bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using correlative and mechanistic species distribution models to predict vector-borne disease risk for the current and future environmental and climatic change: a case study of West Nile Virus in the UK
Authors: Withers A. J. , Croft S. , Budgey R. , Warren D. , Johnson N. 
Published: September 2024

AbstractGlobally, vector-borne diseases have significant impacts on both animal and human health, and these are predicted to increase with the effects of climate change. Understanding the drivers of such diseases can help inform surveillance and control measures to minimise risks both now and in the future. In this study, we illustrate a generalised approach for assessing disease risk combining species distribution models of vector and wildlife hosts with data on livestock and human populations using the potential emergence of West Nile Virus (WNV) in the UK as a case study. Currently absent in the UK, WNV is an orthoflavivirus with a natural transmission cycle betweenCulexmosquitos (Cx. pipiensandCx. modestus) and birds. It can spread into non-target hosts (e.g., equids, humans) via mosquito bites where it can cause febrile disease with encephalitis and mortality in severe cases. We compared six correlative species distribution models and selected the most appropriate for each vector based on a selection of performance measures and compared this to mechanistic species distribution models and known distributions. We then combined these with correlative species distribution models of representative avian hosts, equines, and human population data to predict risk of WNV occurrence. Our findings highlighted areas at greater risk of WNV due to higher habitat suitability for both avian hosts and vectors, and considered how this risk could change by 2100 under a best-case Shared Socioeconomic Pathway (SSP1) and worst-case (SSP5) future climate scenario. Generally, WNV risk in the future was found to increase in south-eastern UK and decrease further north. Overall, this paper presents how current and future vector distributions can be modelled and combined with projected host distributions to predict areas at greater risk of novel diseases. This is important for policy decision making and contingency preparedness to enable adaptation to changing environments and the resulting shifts in vector-borne diseases that are predicted to occur.
Practice Reshapes the Geometry and Dynamics of Task-tailored Representations
Authors: Kikumoto Atsushi , Shibata Kazuhisa , Nishio Takahiro , Badre David 
Published: September 2024

AbstractExtensive practice makes task performance more efficient and precise, leading to automaticity. However, theories of automaticity differ on which levels of task representations (e.g., low-level features, stimulus-response mappings, or high-level conjunctive memories of individual events) change with practice, despite predicting the same pattern of improvement (e.g., power law of practice). To resolve this controversy, we built on recent theoretical advances in understanding computations through neural population dynamics. Specifically, we hypothesized that practice optimizes the neural representational geometry of task representations to minimally separate the highest-level task contingencies needed for successful performance. This involves efficiently reaching conjunctive neural states that integrate task-critical features nonlinearly while abstracting over non-critical dimensions. To test this hypothesis, human participants (n = 40) engaged in extensive practice of a simple, context-dependent action selection task over 3 days while recording EEG. During initial rapid improvement in task performance, representations of the highest-level, context-specific conjunctions of task-features were enhanced as a function of the number of successful episodes. Crucially, only enhancement of these conjunctive representations, and not lower-order representations, predicted the power-law improvement in performance. Simultaneously, over sessions, these conjunctive neural states became more stable earlier in time and more aligned, abstracting over redundant task features, which correlated with offline performance gain in reducing switch costs. Thus, practice optimizes the dynamic representational geometry as task-tailored neural states that minimally tesselate the task space, taming their high-dimensionality.
Endogenous Regulator of G protein Signaling 14 (RGS14) suppresses cocaine-induced emotionally motivated behaviors in female mice
Authors: Bramlett Sara N. , Foster Stephanie L. , Weinshenker David , Hepler John R. 
Published: September 2024

