bluuebunny/crossref_metadata_2025 huggingface dataset:
Benchmarking Mendelian Randomization methods for causal inference using genome-wide association study summary statistics
Authors: Hu Xianghong , Cai Mingxuan , Xiao Jiashun , Wan Xiaomeng , Wang Zhiwei , Zhao Hongyu , Yang Can
Published: January 2024

Mendelian Randomization (MR), which utilizes genetic variants as instrumental variables (IVs), has gained popularity as a method for causal inference between phenotypes using genetic data. While efforts have been made to relax IV assumptions and develop new methods for causal inference in the presence of invalid IVs due to confounding, the reliability of MR methods in real-world applications remains uncertain. To bridge this gap, we conducted a benchmark study evaluating 15 MR methods using real-world genetic datasets. Our study focused on three crucial aspects: type I error control in the presence of various confounding scenarios (e.g., population stratification, pleiotropy, and assortative mating), the accuracy of causal effect estimates, replicability and power. By comprehensively evaluating the performance of compared methods over one thousand pairs of exposure-outcome traits, our study not only provides valuable insights into the performance and limitations of the compared methods but also offers practical guidance for researchers to choose appropriate MR methods for causal inference.
Human bronchopulmonary disposition and plasma pharmacokinetics of oral bemnifosbuvir (AT-527), an experimental guanosine nucleotide prodrug for COVID-19
Authors: Zhou Xiao-Jian , Horga Arantxa , Puri Adeep , Winchester Lee , Montrond Maureen , Pietropaolo Keith , Belanger Bruce , Fletcher Courtney V. , Hammond Janet
Published: January 2024

Bemnifosbuvir (BEM, AT-527) is a novel oral guanosine nucleotide antiviral drug for the treatment of patients with COVID-19. Direct assessment of drug disposition in the lungs, via bronchoalveolar lavage, is necessary to ensure antiviral drug levels at the primary site of SARS-CoV-2 infection are achieved. We conducted a Phase 1 study in healthy subjects to assess the bronchopulmonary pharmacokinetics, safety, and tolerability of repeated doses of BEM. A total of 24 subjects were assigned to receive twice-daily (BID) BEM at doses of 275, 550, or 825 mg for up to 3.5 days. AT-511, the free base of BEM, was largely eliminated from the plasma within 6 h post dose in all dosing groups. Antiviral drug levels of BEM were consistently achieved in the lungs with BEM 550 mg BID. The mean level of the guanosine nucleoside metabolite AT-273, the surrogate of the active triphosphate metabolite of the drug, measured in the epithelial lining fluid of the lungs was 0.62 µM at 4–5 h post dose. This exceeded the targetin vitro90% effective concentration (EC90) of 0.5 µM for antiviral drug exposure against SARS-CoV-2 replication in human airway epithelial cells. BEM was well tolerated across all doses tested, and most treatment-emergent adverse events reported were mild in severity and resolved. The favorable pharmacokinetics and safety profile of BEM demonstrates its potential as an oral antiviral treatment for COVID-19, with 550 mg BEM BID currently under further clinical evaluation in patients with COVID-19.
Substance Use and Overdose in Pennsylvania Libraries, 2019
Authors: Feuerstein-Simon Rachel , Lowenstein Margaret , Szapary Claire , Torres Omaya , Dolan Abby , Jalloh Aminata , Meisel Zachary F. , Cannuscio Carolyn C.
Published: January 2024

This study examines the implementation of naloxone distribution initiatives in Pennsylvania public libraries following a nationwide program offering free Narcan. We conducted a cross-sectional telephone survey with a random sample of Pennsylvania public libraries (n=352). Overall, nearly one-quarter of respondents reported stocking naloxone (23.9%), and over one in ten libraries reported a previous on-site overdose (11.9%). Nearly 30% of respondents had received naloxone training. Significant predictors of on-site overdoses included the library’s county urbanization status and higher county-level overdose mortality rates. Among libraries that stocked naloxone, 73% obtained the medication from local health departments or community-based organizations. This study underscores the role of public libraries in opioid overdose crisis response and the need for tailored strategies to enhance naloxone accessibility, especially in high-risk urban areas. Collaboration between libraries, public health entities, and pharmaceutical companies is crucial to amplify naloxone distribution efforts and address the escalating opioid overdose crisis.
Detecting Goals of Care Conversations in Clinical Notes with Active Learning
Authors: Weissenbacher Davy , Courtright Katherine , Rawal Siddharth , Crane-Droesch Andrew , O’Connor Karen , Kuhl Nicholas , Merlino Corinne , Foxwell Anessa , Haines Lindsay , Puhl Joseph , Gonzalez-Hernandez Graciela
Published: January 2024

Objective

Goals Of Care (GOC) discussions are an increasingly used quality metric in serious illness care and research. Wide variation in documentation practices within the Electronic Health Record (EHR) presents challenges for reliable measurement of GOC discussions. Novel natural language processing approaches are needed to capture GOC discussions documented in real-world samples of seriously ill hospitalized patients’ EHR notes, a corpus with a very low event prevalence.

Methods

To automatically detect utterances documenting GOC discussions outside of dedicated GOC note types, we proposed an ensemble of classifiers aggregating the predictions of rule-based, feature-based, and three transformers-based classifiers. We trained our classifier on 600 manually annotated EHR notes among patients with serious illnesses. Our corpus exhibited an extremely imbalanced ratio between utterances discussing GOC and utterances that do not. This ratio challenges standard supervision methods to train a classifier. Therefore, we trained our classifier with active learning.

