bluuebunny/crossref_metadata_2025_split huggingface dataset:
Distress and factors for maintaining good mental health among general practitioners during the SARS-CoV-2 pandemic: Results from the cross-sectional PRICOV-19 study in Austria
Authors: Hoffmann Kathryn , Stummer Florian O. , van Poel Esther , Willems Sara , Wojczewski Silvia 
Published: May 2024

AbstractBackgroundThe COVID-19 pandemic has had a significant negative impact on the physical and mental health of healthcare workers worldwide. The aim of the paper is to measure the frequency of distress and wellbeing among general practitioners (GPs) in Austria during the pandemic and to identify key levers that could mitigate the risks of distress.MethodsData were collected as part of the international PRICOV-19 study. In Austria, 500 GPs were randomly selected for participation in a survey between December 2020 and July 2021. For analysis, all dependent and independent variables were described using descriptive statistical methods. Subgroup analyses were conducted using cross-tables and Fisher’s exact tests. A binary logistic regression model was also applied. Open text question was analysed via content analysis.ResultsIn total, 130 GPs completed the relevant questions for this analysis of the online survey. More than 40% of GPs felt burned out or stated that their work schedules did not leave enough time for personal/family life. Half of the GPs were found to be in distress, with 14.3% in (very) strong distress. More than 40% of the respondents thought that government support was insufficient for the proper functioning of their practice. Working in rural areas was a protective factor against distress, as were sport and exercise, particularly outdoor activity. Connecting with family and friends and adjustments to the work environment to reduce workload were shown to be important.DiscussionOur results show that GPs in Austria suffered from distress during the first two years of the pandemic. To protect GPs as our first-line healthcare workers in pandemic or high-stress situations, several factors are required for a functioning healthcare system: support of GPs regarding work-life balance, support in terms of collaboration between colleagues and the team and easy access to green outdoor spaces for sports and exercise. By identifying key factors that promote good mental health among GPs, healthcare organizations and policymakers can take targeted action to alleviate the negative impact of stress and burnout on this critical sector of the healthcare workforce.
Large language models to help appeal denied radiotherapy services
Authors: Kiser Kendall , Waters Mike , Reckford Jocelyn , Lundeberg Christopher , Abraham Christopher 
Published: May 2024

AbstractBackgroundLarge language model (LLM) artificial intelligences have potential to perform myriad healthcare tasks but should be validated in specific clinical use cases before deployment. One use case is to help physicians appeal insurer denials of prescribed medical services, a task that delays patient care and contributes to burnout. We evaluated LLM performance at this task for denials of radiotherapy services.MethodsWe evaluated generative pre-trained transformer 3.5 (GPT-3.5) (OpenAI, San Francisco, CA), GPT-4, GPT-4 with internet search functionality (GPT-4web), and GPT-3.5ft. The latter was developed by fine-tuning GPT-3.5 via an OpenAI application programming interface with 53 examples of appeal letters written by radiation oncologists. Twenty test prompts with simulated patient histories were programmatically presented to the LLMs, and output appeal letters were scored by three blinded radiation oncologists for language representation, clinical detail inclusion, clinical reasoning validity, literature citations, and overall readiness for insurer submission.ResultsInterobserver agreement between radiation oncologists’ scores was moderate or better for all domains (Cohen’s kappa coefficients: 0.41 – 0.91). GPT-3.5, GPT-4, and GPT-4web wrote letters that were on average linguistically clear, summarized provided clinical histories without confabulation, reasoned appropriately, and were scored useful to expedite the insurance appeal process. GPT-4 and GPT-4web letters demonstrated superior clinical reasoning and were readier for submission than GPT-3.5 letters (p < 0.001). Fine-tuning increased GPT-3.5ft confabulation and compromised performance compared to other LLMs across all domains (p < 0.001). All LLMs, including GPT-4web, were poor at supporting clinical assertions with existing, relevant, and appropriately cited primary literature.ConclusionsWhen prompted appropriately, three commercially available LLMs drafted letters that physicians deemed would expedite appealing insurer denials of radiotherapy services. LLMs may decrease this task’s clerical workload on providers. However, LLM performance worsened when fine-tuned with a task-specific, small training dataset.
Causal Machine Learning Analysis of Radiation-Induced Leukemia and Solid Tumor Incidence in Japanese Atomic Bomb Survivors
Authors: Shuryak Igor , Liu Zhenqiu , Wang Eric , Ullrich Robert L. , Brenner David J. 
Published: May 2024

