Publishing in the Open Access and Open Science era.

Our research activities would be better served if they were communicated in a manner that is openly accessible to the public and all researchers. The research we share is often limited to representative data included in research papers-science would be much more efficient if all reproducible research data were shared alongside detailed methods and protocols, in the paradigm called Open Science. On the other hand, one primary function of research journals is to select manuscripts of good quality, verify the authenticity of the data and its impact, and deliver to the appropriate audience for critical evaluation and verification. In the current paradigm, where publication in a subset of journals is intimately linked to research evaluation, a hypercompetitive "market" has emerged where authors compete to access a limited number of top-tier journals, leading to high rejection rates. Competition among publishers and scientific journals for market dominance resulted in an increase in both the number of journals and the cost of publishing and accessing scientific papers. Here we summarize the current problems and potential solutions from the development of AI technology discussed in the seminar at the 46th Annual Meeting of the Molecular Biology Society of Japan.

Proposal for a Global Classification and Nomenclature System for A/H9 Influenza Viruses.

Influenza A/H9 viruses circulate worldwide in wild and domestic avian species, continuing to evolve and posing a zoonotic risk. A substantial increase in human infections with A/H9N2 subtype avian influenza viruses (AIVs) and the emergence of novel reassortants carrying A/H9N2-origin internal genes has occurred in recent years. Different names have been used to describe the circulating and emerging A/H9 lineages. To address this issue, an international group of experts from animal and public health laboratories, endorsed by the WOAH/FAO Network of Expertise on Animal Influenza, has created a practical lineage classification and nomenclature system based on the analysis of 10,638 hemagglutinin sequences from A/H9 AIVs sampled worldwide. This system incorporates phylogenetic relationships and epidemiologic characteristics designed to trace emerging and circulating lineages and clades. To aid in lineage and clade assignment, an online tool has been created. This proposed classification enables rapid comprehension of the global spread and evolution of A/H9 AIVs.

Maximizing Access and Minimizing Barriers to Research in Low- and Middle-Income Countries: Open Access and Health Equity.

Access to published research has always been difficult for researchers and clinicians in low- and middle-income countries, because of the cost of and lack of access to the relevant publications. The dramatic recent increase in electronic research publications has resulted in a marked improvement in reader access to these publications through their mainly Open Access policies, however the costs of processing of submissions and publication have now become the burden of the researchers wishing to publish, rather than the readers. For many researchers working in LMIC, the Article Processing Charges (APC) are prohibitive, hampering the publication of research being conducted in and relevant to these countries. A number of grant funding agencies and international not-for-profit organizations are trying to address these issues by including funding for article publications in their grants, or by supporting publishing entities by subsiding the cost of publication, but more needs to be done by major journal publishers through markedly reducing the APC being charged to researchers in LMIC for open access facilities.

Are you aware of your citations? A cross-sectional survey on improper citations of retracted articles in assisted reproduction.

RESEARCH QUESTION: Are authors aware when they have cited a retracted paper in their manuscripts in the medically assisted reproduction (MAR) field? DESIGN: A cross-sectional study based on an online survey was conducted to acquire information on the citation pattern from corresponding authors who had cited a retracted article. A dataset of retracted articles in the MAR field was collected from PubMed and Retraction Watch. A complete list of published articles that cited each retracted article was retrieved. The survey was distributed via e-mail to corresponding authors who had cited a retracted paper in their study. RESULTS: The survey revealed a significant lack of awareness among authors, with 78.7% unaware that they had cited retracted articles. This lack of awareness was attributed to insufficient notification mechanisms within research databases and journals, alongside a reliance on previously stored copies of manuscripts. A notable finding was that reference checks were typically performed by a single author, with no instances of retraction concerns raised during the peer-review process. Only a small fraction (17.8%) of respondents reported verifying retraction notices on both journal websites and scientific databases. CONCLUSIONS: Correcting publications that contain references which are subsequently retracted is significant for systematic reviews, meta-analyses and guidelines. Citations of retracted articles perpetuate erroneous scientific data, but assessing the accuracy of citations requires considerable effort. Proper notification of retraction status and cross-checking of citations can help to prevent errors.

