bluuebunny/crossref_metadata_2025_split huggingface dataset:
Ethical and Social Considerations of Applying Artificial Intelligence in Healthcare; a Two-Pronged Scoping Review
Authors: Ratti Emanuele 
Published: February 2025

AbstractBackgroundArtificial Intelligence (AI) is being designed, tested, and in many cases actively employed in almost every aspect of healthcare from primary care to public health. It is by now well established that any application of AI carries an attendant responsibility to consider the ethical and societal aspects of its development, deployment and impact. However, in the rapidly developing field of AI, developments such as machine learning, neural networks, generative AI, and large language models have the potential to raise new and distinct ethical and social issues compared to, for example, automated data processing or more ‘basic’ algorithms.MethodsThis article presents a scoping review of the ethical and social issues pertaining to AI in healthcare, with a novel two-pronged design. One strand of the review (SR1) consists of a broad review of the academic literature restricted to a recent timeframe (2021-23), to better capture up to date developments and debates. The second strand (SR2) consists of a narrow review, limited to prior systematic and scoping reviews on the ethics of AI in healthcare, but extended over a longer timeframe (2014-2024) to capture longstanding and recurring themes and issues in the debate. This strategy provides a practical way to deal with an increasingly voluminous literature on the ethics of AI in healthcare in a way that accounts for both the depth and evolution of the literature.ResultsSR1 captures the heterogeneity of audience, medical fields, and ethical and societal themes (and their tradeoffs) raised by AI systems. SR2 provides a comprehensive picture of the way scoping reviews on ethical and societal issues in AI in healthcare have been conceptualized, as well as the trends and gaps identified.ConclusionOur analysis shows that the typical approach to ethical issues in AI, which is based on the appeal to general principles, becomes increasingly unlikely to do justice to the nuances and specificities of the ethical and societal issues raised by AI in healthcare, as the technology moves from abstract debate and discussion to real world situated applications and concerns in healthcare settings.
Human genomic regions of systemic interindividual epigenetic variation are implicated in neurodevelopmental and metabolic disorders
Authors: Chang Wen-Jou , Maduranga Uditha , Gunasekara Chathura J. , Yang Alan , Hirschtritt Matthew , Rodriguez Katrina , Coarfa Cristian , Jun Goo , Hanis Craig L. , Flanagan James M. , Gorlov Ivan P. , Amos Christopher I. , Wiemels Joseph L. , Schaefer Catherine A. , Susser Ezra S. , Waterland Robert A. 
Published: February 2025

AbstractEpigenome-wide association studies (EWAS) profile DNA methylation across the human genome to identify associations with diseases and exposures. Most employ Illumina methylation arrays; this platform, however, under-samples interindividual epigenetic variation. The systemic and stable nature of epigenetic variation at correlated regions of systemic interindividual variation (CoRSIVs) should be advantageous to EWAS. Here, we analyze 2,203 published EWAS to determine whether Illumina probes within CoRSIVs are over-represented in the literature. Enrichment of CoRSIV-overlapping probes was observed for most classes of disease, particularly for neurodevelopmental disorders and type 2 diabetes, indicating an opportunity to improve the power of EWAS by over 200- and over 100-fold, respectively. EWAS targeting all known CoRSIVs should accelerate discovery of associations between individual epigenetic variation and risk of disease.
High Tau Expression Correlates with Reduced Invasion and Prolonged Survival in Ewing Sarcoma
Authors: Cidre-Aranaz Florencia , Magrin Claudia , Zimmermann Malenka , Li Jing , Baffa Anna Lisa , Ciccaldo Matteo , Hartmann Wolfgang , Dirksen Uta , Sola Martina , Paganetti Paolo , Grünewald Thomas G P , Papin Stéphanie 
Published: February 2025

