bluuebunny/crossref_metadata_2025_split huggingface dataset:
Type I interferon governs immunometabolic checkpoints that coordinate inflammation duringStaphylococcalinfection
Authors: Reynolds Mack B. , Klein Benjamin , McFadden Michael J. , Judge Norah K. , Navarrete Hannah E. , Michmerhuizen Britton C , Awad Dominik , Schultz Tracey L. , Harms Paul W. , Zhang Li , O’Meara Teresa R. , Sexton Jonathan Z. , Lyssiotis Costas A. , Kahlenberg J. Michelle , O’Riordan Mary X. 
Published: January 2024

SummaryFine-tuned inflammation during infection enables pathogen clearance while minimizing host damage. Inflammation regulation depends on macrophage metabolic plasticity, yet coordination of metabolic and inflammatory programs is underappreciated. Here we show that type I interferon (IFN) temporally guides metabolic control of inflammation during methicillin-resistant Staphylococcus aureus (MRSA) infection. In macrophages, staggered Toll-like receptor and type I IFN signaling permitted a transient respiratory burst followed by inducible nitric oxide synthase (iNOS)-mediated OXPHOS disruption. OXPHOS disruption promoted type I IFN, suppressing other pro-inflammatory cytokines, notably IL-β. iNOS expression peaked at 24h post-infection, followed by lactate-driven iNOS repression via histone lactylation. In contrast, type I IFN pre-conditioning sustained infection-induced iNOS expression and amplified type I IFN. Cutaneous MRSA infection in mice constitutively expressing epidermal type I IFN led to elevated iNOS levels, impaired wound healing, vasculopathy, and lung infection. Thus, kinetically regulated type I IFN signaling coordinates immunometabolic checkpoints that control infection-induced inflammation.Graphical abstract
Devaluing memories of reward: A case for dopamine
Authors: Fry B.R. , Russell N. , Fex V. , Mo B. , Pence N. , Beatty J.A , Manfreddsson F. P. , Toth B.A. , Burgess C.R. , Gershman S. , Johnson A.W. 
Published: January 2024

AbstractWe describe a novel role for dopamine in devaluing sensory memories of reward. Mesencephalic dopamine cells activated during a mediated devaluation phase were later chemogenetically reactivated. This retrieval of the devalued reward memory elicited a reduction in the hedonic evaluation of sucrose reward. Through optogenetic and chemogenetic manipulations, we confirm dopamine cells are both sufficient and necessary for mediated devaluation, and retrieval of these memories reflected dopamine release in the nucleus accumbens. Consistent with our computational modelling data, our findings indicate a critical role for dopamine in encoding predictive representations of the sensory features of reinforcement. Overall, we illuminate the elaborate nature of reinforcement signals encoded by dopamine and suggest novel approaches to treating a host of psychobiological disorders.
Stopping Speed in Response to Auditory and Visual Stop Signals Depends on Go Signal Modality
Authors: Weber Simon , Salomoni Sauro E. , St George Rebecca J. , Hinder Mark R. 
Published: January 2024

AbstractPast research has found that the speed of the action cancellation process is influenced by the sensory modality/modalities of the environmental change that triggers it. However, the effect on selective stopping processes (where participants must cancel only one component of a multi-component movement) remains unknown, despite these complex movements often being required as we navigate our busy modern world.Thirty healthy adults (mean age = 31.1 years, SD = 10.5) completed five response-selective stop signal tasks featuring different combinations of “go signal” modality (the environmental change baring an imperative to initiate movement; auditory or visual) and “stop signal” modality (the environmental change indicating that action cancellation is required; auditory, visual, or audiovisual). Electromyographical (EMG) recordings of effector muscles allowed detailed comparison of the characteristics of voluntary action and cancellation between tasks.Behavioural and physiological measures of stopping speed demonstrated that the modality of thegosignal influenced how quickly participants cancelled movement in response to the stop signal: stopping was faster in two cross-modal experimental conditions (auditory go - visual stop; visual go - auditory stop), than in two conditions using the same modality for both signals. A separate condition testing for multisensory facilitation revealed that stopping was fastest when the stop signal consisted of acombinedaudiovisual stimulus, compared to all other go-stop stimulus combinations. These findings provide novel evidence regarding the role of attentional networks in action cancellation and suggest modality specific cognitive resources influence the latency of the stopping process.
Improved Detection of Drug-Induced Liver Injury by Integrating Predictedin vivoandin vitroData
Authors: Seal Srijit , Williams Dominic P. , Hosseini-Gerami Layla , Mahale Manas , Carpenter Anne E. , Spjuth Ola , Bender Andreas 
Published: January 2024

