bluuebunny/crossref_metadata_2025_split huggingface dataset:
Limited overlap between genetic effects on disease susceptibility and disease survival
Authors: Yang Zhiyu , Pajuste Fanny-Dhelia , Zguro Kristina , Cheng Yipeng , Kurant Danielle E. , Eoli Andrea , Wanner Julian , Jermy Bradley ,   FinnGen,   Estonian Biobank research team, Kanoni Stavroula , van Heel David A. ,   Genes & Health Research Team, Hayward Caroline , Marioni Riccardo E , McCartney Daniel L. , Renieri Alessandra , Furini Simone ,   Genomics England Research Consortium, Mägi Reedik , Gusev Alexander , Drineas Petros , Paschou Peristera , Heyne Henrike , Ripatti Samuli , Mars Nina , Ganna Andrea 
Published: October 2023

AbstractUnderstanding disease progression is of a high biological and clinical interest. Unlike disease susceptibility whose genetic basis has been abundantly studied, less is known about the genetics of disease progression and its overlap with disease susceptibility. Considering ten common diseases (N cases ranging from 17,152 to 99,666) across seven biobanks, we systematically compared the genetic architecture of susceptibility and progression, defined as disease-specific mortality. We identified only one locus significantly associated with disease-specific mortality and show that, at a similar sample size, more genome-wide significant loci can be identified in a GWAS of disease susceptibility. Variants that were significantly affecting disease susceptibility were weakly or not associated with disease-specific mortality. Moreover, susceptibility polygenic scores (PGSs) were weak predictor of disease-specific mortality while a PGS for general lifespan was significantly associated with disease-specific mortality for five out of ten diseases. We used theoretical derivation and simulation to propose plausible explanations for our empirical observations and account for potential index-event bias. Overall, our findings point to little similarity in genetic effects between disease susceptibility and disease-specific mortality and suggest that either larger sample sizes or different measures of progression are needed to identify the genetic underpinning of disease progression.
People who identify as trans, non-binary or gender diverse can experience inclusive, culturally sensitive physical therapy while attending a gender-affirming clinic: qualitative study
Authors: Aird Madelaine , Walters Julie L , Ker Alex , Ross Megan H 
Published: October 2023

ABSTRACTObjectiveTo explore physical therapy experiences and identify barriers and facilitators of access to physical therapy for people who identify as trans, non-binary, or gender diverse (TGD).MethodsA qualitative descriptive design was employed using semi-structured interviews conducted in New Zealand. Participants were individuals aged 12 years or older, who self-identified as TGD, and had accessed physical therapy at a New Zealand clinic that provided a gender-affirming service. Participants were recruited via email invitation to the clinic database. Interview data were analysed using reflexive thematic analysis.Demographics are reported descriptively.ResultsSeventeen individuals participated. Four themes identified during analysis. Barriers to and facilitators of care were identified at policy, environmental, clinic and therapist levels. All participants reported physical therapy experiences relating to one or more of the following themes:challenging cisnormativityat policy, environmental, clinic and therapist levels;safety and trustthroughout the clinical experience-including clinic credibility for being a safe provider, clinic displays of TGD-inclusivity, implementation of safe clinic processes, and respectful therapist interactions;inclusive experiencesin a clinic which provided affordable care and took active steps to understand and affirm TGD identities, and physical therapists with a high level of knowledge of TGD-specific health issues and a biopsychosocial approach to care; and sensitivity tobody discomfort or dysphoriatriggers.ConclusionsPeople who identify as TGD face challenges to accessing safe and culturally sensitive physical therapy. However, there are achievable areas for improvement at policy, environmental, clinic and physical therapist level to gain trust and engagement in care for the TGD-community.Impact StatementThis study provides nuanced exploration of TGD physical therapy experiences and identifies specific areas of improvement for TGD physical therapy care to provide clinicians and physical therapy clinics insights into the provision of safe and culturally sensitive physical therapy.
Availability of Essential Medicines During the COVID-19 Pandemic: A Qualitative Study Examining Experiences and Level of Preparedness in Kenya
Authors: Onyango Joseph Odhiambo , Ogira Dosila , Kokwaro Gilbert 
Published: October 2023