AbstractThe microtubule-associated protein Tau (encoded by theMAPTgene) is linked to a family of neurodegenerative disorders defined as tauopathies, which are characterized by its brain accumulation in neurofibrillary tangles and neuropil threads. Newly described Tau functions comprise DNA protection, chromatin remodeling, p53 regulation and cell fate modulation, suggesting a role of Tau in oncogenesis. Bioinformatic-supported characterization of Tau in cancer reveals robust expression in bone cancer cells, in particular Ewing sarcoma (EwS) cell lines. EwS is an aggressive cancer caused by a fusion of members of theFETandETSgene families, primarilyEWSR1::FLI1. Here we found thatMAPTis a EWSR1::ETS target gene and that higher Tau expression in EwS cells inhibited their migratory and invasive behavior, consistent with a more immobile and proliferative phenotype observed in EwS. Indeed, we report that high Tau expression is associated with improved overall survival of EwS patients. We also show that the sessile but proliferative phenotype of EWSR1::ETS-high cells may result from a modulatory role of Tau on focal adhesion to extracellular matrix proteins. Our data highlight the utility of determining Tau expression as a prognostic factor in EwS as well as the opportunity to target Tau expression as an innovative EwS therapy.
Precise engineering of chimeric antigen receptor expression levels defines T cell identity and function
Authors: Ramos Andrew S. , Simon Sylvain , Siller-Farfan Jesus , Rajan Anusha , Revale Santiago , Zanchini di Castiglionchio Elena , Pelea Oana , Fulga Tudor A. , Riddell Stanley , Dushek Omer , Michaels Yale S. , Sauka-Spengler Tatjana 
Published: February 2025

AbstractChimeric Antigen Receptor (CAR) T therapy is a potent treatment for haematological malignancies, but T cell exhaustion reduces its efficacy in many patients. Although high CAR transgene levels appear to drive T cell exhaustion, the relationship between CAR expression levels, T cell function, and transcriptional identity is yet to be mapped at high resolution. Here, we harness a high-resolution microRNA-based control system to precisely modulate CAR transgene expression levels and assess the impact on T cell activation, gene expression and function. By post-transcriptionally modulating CAR abundance, we show that differential CAR levels significantly impact T cell proliferation, cytokine production and tonic signalling. T cells with high CAR expression become strongly activated even at low target antigen densities, while those with low CAR expression are triggered only by high concentrations of their target. Single-cell RNA sequencing of primary T cells expressing a broad range of CAR transcript levels revealed global transcriptional programmes that become dysfunctional with increased CAR abundance, expanding our understanding of T cell exhaustion. Notably, we identified a narrow CAR expression range where the exhaustion transcriptional state is not triggered, demonstrating that T cell exhaustion can be controlled by fine-tuning CAR levels. This work demonstrates that CAR expression levels are key determinants of T cell transcriptional identity and function and introduces a tractable method to precisely tune CAR expression and T cell activity.
High density probes reveal medullary seizure and rapid medullary shutdown in a model of fatal apnea in seizure
Authors: Budde Ryan , RoaFiore Laura , Irazoqui Pedro 
Published: February 2025