AbstractUncertainty in low-dose ionizing radiation-induced health risks stems from several factors. The complex biological pathways leading to diseases like cancer are not fully understood, making it difficult to distinguish the contribution of radiation, particularly at low doses which induce only small perturbations to background disease risks. Additionally, traditional dose-response models, such as the Linear No-Threshold formalism and competing threshold or hormesis models, impose rigid assumptions on dose response shapes, causing controversy and increasing model selection uncertainty. Furthermore, these modeling strategies operate on the level of correlations/associations, and are not designed to directly address the ultimate goal of radiation epidemiology – assessing causal links between radiation and disease. A promising and rapidly-developing approach for addressing some of these challenges is causal machine learning (CML), such as double/debiased machine learning (DML), which is designed to model causal effects in multi-dimensional data sets. Our study employs DML to elucidate the causal impacts of radiation exposure on the incidence of leukemia, all solid tumors, and stomach tumors among Japanese atomic bomb survivors. Its goal was not to produce a definitive re-analysis of these data sets, but to provide a useful example of implementing CML in radiation epidemiology, which can advance the field by supplementing traditional modeling approaches. The results revealed robust positive causal effects of radiation for all three tumor types, especially for leukemia and stomach tumors. The effect magnitudes, and uncertainties, were not dramatically different at low doses than at higher doses. The influences of age at exposure, attained age, sex and other covariates on the causal effects of radiation were assessed using Shapley Additive Explanations (SHAP) values. We believe that this analysis, based on a flexible machine learning framework with a causal inference motivation and without strict dose response assumptions, provides an important contribution to radiation epidemiology.
Notable transmitted HIV drug resistance among people who inject drugs in Pakistan
Authors: Melnychuk Stephanie , Thompson Laura H. , Archibald Chris , Blanchard James F. , Emmanuel Faran , Reza Tahira , Dar Nosheen , Sandstrom Paul , Shaw Souradet Y. , Becker Marissa L. , Cholette François 
Published: May 2024

AbstractTransmission of drug-resistant HIV strains to treatment-naïve patients can compromise antiretroviral therapy (ART) effectiveness and lead to treatment failure. In Pakistan, transmitted HIV drug resistance among people who inject drugs (PWID) is fuelled by a lack of ART, poor drug adherence, and unsafe injection practices, resulting in efficient transmission in large injecting networks. A cross-sectional study was conducted among PWID recruited in the Pakistani cities of Karachi, Larkana, Peshawar, Quetta and Hyderabad (August 2014 to January 2015). A portion of the HIVpolgene was amplified from HIV-reactive dried blood spot specimens (n=282/367) and sequenced using an in-house Sanger sequencing assay for HIV drug resistance mutation genotyping. Drug resistance mutations (DRMs) were identified using the Stanford University HIV Drug Resistance Database HIVdb algorithm (https://hivdb.stanford.edu/hivdb). Overall, HIV subtype A1 was dominant (78.0%;n=220), followed by CRF02_AG (15.6%;n=44), CRF35_AD (2.5%n=7), recombinants (3.5%;n=10), and subtype C (0.4%n=1). DRM analysis identified over half (63.8%) of participants harbored at least one DRM, of which 28.9% reported using help from a professional injector. Nearly all (99.4%) participants were not actively receiving ART because most (88.7%) had never undergone HIV testing and were unaware of their status. Findings suggest significant transmitted HIV drug resistance present among PWID, exacerbated by unsafe injection practices, particularly professional injection. Low testing rates signal a need for more comprehensive testing programs to improve HIV status awareness and ART coverage in Pakistan. Given most treatment-naïve participants had evidence of drug resistance, drug resistance genotyping prior to ART initiation might aid in ensuring effective treatment to prevent transmission of resistant HIV strains.
Leveraging haplotype information in heritability estimation and polygenic prediction
Authors: Meisner Jonas , Benros Michael Eriksen , Rasmussen Simon 
Published: May 2024