Equisetin protects from atherosclerosis in vivo by binding to STAT3 and inhibiting its activity.

Atherosclerosis is a chronic inflammatory vascular disease characterized by lipid metabolism disorder and lipid accumulation. Equisetin (EQST) is a hemiterpene compound isolated from fungus of marine sponge origin, which has antibacterial, anti-inflammatory, lipid-lowering, and weight loss effects. Whether EQST has anti-atherosclerotic activity has not been reported. In this study, we revealed that EQST displayed anti- atherosclerosis effects through inhibiting macrophage inflammatory response, lipid uptake and foam cell formation in vitro, and finally ameliorated high-fat diet (HFD)-induced atherosclerosis in AopE-/- mice in vivo. Mechanistically, EQST directly bound to STAT3 with high-affinity by forming hydrophobic bonds at GLN247 and GLN326 residues, as well as hydrogen bonds at ARG325 and THR346 residues. EQST interacted with STAT3 physically, and functionally inhibited the transcription activity of STAT3, thereby regulating atherosclerosis. Therefore, these results supports EQST as a candidate for developing anti-atherosclerosis therapeutic agent.

Carnosic acid: an effective phenolic diterpenoid for prevention and management of cancers via targeting multiple signaling pathways.

Cancer is a serious global public health issue, and a great deal of research has been made to treat cancer. Of these, discovery of promising compounds that effectively fight cancer always has been the main point of interest in pharmaceutical research. Carnosic acid (CA) is a phenolic diterpenoid compound widely present in Lamiaceae plants such as Rosemary (Rosmarinus officinalis L.). In recent years, there has been increasing evidence that CA has significant anti-cancer activity, such as leukaemia, colorectal cancer, breast cancer, lung cancer, liver cancer, pancreatic cancer, stomach cancer, lymphoma, prostate cancer, oral cancer, etc. The potential mechanisms involved by CA, including inhibiting cell proliferation, inhibiting metastasis, inducing cell apoptosis, stimulating autophagy, regulating the immune system, reducing inflammation, regulating the gut microbiota, and enhancing the effects of other anti-cancer drugs. This article reviews the biosynthesis, pharmacokinetics and metabolism, safety and toxicity, as well as the molecular mechanisms and signaling pathways of the anticancer activity of CA. This will contribute to the development of CA or CA-containing functional foods for the prevention and treatment of cancer, providing important advances in the advancement of cancer treatment strategies.

GPR40 agonist ameliorates neurodegeneration and motor impairment by regulating NLRP3 inflammasome in Parkinson's disease animal models.

Parkinson's disease (PD) is characterized by the progressive degeneration of dopaminergic neurons in the substantia nigra (SN) and accumulation of intracellular α-synuclein (ɑ-syn) aggregates known as Lewy bodies and Lewy neurites. Levels of polyunsaturated fatty acids (PUFAs) have previously been shown to be reduced in the SN of PD patients. G protein-coupled receptor 40 (GPR40) serves as a receptor for PUFAs, playing a role in neurodevelopment and neurogenesis. Additionally, GPR40 has been implicated in several neuropathological conditions, such as apoptosis and inflammation, suggesting its potential as a therapeutic target in PD. In this study, we investigated the neuroprotective effects of the GPR40 agonist, TUG469 in PD models. Our results demonstrated that TUG469 reduces the neurotoxicity induced by 6-OHDA in SH-SY5Y cells. In 6-OHDA-induced PD model mice, TUG469 treatment improved motor impairment, preserved dopaminergic fibers and cell bodies in the striatum (ST) or SN, and attenuated 6-OHDA-induced microgliosis and astrogliosis in the brain. Furthermore, in a PD model involving the injection of mouse ɑ-syn fibrils into the brain (mPFFs-PD model), TUG469 treatment reduced the levels of pSer129 ɑ-syn, and decreased microgliosis and astrogliosis. Our investigation also revealed that TUG469 modulates inflammasome activation, apoptosis, and autophagy in the 6-OHDA-PD model, as evidenced by the results of RNA-seq and western blotting analyses. In summary, our findings highlight the neuroprotective effects of GPR40 agonists on dopaminergic neurons and their potential as therapeutic agents for PD. These results underscore the importance of targeting GPR40 in PD treatment, particularly in mitigating neuroinflammation and preserving neuronal integrity.