ABSTRACTDrug-induced liver injury (DILI) has been significant challenge in drug discovery, often leading to clinical trial failures and necessitating drug withdrawals. The existing suite of in vitro proxy-DILI assays is generally effective at identifying compounds with hepatotoxicity. However, there is considerable interest in enhancing in silico prediction of DILI because it allows for the evaluation of large sets of compounds more quickly and cost-effectively, particularly in the early stages of projects. In this study, we aim to study ML models for DILI prediction that first predicts nine proxy-DILI labels and then uses them as features in addition to chemical structural features to predict DILI. The features includein vitro(e.g., mitochondrial toxicity, bile salt export pump inhibition) data,in vivo(e.g., preclinical rat hepatotoxicity studies) data, pharmacokinetic parameters of maximum concentration, structural fingerprints, and physicochemical parameters. We trained DILI-prediction models on 888 compounds from the DILIst dataset and tested on a held-out external test set of 223 compounds from DILIst dataset. The best model, DILIPredictor, attained an AUC-ROC of 0.79. This model enabled the detection of top 25 toxic compounds compared to models using only structural features (2.68 LR+ score). Using feature interpretation from DILIPredictor, we were able to identify the chemical substructures causing DILI as well as differentiate cases DILI is caused by compounds in animals but not in humans. For example, DILIPredictor correctly recognized 2-butoxyethanol as non-toxic in humans despite its hepatotoxicity in mice models. Overall, the DILIPredictor model improves the detection of compounds causing DILI with an improved differentiation between animal and human sensitivity as well as the potential for mechanism evaluation. DILIPredictor is publicly available athttps://broad.io/DILIPredictorfor useviaweb interface and with all code available for download and local implementation viahttps://pypi.org/project/dilipred/.GRAPHICAL ABSTRACT
Neuromark PET: A multivariate method for estimating whole brain fMRI guided intrinsic networks and connectomes from fMRI and PET data
Authors: Saha Debbrata K. , Bohsali Anastasia , Saha Rekha , Hajjar Ihab , Calhoun Vince D. 
Published: January 2024

AbstractPositron emission tomography (PET) and magnetic resonance imaging (MRI) are both widely used neuroimaging techniques to study brain functional and molecular connec-tivity. Although whole brain resting functional MRI (fMRI) connectomes (a matrix describing the inter-regional connectivity patterns) are widely used, the integration or association of whole brain molecular connectomes with PET data are rarely done. This likely stems from the fact that PET data is typically analyzed by using a region of inter-est approach, while whole brain spatial networks and their connectivity (covariation) receive much less attention. As a result, to date, there have been little focus on di-rectly comparing whole brain PET and fMRI connectomes. In this study, we present a method that uses spatially constrained independent component analysis (scICA) (uti-lizing fMRI components as spatial priors) to estimate corresponding (Amyloid) PET and fMRI connectomes and examine the relationship between them using datasets that include individuals with mild cognitive impairment (MCI). Our results demonstrate highly modularized PET connectome patterns that complement those identified from resting fMRI. In particular, fMRI showed strong intra-domain connectivity with inter-domain anticorrelation in sensorimotor and visual domains as well as default mode network. PET amyloid data showed similar strong intra-domain effects, but showed much higher correlations within cognitive control and default mode domains, as well as anticorrelation between cerebellum and other domains. The estimated fMRI informed PET networks have similar, but not identical, network spatial patterns to the resting fMRI networks, with the fMRI informed PET networks being slightly smoother and, in some cases, showing variations in subnodes. To further compare the two modalities, we also analyzed the differences between individuals with MCI receiving medication versus a placebo. Results show both common and modality specific treatment effects on fMRI and PET connectomes. From our fMRI analysis, we observed higher connec-tivity differences in various regions, such as the connection between the thalamus and middle occipital gyrus, as well as the insula and right middle occipital gyrus. Mean-while, the PET analysis revealed increased activation between the anterior cingulate cortex and the left inferior parietal lobe, along with other regions, in individuals who received medication versus placebo. In sum, our novel approach identifies correspond-ing whole-brain fMRI informed PET and fMRI networks and connectomes. While we observed common patterns of network connectivity, our analysis of the MCI treatment and placebo groups revealed that each modality captures modality and group specific information about brain networks, highlighting differences between the two groups in both network expression and network connectivity.
An arms race between 5’ppp-RNA virus and its alternative recognition receptor MDA5 in RIG-I-lost teleost fish
Authors: Geng Shang , Lv Xing , Zheng Weiwei , Xu Tianjun 
Published: January 2024