AbstractPolygenic prediction has yet to make a major clinical breakthrough in precision medicine and psychiatry, where the application of polygenic risk scores are expected to improve clinical decision-making. Most widely used approaches for estimating polygenic risk scores are based on summary statistics from external large-scale genome-wide association studies, which relies on assumptions of matching data distributions. This may hinder the impact of polygenic risk scores in modern diverse populations due to small differences in genetic architectures. Reference-free estimators of polygenic scores are instead based on genomic best linear unbiased predictions and models the population of interest directly. We introduce a framework, namedhapla, with a novel algorithm for clustering haplotypes in phased genotype data to estimate heritability and perform reference-free polygenic prediction in complex traits. We utilize inferred haplotype clusters to compute accurate SNP heritability estimates and polygenic scores in a simulation study and the iPSYCH2012 case-cohort for depression disorders and schizophrenia. We demonstrate that our haplotype-based approach robustly outperforms standard genotype-based approaches, which can help pave the way for polygenic risk scores in the future of precision medicine and psychiatry.haplais freely available athttps://github.com/Rosemeis/hapla.
Influence of aversive cue detection sensitivity on extinction in adult male rats
Authors: Cahill Emma N , Sherman Emily R , Jollans Joseph , Deiana Serena , Hengerer Bastian 
Published: May 2024

ABSTRACTThreat detection prompts reactions classified either as fear (obvious, predictable, immediate threat) or anxiety (ambiguous, sustained, distant threat). Hypervigilance is a state of sensitivity to threatening stimuli and an attentional bias symptomatic of anxiety disorders. In rodents, threat detection can be measured by freezing behaviour and production of ultrasonic vocalisation (USV) alarm calls. The amygdala is classically associated with fear-like responses, whereas the bed nucleus of the stria terminalis (BNST) has been proposed to be preferentially recruited by anxiogenic stimuli. The conditioned responses triggered by aversive cues can be extinguished through repeated exposure of a subject to the threat stimulus but without any aversive reinforcement. The extent of extinction acquisition and consolidation are notedly variable across individuals. It has been reported that NMDA-type glutamate receptor co-agonists, like D-cycloserine, can enhance extinction consolidation. In the experiments herein, the salience of a threat cue was modified to compare the relative activation of the brain vigilance networks to an obvious cue, and to test whether sensitivity to the aversive cue at such a ‘vigilance screen’ might predict subsequent ability to extinguish conditioned responses. We demonstrated activation of the BNST by a low salience aversive cue. Rats that had the propensity to make alarm ultrasonic vocalisation calls reacted more strongly to aversive cues and had deficits in conditioned freezing extinction. Finally, we demonstrated the potential to enhance extinction consolidation by targeting glycine transmission. Taken together these results demonstrate how threat detection and responses are sensitive to cue salience and can be manipulated by combined pharmacological and behavioural interventions.HIGHLIGHTS:-Auditory cue at low salience revealed attentional bias unrelated to maze behaviour-Low salience cue recruited activation of the BNST-Alarm call vocaliser rats had deficit in extinction consolidation-GlyT1 inhibition enhanced extinction consolidation
Nuclear Translocation of SIRT4 Mediates Deacetylation of U2AF2 to Modulate Renal Fibrosis Through Alternative Splicing-mediated Upregulation of CCN2
Authors: Yang Guangyan , Xiang Jiaqing , Yang Xiaoxiao , Liu Xiaomai , Li Yanchun , Li Lixing , Kang Lin , Liang Zhen , Yang Shu 
Published: May 2024