AbstractThis study investigated the impact of the COVID-19 pandemic on essential medicine availability in Kenya’s health system. Key informant interviews were conducted, and the data were analyzed using NVIVO software. Six themes emerged, aligning with the WHO health system building blocks. These themes provided insights into the experiences, challenges, and opportunities regarding essential medicine availability during the pandemic. The initial response involved reallocating resources, affecting the procurement of essential medicines at national and county levels. To enhance preparedness, investments are crucial in strengthening financial systems and policies, improving supply chain resilience, and promoting local production through regulatory enhancements. These strategies aim to build resilient health systems and self-reliance, particularly for countries transitioning from donor aid. The findings underscore the importance of effective preparedness to ensure the availability of essential medicines during emergencies like the COVID-19 pandemic
Cohort Profile: ReCoDID Consortium’s Harmonized Acute Febrile Illness Arbovirus Meta-Cohort
Authors: Gómez Gustavo , Hufstedler Heather , Montenegro Carlos , Roell Yannik , Lozano Anyela , Tami Adriana , Magalhaes Tereza , Marques Ernesto T.A. , Balmaseda Angel , Calvet Guilherme , Harris Eva , Brasil Patricia , Herrera Victor , Villar Luis , Maxwell Lauren , Jaenisch Thomas ,   ReCoDID Arbovirus harmonization study group
Published: October 2023

AbstractInfectious disease (ID) cohorts are key to advancing public health surveillance, public policies and pandemic responses. Unfortunately, ID cohorts often lack funding to store and share clinical-epidemiological data (CE) and high-dimensional laboratory (HDL) data long-term, which is evident when the link between these data elements is not kept up to date. This becomes particularly apparent when smaller cohorts fail to successfully address the initial scientific objectives due to limited case numbers, which also limits the potential of pooling for these studies to monitor long-term cross-disease interactions within and across populations. To facilitate advancements in cross-population inference and reuse of cohort data, the European Commission (EC) and the Canadian Institutes of Health Research, Institute of Genetics (CIHR-IG) funded the ReCoDID (Reconciliation of Cohort Data for Infectious Diseases) Consortium to store and share harmonized and standardized CE and HDL data on a federated platform and also provide innovative statistical tools to conduct meta-analyses of the individual patient data. Here we describe the harmonization of CE data from nine arbovirus (arthropod-borne viruses) cohorts in Latin America, which serve as a starting point for the ReCoDID meta-cohort. CE data was retrospectively harmonized using Maelstrom’s methodology and standardized to Clinical Data Interchange Standards Consortium (CDISC).This meta-cohort will facilitate various joint research projects, e.g., on immunological interactions between sequential flavivirus infections and for the evaluation of potential biomarkers for severe arboviral disease.
USe of Diagnostic sUbtraction angiography in The isCHemic stroke setting (US DUTCH study)
Authors: Mulder Maxim J.H.L. , Dippel Diederik W.J. , Burke James 
Published: October 2023

AbstractIntroductionThere are no recommendations for DSA in the ischemic stroke work-up according to current guidelines. We studied the rate of DSA in ischemic stroke, the recent time-trend (given the recent rapid increase in mechanical thrombectomy), hospital variation and associated factors.MethodsThis is a retrospective cross-sectional study among Medicare fee-for-service beneficiaries with ischemic stroke admitted between 2016 and 2020 in the United States. ICD-10 codes were used to determine ischemic stroke diagnosis and procedure codes for thrombectomy and DSA. Hospital trends and factors associated with DSA performance were analyzed in hospitals with DSA capacity.Results7.373 (0.7%) of the 1,085,644 ischemic stroke patients, had a DSA for diagnostic purposes. In the patients that were admitted to a hospital with DSA facility, the following factors showed the strongest association with DSA: younger age (aOR=0.81 [95% confidence interval (CI):0.81-0.83]), thrombectomy rate in that hospital (aOR=2549 [95%CI:610-10663]), transfer (aOR=1.41[95%CI:1.34-1.50]) and carotid disease (aOR=5.8 [95%CI:5.6-6.1]). There was large variation in the hospital DSA rate, varying from 0.07% to 11.1%. Of the variance of DSA rates, 15% was attributed to the residual effect hospital propensity to perform DSA. The top decile of hospitals with the highest DSA rate, performed DSA’s in >2.3% of patients, compared to the 0.6% median. There was no change in DSA rates over time.ConclusionDSA is used infrequently in acute ischemic stroke patients and did not change between 2016 to 2020. Hospital variation in DSA use was however large, and not solely explained by patient and facility factors.
An interactive cellular ecosystem blocks epithelial transformation in naked mole-rat
Authors: Behm Mikaela , Baeza Centurión Pablo , Penso-Dolfin Luca , Botey Bataller Francisco Javier , Hirschmüller Nick , Delaunay Sylvain , Koch Marie-Luise , Del Prete Stefania , Sohn Daniela , Reifenberg Celine , Schopp Meike , Lammers Fritjof , Solé-Boldo Llorenç , Dutton Jeleana , Begall Sabine , Khaled Walid T. , Smith Ewan St. J. , Odom Duncan T. , Frye Michaela , Goncalves Angela 
Published: October 2023