AbstractThe incessant arms race between viruses and hosts has led to numerous evolutionary innovations that shape life’s evolution. During this process, the interactions between viral receptors and viruses have garnered significant interest since viral receptors are cell surface proteins exploited by viruses to initiate infection. Our study sheds light on the arms race between the MDA5 receptor and 5’ppp-RNA virus in a lower vertebrate fish,M. miiuy. Firstly, the frequent and independent loss events of RIG-I in vertebrates prompted us to search for alternative immune substitutes, with homology-dependent genetic compensation response (HDGCR) being the main pathway. Our further analysis suggested that MDA5 ofM. miiuy and G. gallus, the homolog of RIG-I, can replace RIG-I in recognizing 5’ppp-RNA virus, which may lead to redundancy of RIG-I and loss from the species genome during evolution. Secondly, as an adversarial strategy, 5’ppp-RNA SCRV can utilize the m6A methylation mechanism to degrade MDA5 and weaken its antiviral immune ability, thus promoting its own replication and immune evasion. In summary, our study provides a snapshot into the interaction and coevolution between vertebrate and virus, offering valuable perspectives on the ecological and evolutionary factors that contribute to the diversity of the immune system.
Assessing complex member composition and insecticide resistance status ofAnopheles gambiae s.l.in three coastal health districts of Côte d’Ivoire
Authors: Kouamé Jackson IK , Edi Constant VA , Zahouli Julien BZ , Kouamé Ruth MA , Kacou Yves AK , Yokoly Firmain N , Gbalegba Constant GN , Malone David , Koudou Benjamin G 
Published: January 2024

AbstractAlthough malaria is endemic in Coastal Côte d’Ivoire, updated data on the resistance profile of the main vector,Anopheles gambiae sensu lato(s.l.), are still lacking, thus compromising decision-making for an effective vector control intervention. This study investigated the complex members and the insecticide resistance in theAnopheles gambiae s.l.populations in coastal Côte d’Ivoire. Between 2018 and 2020, bioassays were conducted on femaleAn. gambiae s.l.mosquitoes in three coastal health districts (Aboisso, Jacqueville and San Pedro) of Côte d’Ivoire. Pyrethroids deltamethrin, permethrin and alphacypermethrin (1X, 5X and 10X), clothianidin and synergist piperonyl butoxide (PBO) combined with pyrethroid 1X were tested using WHO tube bioassays. Chlorfenapyr was evaluated using CDC bottle bioassays.An. gambiaecomplex members andVgsc995F,Vgsc995S and Ace-1 280S mutations were identified using polymerase chain reaction (PCR) technique. Overall,Anopheles. gambiae s.l.populations were primarily composed ofAnopheles coluzzii(88.24%, n = 312), followed byAnopheles gambiae sensu stricto(s.s.) (7.56%) and hybrids (4.17%). These populations displayed strong resistance to pyrethroids at standard diagnostic doses, with mortality remaining below 98% even at 10X doses, except for alphacypermethrin in Aboisso. Pre-exposure to PBO significantly increased mortality but did not fully restore susceptibility, except for alphacypermethrin in Jacqueville. Clothianidin restored full susceptibility in Jacqueville and San Pedro, while chlorfenapyr restored susceptibility in Aboisso at 100 µg ai/bottle and all three districts at 200 μg ai/bottle.Vgsc995F mutation dominated, with frequencies varying from 71.2% to 79.3%.Vgsc995S had low, and showed frequencies ranging from 2.3% to 5.7%. Ace-1 280S prevalence varied between 4.2% and 42.9%. Coastal Côte d’Ivoire’sAn. gambiae s.l.populations were mainly composed ofAnopheles coluzziiand showed high resistance to pyrethroids. Clothianidin, chlorfenapyr, and PBO with pyrethroids increased mortality, indicating their potential use as an alternative for malaria vector control.
Transient anti-interferon autoantibodies in the airways are associated with efficient recovery from COVID-19
Authors: Babcock Benjamin R. , Kosters Astrid , Eddins Devon J. , Donaire Maria Sophia Baluyot , Sarvadhavabhatla Sannidhi , Pae Vivian , Beltran Fiona , Murray Victoria W. , Gill Gurjot , Xie Guorui , Dobosh Brian S. , Giacalone Vincent D. , Tirouvanziam Rabindra M. , Ramonell Richard P. , Jenks Scott A. , Sanz Ignacio , Lee F. Eun-Hyung , Roan Nadia R. , Lee Sulggi A. , Ghosn Eliver E. B. 
Published: January 2024