Results

Using active learning, we reduced the annotation cost to fine-tune our ensemble by 70% while improving its performance in our test set of 176 EHR notes, with 0.557 F1-score for utterance classification and 0.629 for note classification.

Conclusion

When classifying notes, with a true positive rate of 72% (13/18) and false positive rate of 8% (13/158), our performance may be sufficient for deploying our classifier in the EHR to facilitate point-of-care access to GOC conversations documented outside of dedicated notes types, without overburdening clinicians with false positives. Improvements are needed before using it to enrich trial populations or as an outcome measure.
Trends in types of revision for prosthetic joint infection and risk of a second revision from 1995 to 2022: A descriptive cohort study from the Danish Hip Arthroplasty Registry
Authors: Lundsgaard Daniel , Abedi Armita Armina , Overgaard Søren , Laigaard Jens Holm
Published: January 2024

This protocol outlines a register-based cohort study utilizing Danish Hip Arthroplasty Register data from 1995 to 2022. Focusing on adult patients undergoing primary total hip arthroplasty (THA), the study categorizes revisions, particularly periprosthetic joint infections (PJI), into Debridement, antibiotics, and implant retention (DAIR), one-stage, and two-stage approaches. Annual revision numbers and the risk of a second revision after each primary type will be analyzed. The study’s strengths lie in its comprehensive examination of various PJI revision methods and an extended recording period, leveraging the DHR’s high completeness rates. While acknowledging potential uncertainties, the study offers valuable insights into THA revision trends, aiding in clinical practice optimization and improving patient outcomes.

Study registration

Privacy identifier p-2023-14990

Protocol uploaded to OSF: Not yet uploaded

Budget

The costs of the study are limited to the salary of the investigators, which is paid by the orthopedic department.
Shayona@SMM4H’23: COVID-19 Self diagnosis classification using BERT and LightGBM models
Authors: Chavda Rushi , Makwana Darshan , Patel Vraj , Shukla Anupam
Published: January 2024

This paper describes approaches and results for shared Task 1 and 4 of SMMH4-23 by Team Shayona. Shared Task-1 was binary classification of english tweets self-reporting a COVID-19 diagnosis, and Shared Task-4 was Binary classification of English Reddit posts self-reporting a social anxiety disorder diagnosis. Our team has achieved the highest f1-score 0.94 in Task-1 among all participants. We have leveraged the Transformer model (BERT) in combination with the LightGBM model for both tasks.
Safety and effectiveness of SGLT2-inhibitors in people with type 2 diabetes over 70: UK population-based study using an Instrumental Variable approach
Authors: Güdemann Laura Maria , Young Katie G. , Thomas Nicholas J. M. , Hopkins Rhian , Challen Robert , Jones Angus G. , Hattersley Andrew T. , Pearson Ewan R , Shields Beverley M. , Bowden Jack , Dennis John M. , McGovern Andrew P. ,   the Mastermind consortium
Published: January 2024

Objective

Older adults are underrepresented in trials, meaning the benefits and risks of glucose lowering agents in this age group are unclear. We applied causal analysis to assess the safety and effectiveness of SGLT2-inhibitors in people with type 2 diabetes (T2D) over 70.

Research Design and Methods

Hospital-linked UK primary care data (Clinical Practice Research Datalink, 2013-2020) were used to compare adverse events and effectiveness in individuals initiating SGLT2-inhibitors compared to DPP4-inhibitors. Analysis was age-stratified: <70 years (SGLT2-inhibitors n=66810, DPP4-inhibitors n=76172), ≥70 years (SGLT2-inhibitors n=10419, DPP4-inhibitors n=33434). Outcomes were assessed using the Instrumental Variable causal inference method and prescriber preference as instrument.

Results

Risk of DKA was increased with SGLT2-inhibitors in those aged ≥70 (Incidence risk ratio compared to DPP4i: 3.82 [95%CI 1.12,13.03]), but not in those <70 (1.12 [95%CI 0.41,3.04]). However incidence rates with SGLT2-inhibitors in those ≥70 was low (29.6 [95%CI 29.5,29.7]) per 10000 person-years. SGLT2-inhibitors were associated with similarly increased risk of genital infection in both age groups (IRR <70 2.27 [2.03,2.53]; ≥70 2.16 [1.77,2.63]). There was no evidence of an increased risk of volume depletion, poor micturition control, urinary frequency, falls or amputation with SGLT2-inhibitors in either age group. In those ≥70, HbA1c reduction was similar with SGLT2-inhibitors and DPP4-inhibitors (−0.3 mmol/mol [−1.6,1.1], −0.02% [0.1,0.1]), but in those <70 SGLT2-inhibitors were more effective (−4 mmol/mol [4.8,−3.1], −0.4% [−0.4,−0.3]).

Conclusions

Causal analysis suggests SGLT2-inhibitors are effective in adults ≥70, but increase risk for genital infections and DKA. Our study extends RCT evidence to older adults with T2D.

Article Highlights

Why did we undertake this study?

–

Current guidelines for type 2 diabetes recommend an individualised approach to treatment, but evidence for older adults is limited.

What is the specific question(s) we wanted to answer?

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To assess the safety and effectiveness of SGLT2-inhibitors in older adults by applying a causal inference framework to address potential confounding bias in observational data.

What did we find?