ABSTRACTAddictive drugs hijack the neuronal mechanisms of learning and memory in motivation and emotion processing circuits to reinforce their own use. Regulator of G-protein Signaling 14 (RGS14) is a natural suppressor of post-synaptic plasticity underlying learning and memory in the hippocampus. The present study used immunofluorescence and RGS14 knockout mice to assess the role of RGS14 in behavioral plasticity and reward learning induced by chronic cocaine in emotional-motivational circuits. We report that RGS14 is strongly expressed in discrete regions of the ventral striatum and extended amygdala in wild-type mice, and is co-expressed with D1 and D2 dopamine receptors in neurons of the nucleus accumbens (NAc). Of note, we found that RGS14 is upregulated in the NAc in mice with chronic cocaine history following acute cocaine treatment. We found significantly increased cocaine-induced locomotor sensitization, as well as enhanced conditioned place preference and conditioned locomotor activity in RGS14-deficient mice compared to wild-type littermates. Together, these findings suggest that endogenous RGS14 suppresses cocaine-induced plasticity in emotional-motivational circuits, implicating RGS14 as a protective agent against the maladaptive neuroplastic changes that occur during addiction.
The mitochondrial dicarboxylate carrier mediates in vivo hepatic gluconeogenesis
Authors: Pape Daniel J. , Falls-Hubert Kelly C. , Merrill Ronald A. , Ahmed Adnan , Qian Qingwen , McGivney Gavin R. , Sobieralski Paulina , Rauckhorst Adam J. , Yang Ling , Taylor Eric B. 
Published: September 2024

SUMMARYHepatic gluconeogenesis (GNG) is essential for maintaining euglycemia during prolonged fasting. However, GNG becomes pathologically elevated and drives chronic hyperglycemia in type 2 diabetes (T2D). Lactate/pyruvate is a major GNG substrate known to be imported into mitochondria for GNG. Yet, the subsequent mitochondrial carbon export mechanisms required to supply the extra-mitochondrial canonical GNG pathway have not been genetically delineated. Here, we evaluated the role of the mitochondrial dicarboxylate carrier (DiC) in mediating GNG from lactate/pyruvate. We generated liver-specific DiC knockout (DiC LivKO) mice. During lactate/pyruvate tolerance tests, DiC LivKO decreased plasma glucose excursion and13C-lactate/-pyruvate flux into hepatic and plasma glucose. In a Western diet (WD) feeding model of T2D, acute DiC LivKO after induction of obesity decreased lactate/pyruvate-driven GNG, hyperglycemia, and hyperinsulinemia. Our results show that mitochondrial carbon export through the DiC mediates GNG and that the DiC contributes to impaired glucose homeostasis in a mouse model of T2D.
Escaping the drug-bias trap: using debiasing design to improve interpretability and generalization of drug-target interaction prediction
Authors: Zhang Pei-Dong , Ma Jianzhu , Chen Ting 
Published: September 2024

AbstractConsidering the high cost associated with determining reaction affinities through in-vitro experiments, virtual screening of potential drugs bound with specific protein pockets from vast compounds is critical in AI-assisted drug discovery. Deep-leaning approaches have been proposed for Drug-Target Interaction (DTI) prediction. However, they have shown overestimated accuracy because of the drug-bias trap, a challenge that results from excessive reliance on the drug branch in the traditional drug-protein dual-branch network approach. This casts doubt on the interpretability and generalizability of existing Drug-Target Interaction (DTI) models. Therefore, we introduce UdanDTI, an innovative deep-learning architecture designed specifically for predicting drug-protein interactions. UdanDTI applies an unbalanced dual-branch system and an attentive aggregation module to enhance interpretability from a biological perspective. Across various public datasets, UdanDTI demonstrates outstanding performance, outperforming state-of-the-art models under in-domain, cross-domain, and structural interpretability settings. Notably, it demonstrates exceptional accuracy in predicting drug responses of two crucial subgroups of Epidermal Growth Factor Receptor (EGFR) mutations associated with non-small cell lung cancer, consistent with experimental results. Meanwhile, UdanDTI could complement the advanced molecular docking software DiffDock. The codes and datasets of UdanDTI are available athttps://github.com/CQ-zhang-2016/UdanDTI.
A case is not a case is not a case - challenges and solutions in determining urolithiasis caseloads using the digital infrastructure of a clinical data warehouse
Authors: Schönthaler Martin , Hempen Noah , Weymann Maria , von Bargen Maximilian Ferry , Glienke Maximilian , Elsässer Antonia , Behrens Max , Binder Harald , Binder Nadine 
Published: September 2024