Unwrapping the structural and functional features of antimicrobial peptides from wasp venoms.

The study of wasp venoms has captured attention due to the presence of a wide variety of active compounds, revealing a diverse array of biological effects. Among these compounds, certain antimicrobial peptides (AMPs) such as mastoparans and chemotactic peptides have emerged as significant players, characterized by their unique amphipathic short linear alpha-helical structure. These peptides exhibit not only antibiotic properties but also a range of other biological activities, which are related to their ability to interact with biological membranes to varying degrees. This review article aims to provide updated insights into the structure/function relationships of AMPs derived from wasp venoms, linking this knowledge to the potential development of innovative treatments against infections.

Methodological insights into ChatGPT's screening performance in systematic reviews.

BACKGROUND: The screening process for systematic reviews and meta-analyses in medical research is a labor-intensive and time-consuming task. While machine learning and deep learning have been applied to facilitate this process, these methods often require training data and user annotation. This study aims to assess the efficacy of ChatGPT, a large language model based on the Generative Pretrained Transformers (GPT) architecture, in automating the screening process for systematic reviews in radiology without the need for training data. METHODS: A prospective simulation study was conducted between May 2nd and 24th, 2023, comparing ChatGPT's performance in screening abstracts against that of general physicians (GPs). A total of 1198 abstracts across three subfields of radiology were evaluated. Metrics such as sensitivity, specificity, positive and negative predictive values (PPV and NPV), workload saving, and others were employed. Statistical analyses included the Kappa coefficient for inter-rater agreement, ROC curve plotting, AUC calculation, and bootstrapping for p-values and confidence intervals. RESULTS: ChatGPT completed the screening process within an hour, while GPs took an average of 7-10 days. The AI model achieved a sensitivity of 95% and an NPV of 99%, slightly outperforming the GPs' sensitive consensus (i.e., including records if at least one person includes them). It also exhibited remarkably low false negative counts and high workload savings, ranging from 40 to 83%. However, ChatGPT had lower specificity and PPV compared to human raters. The average Kappa agreement between ChatGPT and other raters was 0.27. CONCLUSIONS: ChatGPT shows promise in automating the article screening phase of systematic reviews, achieving high sensitivity and workload savings. While not entirely replacing human expertise, it could serve as an efficient first-line screening tool, particularly in reducing the burden on human resources. Further studies are needed to fine-tune its capabilities and validate its utility across different medical subfields.

Machine learning models for abstract screening task - A systematic literature review application for health economics and outcome research.

OBJECTIVE: Systematic literature reviews (SLRs) are critical for life-science research. However, the manual selection and retrieval of relevant publications can be a time-consuming process. This study aims to (1) develop two disease-specific annotated corpora, one for human papillomavirus (HPV) associated diseases and the other for pneumococcal-associated pediatric diseases (PAPD), and (2) optimize machine- and deep-learning models to facilitate automation of the SLR abstract screening. METHODS: This study constructed two disease-specific SLR screening corpora for HPV and PAPD, which contained citation metadata and corresponding abstracts. Performance was evaluated using precision, recall, accuracy, and F1-score of multiple combinations of machine- and deep-learning algorithms and features such as keywords and MeSH terms. RESULTS AND CONCLUSIONS: The HPV corpus contained 1697 entries, with 538 relevant and 1159 irrelevant articles. The PAPD corpus included 2865 entries, with 711 relevant and 2154 irrelevant articles. Adding additional features beyond title and abstract improved the performance (measured in Accuracy) of machine learning models by 3% for HPV corpus and 2% for PAPD corpus. Transformer-based deep learning models that consistently outperformed conventional machine learning algorithms, highlighting the strength of domain-specific pre-trained language models for SLR abstract screening. This study provides a foundation for the development of more intelligent SLR systems.