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SGLT2-inhibitors are effective in reducing HbA1c and weight and generally safe for older adults. Adverse events in this older group include genital infections and a small increase in DKA.

What are the implications of our findings?

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SGLT2-inhibitors are effective and safe for older adults, but clinicians should be aware of the risks for genital infections and DKA.
Time to publication in medical education journals: An analysis of publication timelines during COVID-19 (2019-2022)
Authors: Maggio L.A. , Costello J.A. , Brown K. R. , Artino A.R. , Durning S.J , Ma T.
Published: January 2024

Introduction

COVID-19 changed scholarly publishing. Yet, its impact on medical education publishing is unstudied. Because journal articles and their corresponding publication timelines can influence academic success, the field needs updated publication timelines to set evidence-based expectations for academic productivity. This study attempts to answer the following research questions: did publication timelines significantly change around the time of COVID-19 and, if so, how?

Methods

We conducted a bibliometric study; our sample included articles published between January 2018, and December 2022, that appeared in the Medical Education Journals List-24 (MEJ-24). We clustered articles into three time-based groups (pre-COVID, COVID-overlap, and COVID-endemic), and two subject-based groups (about COVID-19 and not about COVID-19). We downloaded each article’s metadata from the National Library of Medicine and analyzed data using descriptive statistics, analysis of variance, and post-hoc tests to compare mean time differences across groups.

Results

Overall, time to publish averaged 300.8 days (SD= 200.8). One-way between-groups ANOVA showed significant differences between the three time-based groupsF(2, 7473) = 2150.7,p<.001. The post-hoc comparisons indicated that COVID-overlap articles took significantly longer (n= 1470,M= 539;SD= 210.6) as compared to pre-COVID (n= 1281;M= 302;SD= 172.5) and COVID-endemic articles (n= 4725;M= 226;SD= 136.5). Notably, COVID-endemic articles were published in significantly less time than pre-pandemic articles,p< .001.

Discussion

Longer publication time was most pronounced for COVID-overlap articles. Publication timelines for COVID-endemic articles have shortened. Future research should explore how the shift in publication timelines has shaped medical education scholarship.
Status of physical activity and its associated factors among the secondary school teachers in Pokhara, Nepal
Authors: Ranabhat Kamal , Shahi Shubhadra , Shrestha Kiran , Kunwar Ramesh , Rana Himalaya , Choulagai Bishnu Prasad
Published: January 2024

Cardiovascular diseases are the leading cause of all the cause of death globally and physical activity is the proven cost effective modifiable behavior risk factors for the prevention of cardiovascular diseases. The objective of the study was to assess the status of the physical activity and its determining factors among the school teachers of Pokhara Nepal. We used quantitative approach for data collection among 406 samples that were drawn using probability proportion to enrollment size. The international questionnaire on physical activity (IPAQ)-long form was used for data collection. SPSS V.27 was used for univariate and bivariate analysis.

The study have found the 13.2 percent of prevalence of physical inactivity. Sex, ethnicity, educational qualification, availability of walking environment around home, mean screen time per day were found having statistical association with the outcome variable. The prevalence of low physical activity was found 13.2 percent. Majority of the study participants achieved WHO global recommendation on physical activity. Domestic and garden work contributed most in domain specific physical activity among the participants.
Prevalence of Hypertension, awareness, treatment, and blood pressure control in Sierra Leone: A systematic review and meta-analysis
Authors: Koroma Theresa Ruba , Russell James Baligeh Walter , Samura Sallieu Kabay , Coker Joshua M , Conteh Sorie , Yendewa George A. , Lisk Durodami Radcliffe
Published: January 2024

Background

In recent years, the prevalence of Hypertension (HTN) has increased in sub-Saharan countries. However, reports on the prevalence of HTN in Sierra Leone are limited. Therefore, we conducted a systematic review and meta-analysis to assess the overall estimates of the prevalence of HTN in Sierra Leone.

Method

A systematic search of electronic databases (PubMed, Embase, African Journal Online and Google Scholar) was conducted by three independent investigators using keywords such as “hypertension”, “prevalence”, “blood pressure”, and “Sierra Leone”. A random-effects model was used to estimate the prevalence across studies. Heterogeneity among studies was assessed using the Cochran Q test and I2statistic, and publication bias was assessed using funnel plots and the Egger test.

Results

We pooled the data from 15 studies (n=14,707) that met the inclusion criteria. The overall prevalence of HTN in Sierra Leone was 27.64% [95% CI = 27.45, 27.82], with significant heterogeneity observed among studies (I2=99.82%, p-value < 0.001). The pooled prevalence of Hypertension among males was higher than that among females (25.11% [95% CI = 24.90-25.32], I2=99.79%, p-value < 0.001) and 24.11% [95% CI = 23.92,24.31, I2=99.67%, p-value < 0.001]). The prevalence of HTN among urban residents (29.76%) was almost twice that among their rural counterparts (15.77%). Of those with HTN, 37.21% were aware of their illness, 12.87% received treatment, and only 29.73% had blood pressure control.

Conclusion

More than 1 in 4 adults aged ≥ 15 years are living with HTN in Sierra Leone, with a low awareness rate and even lower treatment and control rates. Our findings highlighted the need for robust and comprehensive hypertension prevention, treatment and control policies.
Predictors of unsuccessful tuberculosis treatment outcomes in Brazil: an analysis of 259,484 patient records
Authors: Ryuk Do Kyung , Pelissari Daniele M , Alves Kleydson , Oliveira Patricia Bartholomay , Castro Marcia C , Cohen Ted , Sanchez Mauro , Menzies Nicolas A
Published: January 2024

Introduction

Tuberculosis (TB) causes over 1 million deaths annually. Providing effective treatment is a key strategy for reducing TB deaths. In this study, we identified factors associated with unsuccessful treatment outcomes among individuals treated for TB in Brazil.