AbstractThe mechanisms underlying cancer resistance in long-lived organisms are largely unexplored. Here, we report how naked mole-rats (Heterocephalus glaber) resist tumorigenesis when exposed to potent skin carcinogens. Single-cell transcriptional analysis of homeostatic full-thickness naked mole-rat skin revealed higher epidermal turn-over, a distinct composition of dermal extracellular matrix (ECM) and fewer resident T-cells, when compared to mouse and human. Carcinogenic treatment of skin generated the expected mutational landscape, but unlike in the mouse, failed to stimulate T-cells or generate tumours. Instead, naked mole-rat accelerated epidermal turnover to shed mutant cells. At the same time, the ECM was extensively remodelled via enhanced anti-inflammatory communication among fibroblasts and between fibroblasts and epidermal cells, creating a tumour-suppressive microenvironment. We demonstrate that, in contrast to mouse, naked mole-rat dermal fibroblasts lack intrinsic tumour-promoting capabilitiesin vitroandin vivo. Our results demonstrate that the cellular ecosystem of naked mole-rat skin actively suppresses epithelial transformation.
AMBERff at scale: Multimillion-atom simulations with AMBER force fields in NAMD
Authors: Antolínez Santiago , Jones Peter Eugene , Phillips James C. , Hadden-Perilla Jodi A. 
Published: October 2023

AbstractAll-atom molecular dynamics (MD) simulations are an essential structural biology technique with increasing application to multimillion-atom systems, including viruses and cellular machinery. Classical MD simulations rely on parameter sets, such as the AMBER family of force fields (AMBERff), to accurately describe molecular motion. Here, we present an implementation of AMBERff for use in NAMD that overcomes previous limitations to enable high-performance, massively-parallel simulations encompassing up to two billion atoms. Single-point potential energy comparisons and case studies on model systems demonstrate that the implementation produces results that are as accurate as running AMBERff in its native engine.
GPN-MSA: an alignment-based DNA language model for genome-wide variant effect prediction
Authors: Benegas Gonzalo , Albors Carlos , Aw Alan J. , Ye Chengzhong , Song Yun S. 
Published: October 2023

AbstractWhereas protein language models have demonstrated remarkable efficacy in predicting the effects of missense variants, DNA counterparts have not yet achieved a similar competitive edge for genome-wide variant effect predictions, especially in complex genomes such as that of humans. To address this challenge, we here introduce GPN-MSA, a novel framework for DNA language models that leverages whole-genome sequence alignments across multiple species and takes only a few hours to train. Across several benchmarks on clinical databases (ClinVar, COSMIC, OMIM), experimental functional assays (DMS, DepMap), and population genomic data (gnomAD), our model for the human genome achieves outstanding performance on deleteriousness prediction for both coding and non-coding variants.
Multioviz: an interactive platform forin silicoperturbation and interrogation of gene regulatory networks
Authors: Xie Helen , Crawford Lorin , Conard Ashley Mae 
Published: October 2023

AbstractIn this paper, we aim to build a tool that will help bridge the gap between high-dimensional computation and wet-lab experimentation by allowing users to interrogate genomic signatures at multiple molecular levels and identify best next actionable steps for downstream decision making. We introduceMultioviz: a publicly accessibleRpackage and web application platform to easily performin silicohypothesis testing of generated gene regulatory networks. We demonstrate the utility ofMultiovizby conducting an end-to-end analysis in a statistical genetics application focused on measuring the effect ofin silicoperturbations of complex trait architecture. By using a real data set from the Wellcome Trust Centre for Human Genetics, we both recapitulate previous findings and propose hypotheses about the genes involved in the percentage of immune CD8+ cells found in heterogeneous stocks of mice. Source code for theMultioviz Rpackage is available athttps://github.com/lcrawlab/multio-vizand an interactive version of the platform is available atmultioviz.ccv.brown.edu.
MagSlice - Ultra Low-cost, modular and rapid 3D printed anatomical models for preoperative planning and patient education
Authors: Tucker Harrison , Pickering Edmund , Fysh Corey , Chen Michael Y. , Rukin Nicholas J , Woodruff Maria A 
Published: October 2023