Understanding author choices in the current conservation publishing landscape.

Conservation literature addresses a broad spectrum of interdisciplinary questions and benefits. Conservation science benefits most when a diverse range of authors are represented, particularly those from countries where much conservation work is focused. In other disciplines, it is well known that barriers and biases exist in the academic publishing sphere, which can affect research dissemination and an author's career development. We used a discrete choice experiment to determine how 7 journal attributes affect authors' choices of where to publish in conservation. We targeted authors directly by contacting authors published in 18 target journals and indirectly via communication channels for conservation organizations. We only included respondents who had previously published in a conservation-related journal. We used a multinomial logit model and a latent class model to investigate preferences for all respondents and distinct subpopulations. We identified 3 demographic groups across 1038 respondents (older authors from predominantly middle-income countries, younger authors from predominantly middle-income countries, and younger authors from high-income countries) who had published in conservation journals. Each group exhibited different publishing preferences. Only 2 attributes showed a consistent response across groups: cost to publish negatively affected journal choice, including authors in high-income countries, and authors had a consistent preference for double-blind review. Authors from middle-income countries were willing to pay more for society-owned journals, unlike authors from high-income countries. Journals with a broad geographical scope that were open access and that had relatively high impact factors were preferred by 2 of the 3 demographic groups. However, journal scope and open access were more important in dictating journal choice than impact factor. Overall, different demographics had different preferences for journals and were limited in their selection based on attributes such as open access policy. However, the scarcity of respondents from low-income countries (2% of respondents) highlights the pervasive barriers to representation in conservation research. We recommend journals offer double-blind review, reduce or remove open access fees, investigate options for free editorial support, and better acknowledge the value of local-scale single-species studies. Academic societies in particular must reflect on how their journals support conservation and conservation professionals.

Comprensión de las elecciones de los autores en el entorno actual de publicaciones sobre la conservación Resumen La bibliografía sobre conservación aborda un amplio espectro de preguntas y beneficios interdisciplinarios. La mayor parte de ella representa una gama diversa de autores, sobre todo de países en los que se centra gran parte del trabajo de conservación. Es bien sabido que en otras disciplinas existen barreras y sesgos en el ámbito de la publicación académica que pueden afectar a la difusión de la investigación y al desarrollo de la carrera de un autor. Usamos un experimento de elección discreta para determinar cómo afectan siete atributos de las revistas sobre conservación en la elección de los autores sobre en cuál publicar. Nos dirigimos directamente a los autores y nos pusimos en contacto con quienes publicaban en 18 revistas objetivo e indirectamente a través de los canales de comunicación de las organizaciones de conservación. Sólo incluimos a los encuestados que habían publicado anteriormente en una revista relacionada con la conservación. Usamos un modelo logit multinominal y un modelo de clases latentes para investigar las preferencias de todos los encuestados y de las distintas subpoblaciones. Identificamos tres grupos demográficos entre los 1038 encuestados (autores de más edad de países con predominancia de ingresos medios, autores más jóvenes de países con predominancia de ingresos medios y autores más jóvenes de países con ingresos altos) que habían publicado en revistas de conservación. Cada grupo mostraba preferencias editoriales diferentes. Sólo dos atributos mostraron una respuesta coherente en todos los grupos: el costo de la publicación afectaba negativamente a la elección de la revista, incluidos los autores de países con ingresos altos, y los autores tenían una preferencia coherente por la revisión doble ciego. Los autores de países con ingresos medios están dispuestos a pagar más por las revistas pertenecientes a la sociedad, a diferencia de los autores de países de ingresos altos. Dos de los tres grupos demográficos prefieren las revistas de ámbito geográfico amplio, de acceso abierto y con un factor de impacto relativamente alto. Sin embargo, el alcance de la revista y el acceso abierto fueron más importantes que el factor de impacto. En general, los distintos grupos demográficos tenían preferencias diferentes en cuanto a las revistas y su selección se veía limitada por atributos como la política de acceso abierto. No obstante, la falta de encuestados procedentes de países con bajos ingresos (2% de los encuestados) destaca las barreras generalizadas para la representación en la investigación sobre conservación. Recomendamos que las revistas ofrezcan revisiones doble ciego, reduzcan o eliminen las tarifas de acceso abierto, investiguen opciones de apoyo editorial gratuito y reconozcan mejor el valor de los estudios de una sola especie a escala local. Las sociedades académicas, en particular, deben reflexionar sobre la forma en que sus revistas apoyan la conservación y a los profesionales de la conservación.