Methods

We obtained data on individuals treated for TB between 2015 and 2018 from Brazil’s National Disease Notification System (SINAN). We excluded patients with a history of prior TB disease or with diagnosed TB drug resistance. We extracted information on patient-level factors potentially associated with successful treatment, including demographic and social factors, comorbid health conditions, health-related behaviors, health system level at which care was provided, use of directly observed therapy (DOT), and clinical examination results. We categorized treatment outcomes as successful (cure, completed) or unsuccessful (death, regimen failure, loss to follow-up). We fit multivariate logistic regression models to identify factors associated with unsuccessful treatment outcome.

Results

Among 259,484 individuals treated for drug susceptible TB, 19.7% experienced an unsuccessful treatment outcome (death during treatment 7.8%, regimen failure 0.1%, loss to follow-up 11.9%). The odds of unsuccessful outcome were higher with older age (adjusted odds ratio (aOR) 2.90 [95% confidence interval: 2.62–3.21] for 85-100-year-olds vs. 25-34-year-olds), male sex (aOR 1.28 [1.25– 1.32], vs. female sex), Black race (aOR 1.23 [1.19–1.28], vs. White race), no education (aOR 2.03 [1.91– 2.17], vs. complete high school education), HIV infection (aOR 2.72 [2.63–2.81], vs. no HIV infection), illicit drug use (aOR 1.95 [1.88–2.01], vs. no illicit drug use), alcohol consumption (aOR 1.46 [1.41– 1.50], vs. no alcohol consumption), smoking (aOR 1.20 [1.16–1.23], vs. non-smoking), homelessness (aOR 3.12 [2.95–3.31], vs. no homelessness), and immigrant status (aOR 1.27 [1.11–1.45], vs. non-immigrants). Treatment was more likely to be unsuccessful for individuals treated in tertiary care (aOR 2.20 [2.14–2.27], vs. primary care), and for patients not receiving DOT (aOR 2.35 [2.29–2.41], vs. receiving DOT).

Conclusion

The risk of unsuccessful TB treatment varied systematically according to individual and service-related factors. Concentrating clinical attention on individuals with a high risk of poor treatment outcomes could improve the overall effectiveness of TB treatment in Brazil.
A Systematic Review of the Quantitative markers of speech and language of the Frontotemporal Degeneration Spectrum and their potential for cross-linguistic implementation
Authors: Coppieters Rosie , Bouzigues Arabella , Jiskoot Lize , Montembeault Maxime , Tee Boon Lead ,   Genetic Frontotemporal dementia Initiative (GENFI), Rohrer Jonathan D. , Bruffaerts Rose
Published: January 2024

Frontotemporal dementia (FTD) is a neurodegenerative disease spectrum with an urgent need for reliable biomarkers for early diagnosis and monitoring. Speech and language changes occur in the early stages of FTD and offer a potential non-invasive, early, and accessible diagnostic tool. The use of speech and language markers in this disease spectrum is limited by the fact that most studies investigate English-speaking patients. This systematic review examines the literature on psychoacoustic and linguistic features of speech that occur across the FTD spectrum across as many different languages as possible. 76 papers were identified that investigate psychoacoustic and linguistic markers in discursive speech. 75% of these papers studied English-speaking patients. The most generalisable features found across different languages, are speech rate, articulation rate, pause frequency, total pause duration, noun: verb ratio, and total number of nouns. While there are clear interlinguistic differences across patient groups, the results show promise for implementation of cross-linguistic markers of speech and language across the FTD spectrum, particularly for psychoacoustic features.
Machine learning enabled prediction of digital biomarkers from whole slide histopathology images
Authors: McCaw Zachary R , Shcherbina Anna , Shah Yajas , Huang Davey , Elliott Serra , Szabo Peter M , Dulken Benjamin , Holland Sacha , Tagari Philip , Light David , Koller Daphne , Probert Christopher
Published: January 2024

Current predictive biomarkers generally leverage technologies such as immunohis-tochemistry or genetic analysis, which may require specialized equipment, be time-intensive to deploy, or incur human error. In this paper, we present an alternative approach for the development and deployment of a class of predictive biomarkers, leveraging deep learning on digital images of hematoxylin and eosin (H&E)-stained biopsy samples to simultaneously predict a range of molecular factors that are relevant to treatment selection and response. Our framework begins with the training of a pan-solid tumor H&E foundation model, which can generate a universal featurization of H&E-stained tissue images. This featurization becomes the input to machine learning models that perform multi-target, pan-cancer imputation. For a set of 352 drug targets, we show the ability to predict with high accuracy: copy number amplifications, target RNA expression, and an RNA-derived “amplification signature” that captures the transcriptional consequences of an amplification event. We facilitate exploratory analyses by making broad predictions initially. Having identified the subset of biomarkers relevant to a patient population of interest, we develop specialized machine learning models, built on the same foundational featurization, which achieve even higher performance for key biomarkers in tumor types of interest. Moreover, our models are robust, generalizing with minimal loss of performance across different patient populations. By generating imputations from tile-level featurizations, we enable spatial overlays of molecular annotations on top of whole-slide images. These annotation maps provide a clear means of interpreting the histological correlates of our model’s predictions, and align with features identified by expert pathologist review. Overall, our work demonstrates a flexible and scalable framework for imputing molecular measurements from H&E, providing a generalizable approach to the development and deployment of predictive biomarkers for targeted therapeutics in cancer.
Design and development of a flipped classroom-based online software course including online examination for medical statistics
Authors: Muche Rainer , Allgöwer Andreas , Braisch Ulrike , Meule Marianne , Mayer Benjamin
Published: January 2024