ABSTRACTPre-existing anti-interferon alpha (anti-IFN-α) autoantibodies in blood are associated with susceptibility to life-threatening COVID-19. However, it is unclear whether anti-IFN-α autoantibodies in the airways – the initial site of infection – can also determine disease outcomes. In this study, we developed a new multiparameter technology, flowBEAT, to quantify and profile the isotypes of anti-IFN-α and anti-SARS-CoV-2 antibodies in longitudinal samples collected over 20 months from the airway and matching blood of 129 donors with mild, moderate, and severe COVID-19. We found unexpectedly that nasal anti-IFN-α autoantibodies were induced post-infection onset in more than 70% of mild to moderate COVID-19 cases and associated with robust anti-SARS-CoV-2 immunity, fewer symptoms, and efficient recovery. Nasal anti-IFN-α autoantibodies followed the peak of host IFN-α production and waned with disease recovery, revealing a regulated balance between IFN-α and anti-IFN-α response. Notably, only a subset of mild to moderate patients progressed to develop systemic anti-IFN-α, which correlated with systemic inflammation and worsened symptoms. In contrast, patients with life-threatening COVID-19 sustained elevated anti-IFN-α in both airways and blood, coupled with uncontrolled viral load and IFN-α production. Our studies thereby reveal a novel protective role for nasal anti-IFN-α autoantibodies in the immunopathology of COVID-19 and, more broadly, suggest that anti-IFN-α may serve an important regulatory function to restore homeostasis following viral invasion of the respiratory mucosa.
Promoting healthy and sustainable diets through food service interventions in university settings: a scoping review
Authors: Kratzer Suzie , Theurich Melissa A. , Mareis Theresa , Pröbstl Simone , Holliday Nicole , Yan Sebrina , Leibinger Anna , Monsef Ina , Bach Leonie , Schwingshackl Lukas , Simonetti Aline , Hartmann Monika , Lemken Dominic , von Philipsborn Peter 
Published: January 2024

AbstractBackgroundFood service operations in universities and colleges, such as cafeterias and canteens, may support healthy and sustainable diets among students and staff and contribute to a transformation of the wider food system. Multiple studies on interventions to promote health and sustainability in this setting have been conducted, but no up-to-date, comprehensive review exists. This study aims to fill this gap.MethodsWe used state-of-the-art scoping review methodology. We included any study examining interventions in university or college food service settings aimed at, or potentially suitable for: 1), supporting healthy and/or sustainable diets, 2) reducing food waste, or 3) otherwise increasing the sustainability of the food service operation (e.g. by improving energy efficiency). We considered studies using any study design published in any language without publication date restrictions. We comprehensively searched six academic databases and conducted forward and backward citation searches. We extracted and charted data on key study characteristics, including the reported direction of effects/associations.ResultsWe identified 206 studies reporting on 273 interventions. Most studies (71%) used quasi- experimental study designs, were conducted in North America (53%) or Europe (34%), and were implemented in cafeterias or canteens (76%). The most common intervention types were labelling interventions (26%), improved or increased offerings of healthy and/or sustainable food and beverage options (24%), and information and awareness-raising interventions (18%). The most commonly assessed outcomes were implementation-related (e.g. costs, feasibility, acceptability), diet-related (e.g. sales or consumption of specific foods), and sustainability-related (e.g. carbon footprint). Most, but not all, studies reported mostly effects in the desired direction (e.g. increased vegetable consumption, or decreased food waste).DiscussionMultiple approaches for promoting health and sustainability in university and college food service settings exist. The findings of this review suggest that such interventions can be effective, feasible, cost-effective, and aligned with customer and stakeholder expectations. We therefore suggest that they are considered for implementation more widely. Implementation should be accompanied by monitoring and methodologically robust evaluations to allow for evidence-informed tailoring and adjustments and to improve the existing evidence base.
Deep representation learning for clustering longitudinal survival data from electronic health records
Authors: Qiu Jiajun , Hu Yao , Li Li , Erzurumluoglu Abdullah Mesut , Braenne Ingrid , Whitehurst Charles , Schmitz Jochen , Arora Jatin , Bartholdy Boris Alexander , Gandhi Shrey , Khoueiry Pierre , Mueller Stefanie , Noyvert Boris , Ding Zhihao , Jensen Jan Nygaard , de Jong Johann 
Published: January 2024