News coverage of older drivers' fatal car crashes: is it over-represented?

BACKGROUND: Japan's stringent licensing policies for older drivers have not been questioned, possibly due to negative perceptions of older drivers potentially influenced by media coverage of their car crashes. We examined whether older drivers' fatal crashes are over-represented in the news articles. METHODS: To examine the news coverage of fatal crashes that occurred between January 2016 and December 2020, we extracted driver- and crash-related data from articles reporting fatal crashes in the two best-selling newspapers, Yomiuri and Asahi. We obtained the corresponding data of police-reported fatal crashes during the same period. We calculated the proportion of newspaper-reported fatal crashes to police-reported fatal crashes by at-fault driver's age group and crash characteristics. RESULTS: Of 12,987 police-reported fatal crashes, 5,888 (45%) and 2,909 (22%) crashes were reported in Yomiuri and Asahi newspapers, respectively. Excluding 2,098 crashes where at-fault drivers or their ages were not identifiable, Yomiuri reported 39%, 35%, and 31%, and Asahi reported 20%, 16%, and 14% of fatal crashes caused by drivers aged <30 years, 30-69 years, and 70 years or older, respectively. Crashes that caused more fatalities or killed children tended to be reported regardless of at-fault drivers' age groups. Compared with young and middle-aged drivers, older drivers' fatal crashes involving child fatalities were more reported, whereas their single fatal crashes ending in their own deaths were less reported. CONCLUSION: Older drivers' at-fault fatal crashes were not over-represented in the news coverage of overall fatal crashes, and their crashes killing themselves were under-reported.

The Utility of AI in Writing a Scientific Review Article on the Impacts of COVID-19 on Musculoskeletal Health.

PURPOSE OF REVIEW: There were two primary purposes to our reviews. First, to provide an update to the scientific community about the impacts of COVID-19 on musculoskeletal health. Second, was to determine the value of using a large language model, ChatGPT 4.0, in the process of writing a scientific review article. To accomplish these objectives, we originally set out to write three review articles on the topic using different methods to produce the initial drafts of the review articles. The first review article was written in the traditional manner by humans, the second was to be written exclusively using ChatGPT (AI-only or AIO), and the third approach was to input the outline and references selected by humans from approach 1 into ChatGPT, using the AI to assist in completing the writing (AI-assisted or AIA). All review articles were extensively fact-checked and edited by all co-authors leading to the final drafts of the manuscripts, which were significantly different from the initial drafts. RECENT FINDINGS: Unfortunately, during this process, it became clear that approach 2 was not feasible for a very recent topic like COVID-19 as at the time, ChatGPT 4.0 had a cutoff date of September 2021 and all articles published after this date had to be provided to ChatGPT, making approaches 2 and 3 virtually identical. Therefore, only two approaches and two review articles were written (human and AI-assisted). Here we found that the human-only approach took less time to complete than the AI-assisted approach. This was largely due to the number of hours required to fact-check and edit the AI-assisted manuscript. Of note, the AI-assisted approach resulted in inaccurate attributions of references (about 20%) and had a higher similarity index suggesting an increased risk of plagiarism. The main aim of this project was to determine whether the use of AI could improve the process of writing a scientific review article. Based on our experience, with the current state of technology, it would not be advised to solely use AI to write a scientific review article, especially on a recent topic.