Teaching medical statistics for students of human medicine should include both theoretical content as well as its implementation in practice using statistical software. The training period with a software may be time-consuming individually, so there is a risk that imparting methodological skills comes up short in such courses. The flipped classroom concept aims at students to familiarize themselves with both the statistical software and the theoretical content in an individual learning phase prior to the course. Then, within an attendance course deepening both aspects under the lecturer’s supervision is possible. Availability of the software as well as a variety of material to prepare the course are essential presumptions for the flipped classroom to be successful. We present the concept and implementation of an online flipped classroom course using the software SAS Studio. Students used their own devices (laptops or tablets) during the self-learning and examination phases, respectively. The pure online implementation in the flipped classroom setting enabled to contribute to an equalisation of the study plan. Moreover, even more students had the opportunity to participate in this practically oriented course in medical statistics. Initial evaluation results demonstrated that the course is well-accepted among students, while the students’ performance level was similar when compared to a non-flipped teaching approach.
Widely accessible prognostication using medical history for fetal growth restriction and small for gestational age in nationwide insured women
Authors: Sufriyana Herdiantri , Amani Fariska Zata , Al Hajiri Aufar Zimamuz Zaman , Wu Yu-Wei , Su Emily Chia-Yu
Published: January 2024

Objectives

Prevention of fetal growth restriction/small for gestational age is adequate if screening is accurate. Ultrasound and biomarkers can achieve this goal; however, both are often inaccessible. This study aimed to develop, validate, and deploy a prognostic prediction model for screening fetal growth restriction/small for gestational age using only medical history.

Methods

From a nationwide health insurance database (n=1,697,452), we retrospectively selected visits of 12-to-55-year-old females to 22,024 healthcare providers of primary, secondary, and tertiary care. This study used machine learning (including deep learning) to develop prediction models using 54 medical-history predictors. After evaluating model calibration, clinical utility, and explainability, we selected the best by discrimination ability. We also externally validated and compared the models with those from previous studies, which were rigorously selected by a systematic review of Pubmed, Scopus, and Web of Science.

Results

We selected 169,746 subjects with 507,319 visits for predictive modeling. The best prediction model was a deep-insight visible neural network. It had an area under the receiver operating characteristics curve of 0.742 (95% confidence interval 0.734 to 0.750) and a sensitivity of 49.09% (95% confidence interval 47.60% to 50.58% using a threshold with 95% specificity). The model was competitive against the previous models in a systematic review of 30 eligible studies of 381 records, including those using either ultrasound or biomarker measurements. We deployed a web application to apply the model.

Conclusions

Our model used only medical history to improve accessibility for fetal growth restriction/small for gestational age screening. However, future studies are warranted to evaluate if this model’s usage impacts patient outcomes.
Occupational hazards and risks among the women in fisher communities in Cox’s Bazar and Chattogram
Authors: Halder Charls Erik , Das Partha Pratim , Rahman S.M. Tareq , Bhoumick Liton Chandra , Tassdik Hamim , Hasan Md Abeed , Mithun Sourav Nath
Published: January 2024

Background

Women in the fisher communities in coastal regions of Bangladesh are engaged in a wide range of fishery activities including fish sorting, grading, cutting, dry fish processing, transporting and selling. However, there is limited evidence available on the occupational hazards and risks experienced by them.

Method

The study was conducted among fishing colonies in Cox’s Bazar and Chattogram districts in Bangladesh. This was a cross-sectional study comprised of both qualitative and quantitative approaches. Data were primarily collected through eight focus group discussions (FGD) and a quantitative survey of a sample of 207 women working in fisheries sector.

Findings

The study found a high occurrence of occupational hazards, health risks and disease conditions and limited availability of preventive measures among the women in the fisher communities in the coastal Bangladesh. Occupational hazards include physical safety hazards, like slippery surface, fish cutting instruments, fish sting or bite and contact with fishes; physical hazards, like prolonged sun exposure and noise; chemical hazards like pesticides, salt and salt water; ergonomic hazards, like prolonged sitting or standing in uncomfortable posture and heavy weight lifting; and biological hazards, like inadequate provision of sanitary latrine or hand washing soap at workplace. The study also found occupational risks resulting from the hazards including injuries (87.44%), musculoskeletal conditions (69.08%), skin diseases/conditions (56.52%), eye complaints (33.82%), severe respiratory distress (24.15%) and high incidence of self-reported communicable diseases. Majority of the women did not use personal protection equipment at their workplace (78.26%) and have a first aid kit at their workplace (93.72%).