AbstractPrecision medicine requires accurate identification of clinically relevant patient subgroups. Electronic health records provide major opportunities for leveraging machine learning approaches to uncover novel patient subgroups. However, many existing approaches fail to adequately capture complex interactions between diagnosis trajectories and disease-relevant risk events, leading to subgroups that can still display great heterogeneity in event risk and underlying molecular mechanisms. To address this challenge, we implemented VaDeSC-EHR, a transformer-based variational autoencoder for clustering longitudinal survival data as extracted from electronic health records. We show that VaDeSC-EHR outperforms baseline methods on both synthetic and real-world benchmark datasets with known ground-truth cluster labels. In an application to Crohn’s disease, VaDeSC-EHR successfully identifies four distinct subgroups with divergent diagnosis trajectories and risk profiles, revealing clinically and genetically relevant factors in Crohn’s disease. Our results show that VaDeSC-EHR can be a powerful tool for discovering novel patient subgroups in the development of precision medicine approaches.
Prolonged time to breast cancer surgery and the risk for metastasis
Authors: Hölzel Dieter , Schlesinger-Raab Anne , Schubert-Fritschle Gabriele , Halfter Kathrin 
Published: January 2024

AbstractBackgroundA growing breast cancer (BC) is associated with an inherent risk of metastasis (MET). If surgical treatment of a BC is delayed, the prognosis worsens continuously with increasing tumor diameter (TD). This frequently overlooked topic in healthcare is currently the subject of debate.MethodsPopulation-based data on BC incidence and surgery waiting period for the U.S. and Germany are used to examine the resulting risks. BC growth and initiation of MET are calculated in a simulation approach using hormone receptor status (HR), tumor volume doubling time (VDT), and TD- dependent survival.ResultsThe U.S. and Germany report 287,850/71,375 BCs annually. Based on an initial mean TD of 19.8mm 15-year mortality in both countries is estimated using a Gompertz function at 19.6% without surgical delay. VDT of HR+ and HR- BCs differs by a factor of 2.4, leading to an estimated mortality increase of 1.34/3.26% (HR+/HR-) if all surgical procedures are pushed back by five weeks. The mean delay in the U.S. and Germany is 33.7/26.0 days respectively. Prolonged waiting periods lead to estimated 4,676/918 additional BC deaths or a 1.6/1.2% rise in BC mortality rate. Further increases are due to MET relapse up to 25 years after diagnosis.ConclusionsA growing tumor can continuously initiate MET with every millimeter. The results of this study offer replicable and valid evidence, based on publicly available clinical and population-based data, that confirmed BCs should be treated according to HR status as soon as possible.
Impact of genome build on RNA-seq interpretation and diagnostics
Authors: Ungar Rachel A. , Goddard Pagé C. , Jensen Tanner D. , Degalez Fabien , Smith Kevin S. , Jin Christopher A. ,   Undiagnosed Diseases Network, Bonner Devon E. , Bernstein Jonathan A. , Wheeler Matthew T. , Montgomery Stephen B. 
Published: January 2024

SummaryTranscriptomics is a powerful tool for unraveling the molecular effects of genetic variants and disease diagnosis. Prior studies have demonstrated that choice of genome build impacts variant interpretation and diagnostic yield for genomic analyses. To identify the extent genome build also impacts transcriptomics analyses, we studied the effect of the hg19, hg38, and CHM13 genome builds on expression quantification and outlier detection in 386 rare disease and familial control samples from both the Undiagnosed Diseases Network (UDN) and Genomics Research to Elucidate the Genetics of Rare Disease (GREGoR) Consortium. We identified 2,800 genes with build-dependent quantification across six routinely-collected biospecimens, including 1,391 protein-coding genes and 341 known rare disease genes. We further observed multiple genes that only have detectable expression in a subset of genome builds. Finally, we characterized how genome build impacts the detection of outlier transcriptomic events. Combined, we provide a database of genes impacted by build choice, and recommend that transcriptomics-guided analyses and diagnoses are cross-referenced with these data for robustness.