AbstractBackgroundTo provide more evidence in urolithiasis research, we have established the German Nationwide Register for RECurrent URolithiasis (RECUR) using local clinical data warehouses (CDWH). For RECUR and other registers relying on digitalized clinical data, it is crucial to ensure the data’s reliability for answering scientific questions. In this work, we aim to compare the results of different CDWH-based queries on urolithiasis cases next to manual case extraction from the primary source.MethodsSources for data extraction included the Medical Center University of Freiburg (MCUF) hospital information system (HIS), MCUF performance data (a clinical data set with merged data from patients including data from vari-ous time points throughout their treatment), and MCUF reimbursement data. We extracted data on caseloads in urolithiasis algorithmically (performance and reimbursement data) and compared those to a reference group compiled of man-ually extracted data from the local HIS and algorithmically extracted data.ResultsAlgorithmic extraction based on performance data resulted in correct and complete case identification as compared to the reference group. The case numbers from manual extraction from HIS data and algorithmic extraction from reimbursement data differed by 14% and 12%, respectively. The reasons for devi-ations in HIS data included human errors and a lack of data availability from different wards. Deviations in reimbursement data arose primarily due to the merging of cases in the context of reimbursement mechanisms. As the CDWH at MCUF is part of the German Medical Informatics Initiative (MII), the results can be transferred to other medical centers with similar CDWH structure.ConclusionsThe current study provides firm evidence of the importance of clearly defining a study’s target variable, e.g., urolithiasis cases, and a thorough understanding of the data sources and modes used to extract the target data. Our work clearly shows that, depending on various data sources, a case is not a case is not a case.
Barriers and Facilitators to Community Pharmacist-Provided Injectable Naltrexone for Formerly Incarcerated Individuals During Community Reentry in Wisconsin
Authors: Chladek Jason S. , Chui Michelle A. 
Published: September 2024

AbstractMedications for opioid use disorder (MOUD), including injectable naltrexone, are a key component in the treatment of opioid use disorder (OUD). These medications are especially important for individuals transitioning out of correctional facilities and back into their communities, as individuals receiving MOUD are 85% less likely to die due to drug overdose in the first month post-release and have a 32% lower risk of rearrest. Unfortunately, few formerly incarcerated individuals have access to MOUD upon reentry, incurring a 40-fold greater likelihood of overdose following release compared to the general population. While 84% of Wisconsin jails offering MOUD offer naltrexone, less than half provide linkage to community treatment for reentering individuals. In Wisconsin, community pharmacists have the authority to provide naltrexone injections. However, they have not been explored as a resource for improving access to this medication for formerly incarcerated individuals. As a first step, the goal of this study was to understand the barriers and facilitators impacting access to community pharmacist-provided injectable naltrexone for this patient population during community reentry period. The researcher conducted semi-structured interviews with 18 individuals representing five stakeholder groups. Deductive and inductive content analysis were used to identify barrier and facilitator categories across the five levels of the Socioecological Model. Overall, participants discussed factors at every level, and many barriers and facilitators confirmed findings from existing literature focused on MOUD access for formerly incarcerated individuals. Participants also identified factors more specific to community pharmacies, including 1) lack of interagency collaboration between pharmacists, prescribers, and correctional facilities and 2) lack of awareness of community pharmacist-provided MOUD services. Future research should explore interventions to address the barriers identified in this study and improve connections between community pharmacists and formerly incarcerated individuals. This work can help ensure that these individuals are given the chance to successfully reintegrate into society.
Plasma glucosylceramide levels are regulated byATP10Dand are not involved in Parkinson’s disease pathogenesis
Authors: Somerville Emma N. , James Alva , Beetz Christian , Schwieger Robert , Barrel Gal , Kandaswamy Krishna K. , Iurascu Marius I. , Bauer Peter , Ta Michael , Iwaki Hirotaka , Senkevich Konstantin , Yu Eric , Alcalay Roy N. , Gan-Or Ziv 
Published: September 2024