Conclusion

This study highlights the critical occupational health and safety challenges faced by the women in the fisheries sector. A comprehensive multisectoral strategy needs to be undertaken to mitigate the occupational hazards and prevent associated diseases among the women in fisher communities promoting their health and wellbeing.
Immersive Virtual Reality Games in Neuromotor Rehabilitation with Brain-Computer Interfaces: A Scoping Review
Authors: Gaafer Mohamed N. , Ahmed Zeyad M. , El-Husseiny Abdullah S. , Youssef Aliaa Rehan , Al-Kabbany Ahmed
Published: January 2024

The use of immersive virtual reality (VR) is gaining traction among the scientific community as it opens great opportunities in the field of rehabilitation. By making use of video game mechanics and Brain computer interface (BCI) that is based on electroencephalography (EEG) signals, patients undergoing neurorehabilitation can be more engaged in rehabilitation training. This paper reviews the available literature which uses BCI and VR in game rehabilitation and analyses the gaming elements and brain machine interfaces (BMI) used in each study. Four databases (IEEE Xplore, PubMed, Web of Science, Scopus) from inception until October 2023 were queried using a comprehensive searching strategy and then screened by two independent reviewers. A total of 18 articles were found eligible for qualitative synthesis. These are the main findings: (1) A diverse participant demographic spanned age and health conditions; (2) Oculus Rift has gained prominence as a VR device, replacing older CAVE systems; (3) All surveyed studies unanimously relied on the Motor Imagery (MI) paradigm, reflecting its importance in neuro motor rehabilitation and neuroplasticity; (4) Rehabilitation games displayed varied characteristics, emphasizing scoring, embodiment, and customization. Notably, the lack of gamification elements in some games suggests an area for potential enhancement and future research.
Angiographic Tool to Detect Pulmonary Arteriovenous Malformations in Single Ventricle Physiology
Authors: Spurgin Stephen B , Arar Yousef M , Zellers Thomas M , Wang Jijia , Madsen Nicolas L , Veeram Reddy Surendranath R , Cleaver Ondine , Divekar Abhay A
Published: January 2024

Background

Individuals with single ventricle physiology who are palliated with superior cavopulmonary anastomosis (Glenn surgery) may develop pulmonary arteriovenous malformations (PAVMs). The traditional tools for PAVM diagnosis are often of limited diagnostic utility in this patient population. We sought to measure the pulmonary capillary transit time (PCTT) to determine its value as a tool to identify PAVMs in patients with single ventricle physiology.

Methods

We defined the angiographic PCTT as the number of cardiac cycles required for transit of contrast from the distal pulmonary arteries to the pulmonary veins. Patients were retrospectively recruited from a single quaternary North American pediatric center, and angiographic and clinical data was reviewed. PCTT was calculated in 20 control patients and compared to 20 single ventricle patients at the pre-Glenn, Glenn, and Fontan surgical stages (which were compared with a linear-mixed model). Correlation (Pearson) between PCTT and hemodynamic and injection parameters was assessed using 84 Glenn angiograms. Five independent observers calculated PCTT to measure reproducibility (intra-class correlation coefficient).

Results

Mean PCTT was 3.3 cardiac cycles in the control population, and 3.5, 2.4, and 3.5 in the pre-Glenn, Glenn, and Fontan stages, respectively. PCTT in the Glenn population did not correlate with injection conditions. Intraclass correlation coefficient was 0.87.

Conclusions

Pulmonary angiography can be used to calculate the pulmonary capillary transit time, which is reproducible between observers. PCTT accelerates in the Glenn stage, correlating with absence of direct hepatopulmonary venous flow.
Immunological imprinting shapes the specificity of human antibody responses against SARS-CoV-2 variants
Authors: Johnston Timothy S. , Li Shuk Hang , Painter Mark M. , Atkinson Reilly K. , Douek Naomi R. , Reeg David B. , Douek Daniel C. , Wherry E. John , Hensley Scott E.
Published: January 2024

The spike glycoprotein of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) continues to accumulate substitutions, leading to breakthrough infections of vaccinated individuals and prompting the development of updated booster vaccines. Here, we determined the specificity and functionality of antibody and B cell responses following exposure to BA.5 and XBB variants in individuals who received ancestral SARS-CoV-2 mRNA vaccines. BA.5 exposures elicited antibody responses that primarily targeted epitopes conserved between the BA.5 and ancestral spike, with poor reactivity to the XBB.1.5 variant. XBB exposures also elicited antibody responses that targeted epitopes conserved between the XBB.1.5 and ancestral spike. However, unlike BA.5, a single XBB exposure elicited low levels of XBB.1.5-specific antibodies and B cells in some individuals. Pre-existing cross-reactive B cells and antibodies were correlated with stronger overall responses to XBB but weaker XBB-specific responses, suggesting that baseline immunity influences the activation of variant-specific SARS-CoV-2 responses.

Highlights

Variant breakthrough infections boost ancestral cross-reactive antibodies and B cells

First and second BA.5 exposures fail to elicit variant-specific antibodies and B cells

XBB infections and monovalent vaccinations elicit XBB.1.5-specific responses in some individuals

XBB.1.5-specific responses correlate with low levels of pre-existing humoral immunity
Climate warming is expanding dengue burden in the Americas and Asia
Authors: Childs Marissa L. , Lyberger Kelsey , Harris Mallory , Burke Marshall , Mordecai Erin A.
Published: January 2024