SEA-NET: medical image segmentation network based on spiral squeeze-and-excitation and attention modules.

BACKGROUND: Medical image segmentation is an important processing step in most of medical image analysis. Thus, high accuracy and robustness are required for them. The current deep neural network based medical segmentation methods have good effect on image with balanced foreground and background, but it will loss the characteristics of small targets on image with imbalanced foreground and background after multiple convolutions. METHODS: In order to retain the features of small targets in the deep network, we proposed a new medical image segmentation model based on the U-Net with squeeze-and-excitation and attention modules which form a spiral closed path,callled as Spiral Squeeze-and-Excitation and Attention NET (SEA-NET) in this paper. The segmentation model used squeeze-and-extraction modules to adjust the channel information to enhance the useful information and used attention modules to adjust the spatial information of the feature map to highlight the target area for small target segmentation when up-sampling. The deep semantic information is integrated into the shallow feature map by the attention model. Therefore, the deep semantic information cannot be scattered by continuous up-sampling. We used cross entropy loss + Tversky loss function for fast convergence and well processing the imbalanced data sets. Our proposed SEA-NET was tested on the brain MRI dataset LPBA40 and peripheral blood smear images. CONCLUSIONS: On brain MRI data, the average value of the Dice coefficient we obtained reached 98.1[Formula: see text]. On the peripheral blood smear dataset, our proposed model has a good segmentation effect on adhesion cells. RESULTS: The experimental results proved that the proposed SEA-Net performed better than U-Net, U-Net++, etc. in medical image segmentation.

The causal relationship between atopic dermatitis and brain cancer: A bidirectional Mendelian randomization study.

BACKGROUND: Atopic dermatitis ranks among the prevalent skin disorders. Research has indicated a potential association with brain cancer. Yet, establishing a direct causal relationship between atopic dermatitis and brain cancer continues to be challenging. MATERIALS AND METHODS: We extracted single nucleotide polymorphisms (SNPs) significantly associated with atopic dermatitis (sample size = 382 254) at a genome-wide level from a large Finnish Genome-Wide Association Study (GWAS) dataset (n cases = 15 208, n controls = 367 046). Summary data for 372 622 cases of brain cancer (n cases = 606, n controls = 372 016) were obtained via the IEU Open GWAS database. We employed the Inverse Variance Weighted (IVW) method as our primary analytical approach for Mendelian Randomization (MR) analysis. Additionally, heterogeneity was measured using Cochran's Q value, and horizontal pleiotropy was evaluated using MR-Egger 、Mendelian Randomization Pleiotropy RESidual Sum and Outlier and leave-one-out analyses. RESULTS: The risk of brain cancer increases with the presence of atopic dermatitis, as evidenced by the odds ratios (ORs) and 95% confidence intervals (CIs),(OR = 1.0005; 95% CI = 1.0001, 1.0009; p = 0.0096). However, when conducting the analysis in reverse, no significant link was observed. CONCLUSION: The findings from our study indicate a causative link between atopic dermatitis and brain cancer, highlighting the importance of conducting broader clinical investigations into their potential association going forward.

Effect of direct voltage induction by low-frequency security systems on neurostimulator lead.