Abstract3D printed, patient-specific anatomical models have been demonstrated as effective tools for preoperative training, especially in complex surgeries involving rare cases or unique anatomy. Current, state-of-the-art solutions are expensive, requiring 3D printers with large capital and operating costs, making them impractical for common usage and less likely to be adopted in healthcare settings. Alternatively, models fabricated using low-cost printing techniques, like fused filament fabrication (FFF), fail to achieve the utility of their more expensive counterparts. To overcome this challenge, we have developed an innovative approach using FFF that is able to partition the model into separate segments, held together with magnetic fasteners, to unveil the internal anatomy of the model thereby overcoming the challenges of low-cost printing methods and providing equivalent efficacy to the state-of-the-art. Notably, our models can be printed significantly faster and cheaper than other published models and can be viewed holistically as one model, or can be physically expanded into slices (like a deck of cards) whilst maintaining the entire model integrity. By dramatically reducing cost and time, our solution unlocks the potential of 3D printed patient specific models, making these practical for hospital usage.
Generalisability of AI-based scoring systems in the ICU: a systematic review and meta-analysis
Authors: Rockenschaub Patrick , Akay Ela Marie , Carlisle Benjamin Gregory , Hilbert Adam , Meyer-Eschenbach Falk , Näher Anatol-Fiete , Frey Dietmar , Madai Vince Istvan 
Published: October 2023

AbstractBackgroundMachine learning (ML) is increasingly used to predict clinical deterioration in intensive care unit (ICU) patients through scoring systems. Although promising, such algorithms often overfit their training cohort and perform worse at new hospitals. Thus, external validation is a critical – but frequently overlooked – step to establish the reliability of predicted risk scores to translate them into clinical practice. We systematically reviewed how regularly external validation of ML-based risk scores is performed and how their performance changed in external data.MethodsWe searched MEDLINE, Web of Science, and arXiv for studies using ML to predict deterioration of ICU patients from routine data. We included primary research published in English before April 2022. We summarised how many studies were externally validated, assessing differences over time, by outcome, and by data source. For validated studies, we evaluated the change in area under the receiver operating characteristic (AUROC) attributable to external validation using linear mixed-effects models.ResultsWe included 355 studies, of which 39 (11.0%) were externally validated, increasing to 17.9% by 2022. Validated studies made disproportionate use of open-source data, with two well-known US datasets (MIMIC and eICU) accounting for 79.5% of studies. On average, AUROC was reduced by -0.037 (95% CI -0.064 to -0.017) in external data, with >0.05 reduction in 38.6% of studies.DiscussionExternal validation, although increasing, remains uncommon. Performance was generally lower in external data, questioning the reliability of some recently proposed ML-based scores. Interpretation of the results was challenged by an overreliance on the same few datasets, implicit differences in case mix, and exclusive use of AUROC.
SARS-CoV-2, influenza A/B and respiratory syncytial virus positivity and association with influenza-like illness and self-reported symptoms, over the 2022/23 winter season in the UK: a longitudinal surveillance cohort
Authors: Dietz Elisabeth , Pritchard Emma , Pouwels Koen , Ehsaan Muhammad , Blake Joshua , Gaughan Charlotte , Haduli Eric , Boothe Hugh , Vihta Karina-Doris , Peto Tim , Stoesser Nicole , Matthews Philippa , Taylor Nick , Diamond Ian , Studley Ruth , Rourke Emma , Birrell Paul , De Angelis Daniela , Fowler Tom , Watson Conall , Eyre David , House Thomas , Walker Ann Sarah 
Published: October 2023