Climate change is expected to pose significant threats to public health, particularly including vector-borne diseases. Despite dramatic recent increases in the burden of dengue that many anecdotally connect with climate change, the effect of past and future anthropogenic climate change on dengue remains poorly quantified. To assess the link between climate warming and dengue we assembled a dataset covering 21 countries in Asia and the Americas, and found a nonlinear relationship between temperature and dengue incidence with the largest impact of warming at lower temperatures (below about 20°C), peak incidence at 27.8°C, and subsequent declines at higher temperatures. Using this inferred temperature response, we estimate that historical climate change has increased dengue incidence by 18% (11 - 27%) on average across our study countries, and that future warming could further increase it by 49% (16 - 136%) to 76% (27 - 239%) by mid-century for low or high emissions scenarios, respectively, with some cooler regions projected to see dengue doubling due to warming and other currently hot regions seeing no impact or even small declines. Under the highest emissions scenario, we estimate that 262 million people are currently living in places in these 21 countries where dengue incidence is expected to more than double due to climate change by mid-century. These insights highlight the major impacts of anthropogenic warming on dengue burden across most of its endemic range, providing a foundation for public health planning and the development of strategies to mitigate future risks due to climate change.
The effect of post-acute rehabilitation setting on 90-day mobility after stroke: A difference-in-difference analysis
Authors: French Margaret A. , Hayes Heather , Johnson Joshua K. , Young Daniel L. , Roemmich Ryan T. , Raghavan Preeti
Published: January 2024

Background

After discharged from the hospital for acute stroke, individuals typically receive rehabilitation in one of three settings: inpatient rehabilitation facilities (IRFs), skilled nursing facilities (SNFs), or home with community services (i.e., home health or outpatient clinics). The initial setting of post-acute care (i.e., discharge location) is related to mortality and hospital readmission; however, the impact of this setting on the change in functional mobility at 90-days after discharge is still poorly understood. The purpose of this work was to examine the impact of discharge location on the change in functional mobility between hospital discharge and 90-days post-discharge.

Methods

In this retrospective cohort study, we used the electronic health record to identify individuals admitted to Johns Hopkins Medicine with an acute stroke and who had measurements of mobility [Activity Measure for Post Acute Care Basic Mobility (AM-PAC BM)] at discharge from the acute hospital and 90-days post-discharge. Individuals were grouped by discharge location (IRF=190 [40%], SNF=103 [22%], Home with community services=182 [(38%]). We compared the change in mobility from time of discharge to 90-days post-discharge in each group using a difference-in-differences analysis and controlling for demographics, clinical characteristics, and social determinants of health.

Results

We included 475 individuals (age 64.4 [14.8] years; female: 248 [52.2%]). After adjusting for covariates, individuals who were discharged to an IRF had a significantly greater improvement in AM-PAC BM from time of discharge to 90-days post-discharge compared to individuals discharged to a SNF or home with community services (β=-3.5 (1.4), p=0.01 and β=-8.2 (1.3), p=<0.001, respectively).

Conclusions

These findings suggest that the initial post-acute rehabilitation setting impacts the magnitude of functional recovery at 90-days after discharge from the acute hospital. These findings support the need for high-intensity rehabilitation and for policies that facilitate the delivery of high-intensity rehabilitation after stroke.
RFX6 at locus 6q22 confers metastasis and drug resistance in prostate cancer
Authors: Zhong Mengjie , Xu Wenjie , Tian Pan , Zhang Qin , Wang Zixian , Liang Limiao , Zhang Qixiang , Yang Yuehong , Lu Ying , Wei Gong-Hong
Published: January 2024

Genetic and nonmutational epigenetic alterations are cancer hallmark characteristics. However, the role of inherited cancer predisposition alleles in co-opting lineage factor epigenetic reprogramming and contributing to tumor progression remains elusive. Here the FinnGen cohort phenome-wide analysis, along with recent multiple genome-wide association studies, has consistently identified the rs339331-RFX6/6q22 locus associated with prostate cancer (PCa) risk across diverse populations. We uncover that rs339331 resides at a reprogrammed androgen receptor (AR) binding site in PCa tumors, with the T risk allele enhancing AR chromatin occupancy under androgen signaling. We establish that RFX6 is an AR-regulated gene, intricately linked with rs339331, exhibiting synergistic prognostic value for PCa recurrence and metastasis. Through comprehensivein vitroandin vivostudies, we establish the oncogenic functions of RFX6 in promoting PCa cell proliferation and metastasis. Mechanistically, RFX6 upregulates transcription factor HOXA10 that profoundly correlates with adverse PCa outcomes and is pivotal in RFX6-mediated PCa progression, facilitating the epithelial-mesenchymal transition (EMT) process and modulating the TGFβ/SMAD signaling axis. Clinically, HOXA10 elevation is associated with increased EMT scores, tumor advancement and PCa recurrence. Remarkably, reducing RFX6 expression restores responsiveness of enzalutamide-resistant PCa cells and tumors to treatment. Our study highlights an interplay of disrupted genetic and epigenetic mechanisms converging on prostate lineage AR signaling, resulting in abnormal expression of RFX6 conferring PCa pathogenesis and enzalutamide resistance.
RNA methyltransferase SPOUT1/CENP-32 links mitotic spindle organization with the neurodevelopmental disorder SpADMiSS
Authors: Dharmadhikari Avinash V. , Abad Maria Alba , Khan Sheraz , Maroofian Reza , Sands Tristan T. , Ullah Farid , Samejima Itaru , Wear Martin A. , Moore Kiara E. , Kondakova Elena , Mitina Natalia , Schaub Theres , Lee Grace K. , Umandap Christine H. , Berger Sara M. , Iglesias Alejandro D. , Popp Bernt , Jamra Rami Abou , Gabriel Heinz , Rentas Stefan , Rippert Alyssa L , Izumi Kosuke , Conlin Laura K. , Koboldt Daniel C. , Mosher Theresa Mihalic , Hickey Scott E. , Albert Dara V.F. , Norwood Haley , Lewanda Amy Feldman , Dai Hongzheng , Liu Pengfei , Mitani Tadahiro , Marafi Dana , Pehlivan Davut , Posey Jennifer E. , Lippa Natalie , Vena Natalie , Heinzen Erin L , Goldstein David B. , Mignot Cyril , de Sainte Agathe Jean-Madeleine , Al-Sannaa Nouriya Abbas , Zamani Mina , Sadeghian Saeid , Azizimalamiri Reza , Seifia Tahere , Zaki Maha S. , Abdel-Salam Ghada M.H. , Abdel-Hamid Mohamed , Alabdi Lama , Alkuraya Fowzan Sami , Dawoud Heba , Lofty Aya , Bauer Peter , Zifarelli Giovanni , Afzal Erum , Zafar Faisal , Efthymiou Stephanie , Gossett Daniel , Towne Meghan C. , Yeneabat Raey , Wontakal Sandeep N. , Aggarwal Vimla S. , Rosenfeld Jill A. , Tarabykin Victor , Ohta Shinya , Lupski James R. , Houlden Henry , Earnshaw William C. , Davis Erica E. , Jeyaprakash A. Arockia , Liao Jun
Published: January 2024