ABSTRACTObjectiveSudden unexpected death in epilepsy (SUDEP) is suggested to be a cardiorespiratory collapse that occurs shortly after a seizure. Prior work in rats suggests that reflexive apneas (produced by stimulation of trigeminal or vagal peripheral sensory targets) is highly fatal during seizure but well tolerated otherwise. These reflexes share network connectivity in the medulla, particularly the caudal solitary nucleus (NTS) and ventral respiratory column (VRC), and possibly other intermediate structures. We sought to observe the electrographic activity in these regions.MethodsWe use urethane anesthetized long evans rats. We utilized either 125μm silver wire in the caudal NTS or a Neuropixel 1.0 probe along a dorsoventral trajectory that spanned the caudal NTS to the VRC. We additionally recorded cardiorespiratory activity via several methods. We induced a reflexive apnea – the diving reflex – by nasal irrigation of cold water for several seconds, which produces a period of apnea, then gasping, and then a gradual return to eupnea. We repeated several trials while the animal was healthy and subsequently induced continuous seizure activity with kainate and repeated the reflexes, which are ultimately fatal during seizure.ResultsSeizure activity confounds many established methods of analyzing high-density single unit data such as provided by Neuropixels probes, and so our analyses focus on averaging responses over larger anatomical regions (120μm) covering small populations of neurons. Seizure produces broad increases in neuronal activity across the medullary tract, which by itself is not dangerous. Ictal reflexive apneas were broadly more inhibitory (producing a reduction in firing rate) than they were preictally, and fatal ictal responses resulted in a very rapid shutdown of all medullary activity. We only rarely observed ictal central apneas (apneas with no apparent stimuli), but when we did they were apparently safe, always survived, and produced no significant change in network activity (neither increase nor decrease).ConclusionsThese data support the theory that central apnea events in seizure are relatively safe as we observed they produce little change in the medullary tract network, while stimuli-induced-reflexive-apneas are dangerous because they produce profound quieting across respiratory centers. Our data suggest that seizure spreads to this medullary tract at approximately the same rate and intensity as forebrain, as previously described in this model. These data are supportive of SUDEP mechanisms involving brainstem inhibition as a primary cause, such as spreading depolarization waves. These findings likely extend beyond nasal irrigation to any sensory reflexive apnea caused by airway irritation of any kind, and may bear relevance to similar deaths seen in infants.
Genome-wide association study of susceptibility to acute respiratory distress syndrome
Authors: Guillen-Guio Beatriz , Suarez-Pajes Eva , Tosco-Herrera Eva , Hernandez-Beeftink Tamara , Lorenzo-Salazar Jose Miguel , Chang Diana , González-Montelongo Rafaela , Rubio-Rodríguez Luis A. , Leavy Olivia C. , Allen Richard J. , Corrales Almudena , Cruz Raquel , Bardají-Carrillo Miguel , Carracedo Angel , Tamayo Eduardo , Kerchberger V. Eric , Ware Lorraine B. , Yaspan Brian L. , Scholz Markus , Scherag André , Villar Jesús , Wain Louise V. , Flores Carlos 
Published: February 2025

AbstractIntroductionAcute respiratory distress syndrome (ARDS) is a severe inflammatory process of the lung, often due to sepsis, and poses significant mortality burden in intensive care units. Here we conducted the largest genome-wide association study (GWAS) of sepsis-associated ARDS to identify novel genetic risk loci that can help guide the development of new therapeutic options.MethodsWe performed a case-control GWAS in 716 patients with sepsis-associated ARDS and 4,399 at-risk sepsis controls from three independent studies. Results were meta-analysed across the three studies, with significance set atp<5×10-8. Suggestive associations were declared for variants exhibiting consistent effects, likely to replicate and nominal significance (p<0.05) in all three studies. Prioritised loci were subjected to Bayesian fine mapping,in-silicofunctional assessments, and gene-based rare variant collapsing analysis using whole exome sequencing (WES) data. Two independent studies with 430 ARDS cases and 1,398 controls served as replication samples.ResultsWe identified a variant showing genome-wide significant association with sepsis-associated ARDS risk intergenic toANKRD31andHMGCR, previously linked to cholesterol metabolism. Suggestive associations were found for eight other variants. The rare exonic variant analysis showed associations betweenHMGCRandPOC5and sepsis-associated ARDS at nominal level (p<0.05). While no nominal significance was achieved in the two additional validation cohorts, three variants exhibited a consistent direction of effects across all 5 studies.ConclusionA common variant intergenic toANKRD31andHMGCRwas associated with sepsis-associated ARDS risk, suggesting a link between cholesterol metabolism and ARDS risk. Validation in independent studies is needed.
The Link to Oxidative Metabolism Varies across rs-fMRI Metrics: A Whole-Brain Assessment Using Macrovascular Correction
Authors: Zhong Xiaole Z. , Van Lankveld Hannah , Chen J. Jean 
Published: February 2025