AbstractTGF-β stimulates CCN2 expression which in turn amplifies TGF-β signaling. This process promotes extracellular matrix production and accelerates the pathological progression of fibrotic diseases. Alternative splicing plays an important role in multiple disease development, while U2 small nuclear RNA auxiliary factor 2 (U2AF2) is an essential factor in the early steps of pre-mRNA splicing. However, the molecular mechanism underlying abnormalCCN2expression upon TGF-β stimulation remains unclear. This study elucidates that SIRT4 acts as a master regulator for CCN2 expression in response to TGF-β by modulating U2AF2-mediated alternative splicing. Analyses of renal biopsy specimens from patients with CKD and mouse fibrotic kidney tissues revealed marked nuclear accumulation of SIRT4. The tubulointerstitial fibrosis was alleviated by global deletion or tubular epithelial cell (TEC)-specific knockout ofSirt4, and aggravated by adeno-associated virus-mediated SIRT4 overexpression in TECs. Furthermore, SIRT4 was found to translocate from the mitochondria to the cytoplasm through the BAX/BAK pore under TGF-β stimulation. In the cytoplasm, TGF-β activated the ERK pathway and induced the phosphorylation of SIRT4 at Ser36, which further promoted its interaction with importin α1 and subsequent nuclear translocation. In the nucleus, SIRT4 was found to deacetylate U2AF2 at K413, facilitating the splicing of CCN2 pre-mRNA to promote CCN2 protein expression. Importantly, exosomes containing anti-SIRT4 antibodies were found to effectively mitigate the UUO-induced kidney fibrosis in mice. Collectively, these findings indicated that SIRT4 plays a role in kidney fibrosis by regulating CCN2 expression via the pre-mRNA splicing.
Accurate localization of cortical and subcortical sources of M/EEG signals by a convolutional neural network with a realistic head conductivity model: Validation with M/EEG simulation, evoked potentials, and invasive recordings
Authors: Yokoyama Hikaru , Kaneko Natsuko , Usuda Noboru , Kato Tatsuya , Ming Khoo Hui , Fukuma Ryohei , Oshino Satoru , Tani Naoki , Kishima Haruhiko , Yanagisawa Takufumi , Nakazawa Kimitaka 
Published: May 2024

AbstractWhile electroencephalography (EEG) and magnetoencephalography (MEG) are well-established non-invasive methods in neuroscience and clinical medicine, they suffer from low spatial resolution. Particularly challenging is the accurate localization of subcortical sources of M/EEG, which remains a subject of debate. To address this issue, we propose a four-layered convolutional neural network (4LCNN) designed to precisely locate both cortical and subcortical source activity underlying M/EEG signals. The 4LCNN was trained using a vast dataset generated by forward M/EEG simulations based on a realistic head volume conductor model. The 4LCNN implicitly learns the characteristics of M/EEG and their sources from the training data without need for explicitly formulating and fine-tuning optimal priors, a common challenge in conventional M/EEG source imaging techniques. We evaluated the efficacy of the 4LCNN model on a validation dataset comprising forward M/EEG simulations and two types of real experimental data from humans: 1) somatosensory evoked potentials recorded by EEG, and 2) simultaneous recordings from invasive electrodes implanted in the brain and MEG signals. Our results demonstrate that the 4LCNN provides robust and superior estimation accuracy compared to conventional M/EEG source imaging methods, aligning well with established neuroscience knowledge. Notably, the accuracy of the subcortical regions was as accurate as that of the cortical regions. The 4LCNN method, as a data-driven approach, enables accurate source localization of M/EEG signals, including in subcortical regions, suggesting future contributions to various research endeavors such as contributions to the clinical diagnosis, understanding of the pathophysiology of various neuronal diseases and basic brain functions.
Layer 6 corticocortical neurons are a major route for intra and interhemispheric feedback
Authors: Weiler Simon , Teichert Manuel , Margrie Troy W. 
Published: May 2024