SPOUT1/CENP-32encodes a putative SPOUT RNA methyltransferase previously identified as a mitotic chromosome associated protein. SPOUT1/CENP-32 depletion leads to centrosome detachment from the spindle poles and chromosome misalignment. Aided by gene matching platforms, we identified 24 individuals with neurodevelopmental delays from 18 families with bi-allelic variants inSPOUT1/CENP-32detected by exome/genome sequencing. Zebrafishspout1/cenp-32mutants showed reduction in larval head size with concomitant apoptosis likely associated with altered cell cycle progression.In vivocomplementation assays in zebrafish indicated thatSPOUT1/CENP-32missense variants identified in humans are pathogenic. Crystal structure analysis of SPOUT1/CENP-32 revealed that most disease-associated missense variants mapped to the catalytic domain. Additionally, SPOUT1/CENP-32 recurrent missense variants had reduced methyltransferase activityin vitroand compromised centrosome tethering to the spindle poles in human cells. Thus,SPOUT1/CENP-32pathogenic variants cause an autosomal recessive neurodevelopmental disorder: SpADMiSS (SPOUT1Associated Development delay Microcephaly Seizures Short stature) underpinned by mitotic spindle organization defects and consequent chromosome segregation errors.
Generating complex explanations for artificial intelligence models: an application to clinical data on severe mental illness
Authors: Banerjee Soumya
Published: January 2024

We present an explainable artificial intelligence methodology for predicting mortality in patients. We combine clinical data from an electronic patient healthcare record system with factors relevant for severe mental illness and then apply machine learning.

The machine learning model is used to predict mortality in patients with severe mental illness.

Our methodology uses class-contrastive reasoning. We show how machine learning scientists can use class-contrastive reasoning to generate complex explanations that explain machine model predictions and the data.

An example of a complex class-contrastive explanation is the following: “ The patient is predicted to have a low probability of death because the patient has self-harmed before, and was at some point on medications such as first-generation and second-generation antipsychotics. There are 11 other patients with these characteristics. If the patient did not have these characteristics, the prediction would be different. ”

This can be used to generate new hypotheses which can be tested in follow-up studies.

Our technique can be employed to create intricate explanations from healthcare data and possibly other areas where explainability is important. We hope this will be a step towards explainable AI in personalized medicine.
Population clustering of structural brain aging and its association with brain development
Authors: Duan Haojing , Shi Runye , Kang Jujiao , Banaschewski Tobias , Bokde Arun L. W. , Büchel Christian , Desrivières Sylvane , Flor Herta , Grigis Antoine , Garavan Hugh , Gowland Penny A. , Heinz Andreas , Brühl Rüdiger , Martinot Jean-Luc , Martinot Marie-Laure Paillère , Artiges Eric , Nees Frauke , Papadopoulos Orfanos Dimitri , Poustka Luise , Hohmann Sarah , Holz Nathalie , Fröhner Juliane H. , Smolka Michael N. , Vaidya Nilakshi , Walter Henrik , Whelan Robert , Schumann Gunter , Lin Xiaolei , Feng Jianfeng ,   IMAGEN consortium
Published: January 2024

Structural brain aging has demonstrated strong inter-individual heterogeneity and mirroring patterns with brain development. However, due to the lack of large-scale longitudinal neuroimaging studies, most of the existing research focused on the cross-sectional changes of brain aging. In this investigation, we present a data-driven approach that incorporate both cross-sectional changes and longitudinal trajectories of structural brain aging and identified two brain aging patterns among 37,013 healthy participants from UK Biobank. Participants with accelerated brain aging also demonstrated accelerated biological aging, cognitive decline and increased genetic susceptibilities to major neuropsychiatric disorders. Further, by integrating longitudinal neuroimaging studies from a multi-center adolescent cohort, we validated the “last in, first out” mirroring hypothesis and identified brain regions with manifested mirroring patterns between brain aging and brain development. Genomic analyses revealed risk loci and genes contributing to accelerated brain aging and delayed brain development, providing molecular basis for elucidating the biological mechanisms underlying brain aging and related disorders.