomedical context; specifically no detailed analysis of neural models on this data is available. Experimental results show that in general, the neural models outperform the feature-based models on two benchmark biomedical corpora GENIA and CRAFT. We also perform a task-oriented evaluation to investigate the influences of these models in a downstream application on biomedical event extraction, and show that better intrinsic parsing performance does not always imply better extrinsic event extraction performance.ConclusionWe have presented a detailed empirical study comparing traditional feature-based and neural network-based models for POS tagging and dependency parsing in the biomedical context, and also investigated the influence of parser selection for a biomedical event extraction downstream task.Availability of data and materialsWe make the retrained models available at https://github.com/datquocnguyen/BioPosDep.

50 years of Iranian clinical, biomedical, and public health research: a bibliometric analysis of the Web of Science Core Collection (1965-2014).

BackgroundA substantial growth has been reported in Iran’s number of clinical, biomedical, and public health research publications over the last 30 years. It is of interest to investigate whether this quantitative growth has also led to a larger number of papers with a high citation impact; to explore where the capacity for performing research lies; and which fields/institutions are lagging behind.MethodsThis was a bibliometric study. Web of Science Core Collection and its different tools were used for retrieving and analysing the publications. Information about the journals was found on Journal Citation Reports®. Different types of collaborations across the highly-cited papers was investigated based on the affiliations, the characteristics of the language of the authors’ names, and the authors’ study and work backgrounds.ResultsIran’s number of clinical, biomedical, and public health research publications has substantially increased since 2000, a surge was seen in 2007, and the figure reached a peak in 2011. 11% of the publications were in Pharmacology Pharmacy; and the majority originated in Tehran University of Medical Sciences. Six of the 10 journals that had published the most were Iranian journals. H-index of publications had also increased over time (almost doubled between 2000 and 2010). 30.9% of the most-cited publications had only relied on Iranian resources (including 48 publications); had been published in journals with impact factors ranging between 0.4 and 8.3; and the majority were original basic sciences research.ConclusionsIn Iran, a great capacity for research lies in clinical, biomedical, and public health fields which can be strengthened with further investment. It is important to use this capacity in a way that would align with the national population health needs. It is also essential to consider the limitations of only relying on bibliometric tools for assessing health research activities. Finally, the Iranian science policy-makers are encouraged to (i) support the researchers and institutions that have proved research capacity; (ii) direct further resources towards research areas and/or institutions that are lagging behind; (iii) facilitate further international collaboration with the academics and/or institutions that have shown the capacity for conducting successful research projects with Iran.