AbstractOne of the major obstacles to the clinical application of resting-state functional magnetic resonance imaging (rs-fMRI) is the complex nature of its measurements, which limits interpretability. An approach to enhance the interpretability of the rs-fMRI metrics is to link them to more fundamental brain physiology, especially cerebral metabolism. Previous studies have established associations between glucose metabolism (CMRglu) and rs-fMRI measurements. In spite of this, oxidative metabolism (CMRO2) is more closely related to cerebral blood flow (CBF) and thus the BOLD signal, and its relationship with CMRgluis complex. Additionally, most currently published rs-fMRI metrics are uncorrected for macrovascular contribution, which may obscure the neuronal contributions. In this study, we measured resting CMRO2(along with the oxygen extraction fraction, OEF and cerebral blood flow, CBF) using gas-free calibrated fMRI. We used linear mixed-effects (LME) models to examine associations between CMRO2and various rs-fMRI metrics before and after macrovascular correction. We found that: 1) significant associations exist between CMRO2and multiple rs-fMRI metrics, with the strongest association found for the global functional density (gFCD) and the weakest for seed-based functional connectivity (FC); 2) associations with rs-fMRI metrics also varied for OEF and CBF; 3) significant sex differences were observed in the above associations; 4) the use of macrovascular correction substantially strengthened the goodness fit of all LME models examined. This latter improvement further validates the use of macrovascular correction in rs-fMRI. These results provide a framework for linking rs-fMRI metrics to fundamental brain physiology, thus improving interpretability of rs-fMRI measurements. This is the first study to formally link whole-brain MRI-based baseline CMRO2and rs-fMRI metrics, and helps to push the envelope for rs-fMRI in future clinical applications.
Learning decouples accuracy and reaction time for rapid decisions in a transitive inference task
Authors: Munoz Fabian , Jensen Greg , Shinn Maxwell , Alkan Yelda , Murray John D. , Terrace Herbert S. , Ferrera Vincent P. 
Published: February 2025

AbstractThe accumulation of evidence over time formalized in the drift diffusion model (DDM), has become one of the most prevalent models of deliberative decision-making. To better understand the role of latent variables during a serial learning task, in which decisions were made rapidly and did not show typical accuracy and response time patterns, we fit behavioral data with a DDM using PyDDM (Shinn et al., 2020). We trained macaque monkeys (N = 3) on a transitive inference transfer task in which they learned the implied order in a ranked list of 7 novel pictures in each behavioral session, indicating their choices by making saccadic eye movements. They reliably learned each new list order within 200-300 trials with asymptotic accuracy of around 80-90% correct. Their responses showed a symbolic distance effect, with 60% accuracy for adjacent list items and 90% accuracy for the largest symbolic distance. Although performance accuracy improved with learning and symbolic distance, reaction times were nearly constant. Nevertheless, accuracy and reaction time were well fit by the generalized drift- diffusion model. The fits were achieved by simultaneously increasing both the evidence accumulation rate and a collapsing bound to capture the shape of the reaction time distributions. These results indicate that decision-making during learning and transfer in a TI task may be characterized by a “variable collapsing bound” DDM.
A dendritic guidance receptor functions in both ligand dependent and independent modes
Authors: Reddy Anay R , Machera Sebastian J , Cook Zoe T , Özkan Engin , Shen Kang 
Published: February 2025

AbstractThe formation of an appropriately shaped dendritic arbor is critical for a neuron to receive information. Dendritic morphogenesis is a dynamic process involving growth, branching, and retraction. How the growth and stabilization of dendrites are coordinated at the molecular level remains a key question in developmental neurobiology. The highly arborized and stereotyped dendritic arbors of theCaenorhabditis elegansPVD neuron are shaped by the transmembrane DMA-1 receptor through its interaction with a tripartite ligand complex consisting of SAX-7, MNR-1, and LECT-2. However, receptor null mutants exhibit strongly reduced dendrite outgrowth, whereas ligand null mutants show disordered branch patterns, suggesting a ligand-independent function of the receptor. To test this idea, we identified point mutations indma-1that disrupt receptor-ligand binding and introduced corresponding mutations into the endogenous gene. We show that the ligand-free receptor is sufficient to drive robust, disordered dendritic branch formation but results in a complete loss of arbor shape. This disordered outgrowth program utilizes similar downstream effectors as the stereotyped outgrowth program, further arguing that ligand binding is not necessary for outgrowth. Finally, we demonstrate that ligand binding is required to maintain higher-order dendrites after development is complete. Taken together, our findings support a surprising model in which ligand-free and ligand-bound DMA-1 receptors have distinct functions: the ligand-free receptor promotes stochastic outgrowth and branching, whereas the ligand-bound receptor guides stereotyped dendrite morphology by stabilizing arbors at target locations.
Annotation Comparison Explorer (ACE): connecting brain cell types across studies of health and Alzheimer’s Disease
Authors: Miller Jeremy A. , Travaglini Kyle J. , Luquez Tain , Hostetler Rachel E. , Oster Aaron , Daniel Scott , Tasic Bosiljka , Menon Vilas 
Published: February 2025

