bluuebunny/crossref_metadata_2025_split huggingface dataset:
Impact of Advanced Therapy Centers on Characteristics and Outcomes of Heart Failure Admissions
Authors: Lu Daniel Y , Kanduri Jaya , Yeo Ilhwan , Goyal Parag , Krishnan Udhay , Horn Evelyn M , Karas Maria G , Sobol Irina , Majure David T , Naka Yoshifumi , Minutello Robert M , Cheung Jim W , Uriel Nir , Kim Luke K 
Published: August 2023

AbstractBackgroundAlthough much attention has been paid to admission and transfer patterns for cardiogenic shock, contemporary data is lacking on decompensated heart failure (HF) admissions and transfers, and the impact of advanced therapy centers (ATCs) on outcomes.MethodsHF hospitalizations were obtained from the Nationwide Readmissions Database 2016-2019. Centers performing at least one heart transplant or left ventricular assist device were classified as ATCs. Patient characteristics, outcomes, and procedural volume were compared among three cohorts: admissions to non-ATCs, admissions to ATCs, transfers to ATCs. A secondary analysis evaluated outcomes for severe HF hospitalizations (cardiogenic shock, cardiac arrest, mechanical ventilation).Results2,331,690 hospitalizations were admissions to non-ATCs (94.5% of centers), 525,037 were admissions to ATCs (5.5% of centers), and 15,541 were transfers to ATCs. Patients treated at ATCs (especially those transferred) had higher rates of HF decompensations, procedural frequency, lengths-of-stay, and costs. Unadjusted mortality was 2.6% at non-ATCs and was higher at ATCs, both for directly admitted (2.9%, p<0.01) and transferred (11.2%, p<0.01) patients. However, multivariable adjusted mortality was significantly lower at ATCs, both for directly admitted (OR 0.82, p<0.01) and transferred (OR 0.66, p<0.01) patients. For severe HF admissions, unadjusted mortality was 37.2% at non-ATCs and was lower at ATCs, both for directly admitted (25.3%, p<0.01) and transferred (25.2%, p<0.01) patients, with similarly lower multivariable adjusted mortality.ConclusionsHF patients treated at ATCs were sicker but associated with higher procedural volume and lower adjusted mortality.Clinical PerspectiveContemporary data is lacking on admissions and transfers for decompensated heart failure (HF) and the impact of advanced therapy centers (ATCs) on outcomes. Our findings show that decompensated HF patients treated at ATCs had higher rates of HF decompensations, procedural frequency, lengths-of-stay, and costs. While unadjusted mortality was higher at ATCs, multivariable adjusted mortality was significantly lower at ATCs, both for directly admitted and transferred patients. Our findings will hopefully prompt earlier recognition and referral of patients to ATCs, emphasize the need for increased numbers of ATCs, and spark further research into the decision-making process for referral to ATCs.
pADP-ribosylation Regulates the Cytoplasmic Localization, Cleavage and Pro-apoptotic Function of HuR
Authors: Ashour Kholoud , Hall Derek , Mubaid Souad , Busque Sandrine , Lian Xian Jin , Gagné Jean-Philippe , Khattak Shahryar , Marco Sergio Di , Poirier Guy G. , Gallouzi Imed-Eddine 
Published: August 2023

AbstractHuR (ElavL1) is one of the main posttranscriptional regulators that determines cell fate. While the role of HuR in apoptosis is well-established, the posttranslational modifications that governs this function remain elusive. In this study we show that PARP1/2-mediated poly(ADP)-ribosylation (PARylation) is instrumental in the pro-apoptotic function of HuR. During apoptosis or in cells depleted of PARP1/2 enzymes, a substantial reduction in HuR PARylation is observed. This results in the cytoplasmic accumulation and the cleavage of HuR, both of which are essential events for apoptosis. These effects are mediated by a pADP-ribose (PAR) binding motif within the HuR-HNS region (HuR PAR Binding Site (HuR-PBS)). Under normal conditions, the association of HuR-PBS with PAR is responsible for the nuclear retention of HuR. Mutations within this motif prevents the binding of HuR to its import factor TRN2, leading to its cytoplasmic accumulation and cleavage. Collectively, our findings underscore the role of PARylation in controlling the proapoptotic function of HuR, offering insight into the mechanism by which PARP1/2 enzymes regulate cell fate and adaptation to various assaults.
Microglial cGAS deletion protects against amyloid-β induced Alzheimer’s disease pathogenesis
Authors: He Sijia , Li Xin , Mittra Namrata , Bhattacharjee Anindita , Wang Hu , Zhao Shangang , Liu Feng , Han Xianlin 
Published: August 2023