Low-frequency (LF) security systems, such as antitheft electronic article surveillance (EAS) gates emit strong magnetic fields that could potentially interfere with neurostimulator operation. Some patients reported pain and shocking sensations near EAS gates, even after they turned off their pulse generator. To investigate the direct voltage induction of EAS systems on neurostimulator leads, we evaluated voltages induced by two EAS systems (14 kHz continuous wave or 58 kHz pulsed) on a 40 cm sacral neurostimulator lead formed in a circular loop attached to a pulse generator that was turned off. The lead and neurostimulator were mounted in a saline-filled rectangular phantom placed within electromagnetic fields emitted by EAS systems. The measured voltage waveforms were applied to computational models of spinal nerve axons to predict whether these voltages may evoke action potentials. Additional in vitro testing was performed on the semicircular lead geometry, to study the effect of lead geometry on EAS induced voltages. While standard neurostimulator testing per ISO 14708-3:2017 recommends electromagnetic compatibility testing with LF magnetic fields for induction of malfunctions of the active electronic circuitry while generating intended stimulating pulses, our results show that close to the EAS antenna frames, the induced voltage on the lead could be strong enough to evoke action potentials, even with the pulse generator turned off. This work suggests that patient reports of pain and shocking sensations when near EAS systems could also be correlated with the direct EAS-induced voltage on neurostimulator lead.

The McMaster Health Information Research Unit: Over a Quarter-Century of Health Informatics Supporting Evidence-Based Medicine.

Evidence-based medicine (EBM) emerged from McMaster University in the 1980-1990s, which emphasizes the integration of the best research evidence with clinical expertise and patient values. The Health Information Research Unit (HiRU) was created at McMaster University in 1985 to support EBM. Early on, digital health informatics took the form of teaching clinicians how to search MEDLINE with modems and phone lines. Searching and retrieval of published articles were transformed as electronic platforms provided greater access to clinically relevant studies, systematic reviews, and clinical practice guidelines, with PubMed playing a pivotal role. In the early 2000s, the HiRU introduced Clinical Queries-validated search filters derived from the curated, gold-standard, human-appraised Hedges dataset-to enhance the precision of searches, allowing clinicians to hone their queries based on study design, population, and outcomes. Currently, almost 1 million articles are added to PubMed annually. To filter through this volume of heterogenous publications for clinically important articles, the HiRU team and other researchers have been applying classical machine learning, deep learning, and, increasingly, large language models (LLMs). These approaches are built upon the foundation of gold-standard annotated datasets and humans in the loop for active machine learning. In this viewpoint, we explore the evolution of health informatics in supporting evidence search and retrieval processes over the past 25+ years within the HiRU, including the evolving roles of LLMs and responsible artificial intelligence, as we continue to facilitate the dissemination of knowledge, enabling clinicians to integrate the best available evidence into their clinical practice.

Twenty-Five Years of Progress-Lessons Learned From JMIR Publications to Address Gender Parity in Digital Health Authorships: Bibliometric Analysis.

BACKGROUND: Digital health research plays a vital role in advancing equitable health care. The diversity of research teams is thereby instrumental in capturing societal challenges, increasing productivity, and reducing bias in algorithms. Despite its importance, the gender distribution within digital health authorship remains largely unexplored. OBJECTIVE: This study aimed to investigate the gender distribution among first and last authors in digital health research, thereby identifying predicting factors of female authorship. METHODS: This bibliometric analysis examined the gender distribution across 59,980 publications from 1999 to 2023, spanning 42 digital health journals indexed in the Web of Science. To identify strategies ensuring equality in research, a detailed comparison of gender representation in JMIR journals was conducted within the field, as well as against a matched sample. Two-tailed Welch 2-sample t tests, Wilcoxon rank sum tests, and chi-square tests were used to assess differences. In addition, odds ratios were calculated to identify predictors of female authorship. RESULTS: The analysis revealed that 37% of first authors and 30% of last authors in digital health were female. JMIR journals demonstrated a higher representation, with 49% of first authors and 38% of last authors being female, yielding odds ratios of 1.96 (95% CI 1.90-2.03; P<.001) and 1.78 (95% CI 1.71-1.84; P<.001), respectively. Since 2008, JMIR journals have consistently featured a greater proportion of female first authors than male counterparts. Other factors that predicted female authorship included having female authors in other relevant positions and gender discordance, given the higher rate of male last authors in the field. CONCLUSIONS: There was an evident shift toward gender parity across publications in digital health, particularly from the publisher JMIR Publications. The specialized focus of its sister journals, equitable editorial policies, and transparency in the review process might contribute to these achievements. Further research is imperative to establish causality, enabling the replication of these successful strategies across other scientific fields to bridge the gender gap in digital health effectively.