AbstractBackgroundSyndromic surveillance often relies on patients presenting to healthcare. Community cohorts, although more challenging to recruit, could provide additional population-wide insights, particularly with SARS-CoV-2 co-circulating with other respiratory viruses.MethodsWe estimated positivity and incidence of SARS-CoV-2, influenza A/B, and RSV, and trends in self-reported symptoms including influenza-like illness (ILI), over the 2022/23 winter season in a broadly representative UK community cohort (COVID-19 Infection Survey), using negative-binomial generalised additive models. We estimated associations between test positivity and each of symptoms and influenza vaccination, using adjusted logistic and multinomial models.FindingsSwabs taken at 32,937/1,352,979 (2.4%) assessments tested positive for SARS-CoV-2, 181/14,939 (1.2%) for RSV and 130/14,939 (0.9%) for influenza A/B, varying by age over time. Positivity and incidence peaks were earliest for RSV, then influenza A/B, then SARS-CoV-2, and were highest for RSV in the youngest and for SARS-CoV-2 in the oldest age-groups. Many test-positives did not report key symptoms: middle-aged participants were generally more symptomatic than older or younger participants, but still only ∼25% reported ILI-WHO and ∼60% ILI-ECDC. Most symptomatic participants did not test positive for any of the three viruses. Influenza A/B-positivity was lower in participants reporting influenza vaccination in the current and previous seasons (odds ratio=0.55 (95% CI 0.32,0.95)) versus neither season.InterpretationSymptom profiles varied little by aetiology, making distinguishing SARS-CoV-2, influenza and RSV using symptoms challenging. Most symptoms were not explained by these viruses, indicating the importance of other pathogens in syndromic surveillance. Influenza vaccination was associated with lower rates of community influenza test positivity.FundingUK Health Security Agency, Department of Health and Social Care, National Institute for Health Research.
Molecular Epidemiology of DiarrhoeagenicEscherichia coliin Africa: A Systematic Review and Meta-Analysis
Authors: Kalule John Bosco , Bester Linda A. , Banda Daniel L. , Derra Firehiwot Abera , Chikuse Francis , Tessema Sofonias K. ,   Africa PGI Foodborne Diseases Genomic Surveillance Focus Group, Foster-Nyarko Ebenezer 
Published: October 2023

AbstractIntroductionDiarrhoeagenicEscherichia coli(DEC) persistently challenges public health in Africa, contributing substantially to the diarrhoeal disease burden. This systematic review and meta-analysis illuminate the distribution and antimicrobial resistance (AMR) patterns of DEC pathotypes across the continent.MethodsThe review selectively focused on studies reporting prevalence and/or AMR of human-derived DEC pathotypes from African nations, excluding data from extra-intestinal, animal, and environmental sources, and studies focused on drug and mechanism experiments. Employing a robust search strategy, pertinent studies were retrieved from SCOPUS, PubMed, and EBSCOhost, processed with Covidence, and screened in alignment with PRISMA guidelines.ResultsThe reviewed studies were predominantly hospital-based (80%) and paediatric-focused (91%), with a meagre 4.4% documenting DEC outbreaks. Seven DEC pathotypes were discerned, with EnteroaggregativeE. coli(EAEC) being notably prevalent (43%, 95% CI: 30% – 55%) and EnteroinvasiveE. coli(EIEC) least prevalent (24%, 95%CI: 17% – 32%). Identified non-susceptibilities were noted against essential antibiotics, including ciprofloxacin, ceftriaxone, and ampicillin, while instances of carbapenem and Extended-Spectrum Beta-Lactamase (ESBL) resistance were scarce.ConclusionDespite sporadic data on DEC prevalence and AMR in Africa, particularly in community settings, a palpable gap remains in real-time outbreak surveillance and comprehensive data documentation. Augmenting surveillance and embracing advancements in molecular/genomic characterisation techniques are crucial to precisely discerning the actual impact and resistance continuum of DEC in Africa.
Transcriptomics profiling of Parkinson’s disease progression subtypes reveals distinctive patterns of gene expression
Authors: Fabrizio Carlo , Termine Andrea , Caltagirone Carlo 
Published: October 2023

AbstractParkinson’s Disease (PD) exhibits significant individual variability, and recent Artificial Intelligence advancements have identified three distinct progression subtypes, each with known clinical features but unexplored gene expression profiles. This study aimed to identify the transcriptomics characteristics of PD progression subtypes, and assess the utility of gene expression data in subtype prediction at baseline. Differentially expressed genes were subtype-specific, and not typically found in other PD studies. Pathway analysis showed distinct and shared features among subtypes. Two had opposing expression patterns for shared pathways, and the third had a more unique profile with respect to the others. Machine Learning revealed that the progression subtype with the worst prognosis can be predicted at baseline with 0.877 AUROC, yet the contribution of gene expression was marginal for the prediction of the subtypes. This study offers insights into PD subtypes transcriptomics, fostering precision medicine for improved diagnosis and prognosis.