AbstractInnate immune activation plays a vital role in the development of Alzheimer’s disease (AD) and related dementias (ADRD). Among which, the DNA sensing cyclic GMP-AMP synthase (cGAS)- STING pathway has been implicated in diverse aspects of AD progression.In the current study, we showed that the cGAS-STING signaling was up-regulated in AD and this elevation was mainly contributed by the microglial population other than non-microglial cell types in the brain. By establishing an inducible, microglia-specific cGAS knockout mouse model in 5xFAD background, we found that deleting microglial cGAS at the onset of amyloid-β (Aβ) pathology significantly limited plaque formation, and protected mice from Aβ-induced cognitive impairment. Mechanistically, we found cGAS was necessary for plaque-associated microglial enrichment potentially driven by IRF8, and was indispensable for the development of disease-associated microglia (DAM) phenotype. Meanwhile, the loss of microglial cGAS reduced the levels of dystrophic neurites which led to preserved synaptic integrity and neuronal function. Our study provides new insights in understanding the effects of innate immune in AD via a cell-type specific manner, and lays the foundation for potential targeted intervention of the microglial cGAS-STING pathway toward the improvement of AD.
DeltaAI: Semi-Autonomous Tissue Grossing Measurements and Recommendations using Neural Radiance Fields for Rapid, Complete Intraoperative Histological Assessment of Tumor Margins
Authors: Suvarna Anish , Vempati Ram , Chacko Rachael , Srinivasan Gokul , Lu Yunrui , Hunt Brady , Torres Veronica , Samkoe Kimberly , Davis Matthew , Fu Lucy , Christensen Brock , Vaickus Louis , LeBoeuf Matthew , Levy Joshua 
Published: August 2023

AbstractMohs Micrographic Surgery (MMS) aims to excise cutaneous cancer with real-time margin analysis. However, manual tissue grossing and analysis can be inefficient, so we propose DeltaAI, a novel workflow that utilizes Neural Radiance Fields (NeRF) to enable rapid tissue grossing and generate a 3D model in an augmented reality (AR) environment. In our study, we captured 30-second videos of 17 MMS specimens using a photogrammetry turntable and cellphone camera. Preprocessing the tissues with segmentation models, we created a dataset of 923, 360-degree-view, images per video (17 videos). Using COLMAP, we estimated poses for sparse tissue reconstructions and trained the NeRF model for 3D volumetric tissue renderings. The results demonstrated that DeltaAI generated more accurate and complete 360-degree, 3D tissue renderings compared to previous models, while also achieving significantly faster runtimes. Our proposed semi-autonomous NeRF-based workflow has the potential to enhance the speed of MMS specimen processing, measurement, report generation, and margin assessment. It can inform real-time grossing decisions, automate the export of electronic health record data, and facilitate time-efficient and complete cancer excisions. Moreover, DeltaAI can contribute to the wider adoption of AI technology in clinical settings by improving tissue modeling for manual grossing.
Alteration of the chicken upper respiratory microbiota, following H9N2 avian influenza virus infection
Authors: Davis Tara , Bialy Dagmara , Leng Joy , Ragione Roberto La , Shelton Holly , Chrzastek Klaudia 
Published: August 2023

AbstractSeveral studies have highlighted the importance of the gut microbiota in developing immunity against viral infections in chickens. We have previously shown that H9N2 avian influenza A virus (AIV) infection retards the diversity of the natural colon associated microbiota, which may further influence chicken health following recovery from infection. The effects of influenza infection on the upper respiratory tract (URT) microbiota are largely unknown. Here we showed that H9N2 AIV infection lowers alpha diversity indices in the acute phase of infection in URT, largely due to the family Lactobacillaceae being highly enriched during this time in the respiratory microbiota. Interestingly, microbiota diversity did not return to levels similar to control chickens in the recovery phase after viral shedding has ceased. Beta diversity followed similar trend following challenge.Lactobacillusassociate statistically with the disturbed microbiota of infected chickens at acute and recovery phase of infection. Additionally, we study age-related changes in the respiratory microbiota during maturation in chickens. From 7 to 28 days of age, species richness and evenness were observed to advance over time as the microbial composition evolved.Maintaining microbiota homeostasis might be considered as a potential therapeutic target to prevent or aid recovery from H9N2 AIV infection.
The Hedgehog receptors PTCH1 and PTCH2 exist as active homomeric and heteromeric complexes
Authors: Timmis Alex J. , Cross Felix , Gkotsi Danai S. , Ollerton Hattie , Johnson Colin A. , Galdo Natalia A. Riobo-Del 
Published: August 2023