AbstractGBA1variants and decreased glucocerebrosidase (GCase) activity are implicated in Parkinson’s disease (PD). We investigated the hypothesis that increased levels of glucosylceramide (GlcCer), one of GCase main substrates, are involved in PD pathogenesis. Using multiple genetic methods, we show thatATP10D, notGBA1, is the main regulator of plasma GlcCer levels, yet it is not involved in PD pathogenesis. Plasma GlcCer levels were associated with PD, but not in a causative manner, and are not predictive of disease status. These results argue against targeting GlcCer inGBA1-PD and underscore the need to explore alternative mechanisms and biomarkers for PD.
Covidization and decovidization of the scientific literature and scientific workforce
Authors: Ioannidis John P. A. , Collins Thomas A. , Bendavid Eran , Baas Jeroen 
Published: September 2024

AbstractWe examined the growth trajectory and impact of COVID-19-related papers in the scientific literature until August 1, 2024 and how the scientific workforce was engaged in this work. Scopus indexed 718,660 COVID-19-related publications. As proportion of all indexed scientific publications, COVID-19-related publications peaked in September 2021 (4.7%) remained at 4.3-4.6% for another year and then gradually declined, but was still 1.9% in July 2024). COVID-19-related publications included 1,978,612 unique authors: 1,127,215 authors had ≥5 full papers in their career and 53,418 authors were in the top-2% of their scientific subfield based on a career-long composite citation indicator. Authors with >10%, >30% and >50% of their total career citations be to COVID-19-related publications were 376,942, 201,702, and 125,523, respectively. As of August 1, 2024, 65 of the top-100 most-cited papers published in 2020 were COVID-19-related, declining to 24/100, 19/100, 7/100, and 5/100 for the most-cited papers published in 2021, 2022, 2023, and 2024, respectively. Across 174 scientific subfields, 132 had ≥10% of their active influential (top-2% by composite citation indicator) authors publish something on COVID-19 during 2020-2024. Among the 300 authors with highest composite citation indicator specifically for their COVID-19-related publications, 41 were editors or journalists/columnists and another 23 had most of their COVID-19 citations to published items other than full papers (opinion pieces/letters/notes). COVID-19 massively engaged the scientific workforce in unprecedented ways. As the pandemic ended, there has been a sharp decline in the overall volume and high impact of newly published COVID-19-related publications.Significance statementCOVID-19 massively mobilized the scientific workforce. Between 2020 and 2024, over 700,000 papers were published on COVID-19, including 2 million different authors. Across science, almost a third of authors at the top-2% of citation impact in their subfield published on COVID-19. There was a sharp decline in the proportion of COVID-19 papers across science after 2022 and an even more sharp decline in the proportion of COVID-19 papers reaching the highest level of citations. Authors with the highest COVID-19 citation impact prominently included many who were editors, journalists/columnists and opinion writers publishing massively. While other epidemics also witnessed sharp increases and subsequent decline in interest, the magnitude of the covidization and decovidization process is unique in the scientific literature to-date.
Improving Access and Efficiency of Acute Ischemic Stroke Treatment Across Four Canadian Provinces: A Stepped-Wedge Trial
Authors: Kamal Noreen , Cora Elena A. , Alim Simone , Goldstien Judah , Volders David , Aljendi Shadi , Williams Heather , Fok Patrick T. , van der Linde Etienne , Helm-Neima Trish , Cashin Renee , Metcalfe Brian , BNSc Julie Savoie , Simpkin Wendy , Chisholm Cassie , Hill Michael D , Menon Bijoy K. , Phillips Stephen ,   the ACTEAST Collaborators
Published: September 2024