ABSTRACTSingle-cell multiomic technologies have allowed unprecedented access to gene profiles of individual cells across species and organ systems, including >1000 papers focused on brain cell types alone. The Allen Institute has created foundational atlases characterizing mammalian brain cell types in the adult mouse brain and the neocortex of aged humans with and without Alzheimer’s disease (AD). With so many public cell type classifications (or ‘taxonomies’) available and many groups choosing to define their own, linking cell types and associated knowledge between studies remains a major challenge. Here, we introduce Annotation Comparison Explorer (ACE), a web application for comparing cell type assignments and other cell-based annotations (e.g., donor demographics, anatomic locations, batch variables, and quality control metrics). ACE allows filtering of cells and includes an interactive set of tools for comparing two or more taxonomy annotations alongside collected knowledge (e.g., increased abundance in disease conditions, cell type aliases, or other information about a specific cell type). We present three primary use cases for ACE. First, we demonstrate how a user can assign cell type labels from the Seattle Alzheimer’s Disease Brain Cell Atlas (SEA-AD) taxonomy to cells from their own study and compare these cell type mappings to existing cell type assignments and cell metadata. Second, we extend this approach to ten published human AD studies which we previously reprocessed through a common data analysis pipeline. This allowed us to compare brain taxonomies across otherwise incomparable studies and identify congruent cell type abundance changes in AD, including a decrease in abundance of subsets of somatostatin interneurons. Finally, ACE includes translation tables between different mouse and human brain cell type taxonomies publicly accessible on Allen Brain Map, from initial studies in individual neocortical areas to more recent studies spanning the whole brain. ACE can be freely and publicly accessed as a web application (https://sea-ad.shinyapps.io/ACEapp/) and on GitHub (github.com/AllenInstitute/ACE).
In harmony? A scoping review of methods to combine multiple 16S amplicon data sets
Authors: Li Zone , Chen Yingan , Sun Yage , McArthur Kristen , Carnes Megan , Liu Tiange , Mueller Noel T. , Page Grier P. , Rossman Lori , Smirnova Ekaterina , White Julie D. , Kress Amii M. , Debelius Justine W 
Published: February 2025

AbstractRobust evidence on relationships between the human microbiome and health are critical for understanding and improving the human condition. However, there is little information about methodological approaches to combine and analyze multiple microbiome data sets. To address this gap, we conducted a scoping review of studies that combine sequencing data from multiple data sets to understand the study objectives, data sources and selection, feature -table assembly methods, and analyses. References were identified through a systematic search of literature published between 2011 and 2022. Our final review included 60 articles. Despite the wide-spread use of the word “meta-analysis,” we found that only 24 studies used a systematic process to select their data sets, suggesting multiple meanings of the term within the field. While more than two thirds of studies used at least one publicly available data source, 19 had to request data from the original authors. Most studies (60%) combined data sets from multiple disjoint hypervariable regions. The number of hypervariable regions combined was not associated with the table construction method, but feature table construction method and the number of hypervariable regions influenced analytical resolution. Our results suggest the microbiome community needs to examine the use of terminology and analytic approaches for combining data sets; that additional work is needed to explore the impact of data source on bias in combined studies; and invite an independent evaluation of the methods used for feature table construction across disjoint regions.