Application of cognitive load theory in reading English academic articles on medical education among Chinese undergraduate medical students.

Reading English academic articles is the cornerstone of innovative medical education and scientific research. However, limited by both language and professional knowledge, many nonnative English-speaking undergraduate medical students have a fear of reading English academic articles. The purpose of this study was to explore whether cognitive load theory can be a useful guiding strategy to promote English medical education article reading among Chinese undergraduates, while also evaluating students' attitudes toward the reading activities and cognitive load entailed in the last article they read. In the reading activities, students needed to read 19 English academic articles that are closely related to their courses. A questionnaire was administered after the students finished reading the 19th article to determine their attitudes toward reading English medical education articles and the cognitive load involved in reading the 19th article. The results showed that students' overall perceptions of reading English medical education articles were positive. Most students felt that their ability to read English academic articles and related skills had improved. The mean scores for students' intrinsic and germane cognitive loads in reading the 19th article were 6.44 ± 1.81 and 6.92 ± 2.05, respectively. The mean score for the extraneous cognitive load was 2.31 ± 2.63. In conclusion, the cognitive load theory can serve as the basis for an effective strategy to guide English medical education article reading activities among undergraduates in China. Meanwhile, students' attitudes toward the reading activities were favorable, and they read the latest article within an acceptable cognitive load.NEW & NOTEWORTHY Many nonnative English-speaking undergraduates have a fear of reading English academic articles. This study was performed to explore whether cognitive load theory can be a useful guiding strategy to promote English article reading among Chinese medical undergraduates. The results showed that cognitive load theory can serve as the basis for an effective strategy to guide English medical education article reading activities among undergraduates in China, and students' attitudes toward the reading activities were favorable.

What makes an article a must read in medical education?

BACKGROUND: The dissemination of published scholarship is intended to bring new evidence and ideas to a wide audience. However, the increasing number of articles makes it challenging to determine where to focus one's attention. This study describes factors that may influence decisions to read and recommend a medical education article. METHODS: Authors analyzed data collected from March 2021 through September 2022 during a monthly process to identify "Must Read" articles in medical education. An international team of health sciences educators, learners, and researchers voted on titles and abstracts to advance articles to full text review. Full texts were rated using five criteria: relevance, methodology, readability, originality, and whether it addressed a critical issue in medical education. At an end-of-month meeting, 3-4 articles were chosen by consensus as "Must Read" articles. Analyses were used to explore the associations of article characteristics and ratings with Must Read selection. RESULTS: Over a period of 19 months, 7487 articles from 856 journals were screened, 207 (2.8%) full texts were evaluated, and 62 (0.8%) were chosen as Must Reads. During screening, 3976 articles (53.1%) received no votes. BMC Medical Education had the largest number of articles at screening (n = 1181, 15.8%). Academic Medicine had the largest number as Must Reads (n = 22, 35.5%). In logistic regressions adjusting for the effect of individual reviewers, all rating criteria were independently associated with selection as a Must Read (p < 0.05), with methodology (OR 1.44 (95%CI = 1.23-1.69) and relevance (OR 1.43 (95%CI = 1.20-1.70)) having the highest odds ratios. CONCLUSIONS: Over half of the published medical education articles did not appeal to a diverse group of potential readers; this represents a missed opportunity to make an impact and potentially wasted effort. Our findings suggest opportunities to enhance value in the production and dissemination of medical education scholarship.