AbstractBackgroundThe translation of standard-of-care in acute ischemic stroke reperfusion interventions into practice is well established, but multifactorial obstacles exist in the complete adoption, which has led to inequities in access and delivery of services. The objective of this study was to improve access and efficiency of ischemic stroke treatment across four Atlantic Canadian Provinces.MethodsA stepped-wedge cluster trial was conducted over 30 months with 3 clusters covering 34 sites. The trial was conducted across all 4 Atlantic Canadian provinces: Nova Scotia (NS), New Brunswick (NB), Prince Edward Island (PE), and Newfoundland and Labrador (NL). The design was quasi-randomized, with each cluster associated with one or more provinces: cluster 1 – NS; cluster 2 – NB and PE; and cluster 3 – NL. The patient population was all ischemic stroke patients across all 4 provinces. The intervention was a 6-month modified Quality Improvement Collaborative (mQIC), which was modified from the Breakthrough Series Collaborative to be half of the 1-year period and conducted virtually. The intervention consisted of assembling an interdisciplinary improvement team, 2 full-day workshops, webinars, and virtual site visits. Suggested changes included 6 process improvement strategies.ResultsOver the trial period, 8594 ischemic stroke patients were included, out of which 1576 patients received acute treatment. The proportion of patients that received treatment did not increase significantly with the intervention [0.4% increase for patients that received thrombolysis and/or EVT (p=0.68)]. Median door-to-needle time was reduced by 9.2 minutes with the intervention (p=0.01). Cluster 3 saw the greatest improvements in both access and efficiency.ConclusionsA mQIC intervention resulted in improvement of process measures like door-to-needle time. Quality improvement initiatives may need to be longer to allow full implementation and tailored for each health system to ensure that each system sees improvement. In-person activities might be critical to ensure fidelity of the intervention.
Introduction of cytosine-5 DNA methylation sensitizes cells to oxidative damage
Authors: Krwawicz J. , Sheeba C.J. , Hains K. , McMahon T. , Zhang Y. , Kriaucionis S. , Sarkies P. 
Published: September 2024

AbstractDNA methylation at the 5 position of cytosine (5mC) is an ancient epigenetic mark in eukaryotes. The levels of total 5mC vary enormously between different species, and the DNA methyltransferases that introduce 5mC have been repeatedly lost in several independent lineages. DNA methyltransferases are a threat to genomic stability due to the increased mutagenicity of 5mC bases and the propensity of DNA methyltransferases themselves to introduce DNA alkylation damage as an off-target effect. However, whether alkylation damage explains why 5mC is frequently lost in evolution is unclear. Here we tested the fitness consequences of DNA methyltransferase-induced alkylation damage by introducing a eukaryotic-like 5mC system intoE. coli. We showed that introducing 5mC genome-wide leads to increased sensitivity to alkylating agents, which is strongly enhanced by removal of the 3mC repair enzyme AlkB. Unexpectedly, we discovered that 5mC introduction led to increased sensitivity to oxidative stress. We showed that this is due to increased formation of reactive oxygen in the presence of 5mC. We determined that reactive oxygen species led to non-enzymatic oxidation of 5mC, producing modified cytosines such as 5fC that are recognised as DNA base damage inE. coli. Overall, our work identifies increased sensitivity to oxidative stress, as well as alkylating agents, as a negative consequence of genome-wide 5mC. Oxidative stress is frequently encountered by organisms in their environment, thus offering a plausible reason for total loss of 5mC in some species.
Proof of Concept for High-Dose Cannabidiol Pretreatment to Antagonize Opioid Induced Persistent Apnea
Authors: Wiese Beth M. , Bondarenko Evgeny , Feldman Jack L. 
Published: September 2024

AbstractUsing a mouse equivalent of FDA-approved cannabidiol (CBD) dosing, we found high dose CBD affects opioid induced persistent apnea (OIPA), the principal cause of opioid related fatalities. CBD pretreatment mitigated respiratory depression from fentanyl in awake mice and significantly delayed OIPA onset in anesthetized mice, effective as the opioid antagonist naloxone. The powerful effect of CBD pretreatment on OIPA suggests a novel therapeutic strategy to reduce fatal opioid overdose incidence.