AbstractThe mouse neocortex contains at least ninety distinctly defined yet interconnected areas that are symmetrically located across the two hemispheres. Determining the logic of this long range circuitry is necessary for understanding how inter-areal integration enables high level brain function involving multiple sensory, motor and cognitive processes. To address this we have performed a systematic anatomical analysis of the areal and laminar organization of the ipsilateral and contralateral cortical projection onto the primary visual (VISp), primary somatosensory barrel field (SSp-bfd) and primary motor (MOp) cortices. The resultant input maps reveal that although the ipsilateral hemisphere is the primary source of cortical input, there is substantial bilateral symmetry regarding the relative contribution and areal identity of contralateral input. Laminar analysis of these input areas show that excitatory Layer 6 corticocortical cells (L6 CCs) are a major projection pathway from both within and across the two hemispheres. Based on cortical hierarchy analysis that compares the relative contribution of inputs from supra-(feedforward) and infra-granular (feedback) layers, we find that contra-hemispheric projections reflect a dominant feedback organization compared to their ipsi-cortical counterpart. The magnitude of the interhemispheric difference in hierarchy was largest for sensory and motor projection areas compared to frontal, medial or lateral brain areas and can be explained by a proportional increase in input from L6 neurons. L6 CCs therefore not only mediate long-range cortical communication but also reflect its inherent feedback organization.
Emergence and interstate spread of highly pathogenic avian influenza A(H5N1) in dairy cattle
Authors: Nguyen Thao-Quyen , Hutter Carl , Markin Alexey , Thomas Megan , Lantz Kristina , Killian Mary Lea , Janzen Garrett M. , Vijendran Sriram , Wagle Sanket , Inderski Blake , Magstadt Drew R. , Li Ganwu , Diel Diego G. , Frye Elisha Anna , Dimitrov Kiril M. , Swinford Amy K. , Thompson Alexis C. , Snevik Kevin R. , Suarez David L. , Spackman Erica , Lakin Steven M. , Ahola Sara C. , Johnson Kammy R. , Baker Amy L. , Robbe-Austerman Suelee , Torchetti Mia Kim , Anderson Tavis K. 
Published: May 2024

AbstractHighly pathogenic avian influenza (HPAI) viruses cross species barriers and have the potential to cause pandemics. In North America, HPAI A(H5N1) viruses related to the goose/Guangdong 2.3.4.4b hemagglutinin phylogenetic clade have infected wild birds, poultry, and mammals. Our genomic analysis and epidemiological investigation showed that a reassortment event in wild bird populations preceded a single wild bird-to-cattle transmission episode. The movement of asymptomatic cattle has likely played a role in the spread of HPAI within the United States dairy herd. Some molecular markers in virus populations were detected at low frequency that may lead to changes in transmission efficiency and phenotype after evolution in dairy cattle. Continued transmission of H5N1 HPAI within dairy cattle increases the risk for infection and subsequent spread of the virus to human populations.
Identification of Fibrinogen as a Plasma Protein Binding Partner for Lecanemab Biosimilar IgG: Implications for Alzheimer’s Disease Therapy
Authors: Bellier Jean-Pierre , Román Viera Andrea M. , Christiano Caitlyn , Anzai Juliana A. U. , Moreno Stephanie , Campbell Emily C. , Godwin Lucas , Li Amy , Chen Alan Y. , Alam Sarah , Saba Adriana , Yoo Han bin , Yang Hyun-Sik , Chhatwal Jasmeer P. , Selkoe Dennis J. , Liu Lei 
Published: May 2024

ABSTRACTObjectiveRecombinant monoclonal therapeutic antibodies like lecanemab, which target amyloid beta in Alzheimer’s disease, offer a promising approach for modifying the disease progression. Due to its relatively short half-life, Lecanemab, administered as a bi-monthly infusion (typically 10mg/kg) has a relatively brief half-life. Interaction with abundant plasma proteins binder in the bloodstream can affect pharmacokinetics of drugs, including their half-life. In this study we investigated potential plasma protein binding interaction to lecanemab using lecanemab biosimilar.MethodsLecanemab biosimilar used in this study was based on publicly available sequences. ELISA and Western blotting were used to assess lecanemab biosimilar immunoreactivity in the fractions human plasma sample obtained through size exclusion chromatography. The binding of lecanemab biosimilar to candidate binders was confirmed by Western blotting, ELISA, and surface plasmon resonance analysis.ResultsUsing a combination of equilibrium dialysis, ELISA, and Western blotting in human plasma, we first describe the presence of likely plasma protein binding partner to lecanemab biosimilar, and then identify fibrinogen as one of them. Utilizing surface plasmon resonance, we confirmed that lecanemab biosimilar does bind to fibrinogen, although with lower affinity than to monomeric amyloid beta.InterpretationIn the context of lecanemab therapy, these results imply that fibrinogen levels could impact the levels of free antibodies in the bloodstream and that fibrinogen might serve as a reservoir for lecanemab. More broadly, these results indicate that plasma protein binding may be an important consideration when clinically utilizing therapeutic antibodies in neurodegenerative disease.