ABSTRACTWith the importance of Hedgehog signalling in embryonic development, tissue homeostasis and disease, understanding the molecular mechanisms of signal transduction is paramount for the design of specific, effective therapeutics. The Hedgehog receptor PTCH1 and the less studied PTCH2 isoform are evolutionarily related to bacterial RND permeases and sterol sensing proteins, which mobilise hydrophobic compounds powered by a cation gradient. Here we demonstrate that, in the active state, PTCH1 and PTCH2 form homomeric and heteromeric complexes that are inhibited by binding of Sonic Hedgehog. We show that PTCH2, unlike PTCH1, appears to have minimal cholesterol transport activity, but that conserved residues involved in cation transport are essential for its function. Heteromeric PTCH1-PTCH2 complexes depend on PTCH1’s cholesterol transport capacity, but the cation transport can be provided in trans by PTCH2, suggesting that some deleterious mutations in either isoform can be silenced by formation of heteromers, enhancing the robustness of this signal transduction system. These findings provide the molecular basis for the intriguing behaviour of PTCH2 as semi-redundant and partially overlapping in function with PTCH1 and explain the dominant negative effect of mutations that disrupt the PTCH2 cation transport triad in rare cases of cancer.
The HuMet Repository: Watching human metabolism at work
Authors: Weinisch Patrick , Raffler Johannes , Römisch-Margl Werner , Arnold Matthias , Mohney Robert P. , Rist Manuela J. , Prehn Cornelia , Skurk Thomas , Hauner Hans , Daniel Hannelore , Suhre Karsten , Kastenmüller Gabi 
Published: August 2023

AbstractThe human metabolism constantly responds to stimuli such as food intake, fasting, exercise, and stress, triggering adaptive biochemical processes across multiple metabolic pathways. To understand the role of these processes and disruptions thereof in health and disease, detailed documentation of healthy metabolic responses is needed but still scarce on a time-resolved metabolome-wide level.Here, we present the HuMet Repository, a web-based resource for exploring dynamic metabolic responses to six physiological challenges (exercise, 36 h fasting, oral glucose and lipid loads, mixed meal, cold stress) in healthy subjects. For building this resource, we integrated existing and newly derived metabolomics data measured in blood, urine, and breath samples of 15 young healthy men at up to 56 time points during the six highly standardized challenge tests conducted over four days. The data comprise 1.1 million data points acquired on multiple platforms with temporal profiles of 2,656 metabolites from a broad range of biochemical pathways. By embedding the dataset into an interactive web application, we enable users to easily access, search, filter, analyze, and visualize the time-resolved metabolomic readouts and derived results. Users can put metabolites into their larger context by identifying metabolites with similar trajectories or by visualizing metabolites within holistic metabolic networks to pinpoint pathways of interest. In three showcases, we outline the value of the repository for gaining biological insights and generating hypotheses by analyzing the wash-out of dietary markers, the complementarity of metabolomics platforms in dynamic versus cross-sectional data, and similarities and differences in systemic metabolic responses across challenges.With its comprehensive collection of time-resolved metabolomics data, the HuMet Repository, freely accessible athttps://humet.org/, is a reference for normal, healthy responses to metabolic challenges in young males. It will enable researchers with and without computational expertise, to flexibly query the data for their own research into the dynamics of human metabolism.
Antibody Inhibition of Influenza A Virus Assembly and Release
Authors: He Yuanyuan , Guo Zijian , Subiaur Sofie , Benegal Ananya , Vahey Michael D. 
Published: August 2023

ABSTRACTAntibodies are frontline defenders against influenza virus infection, providing protection through multiple complementary mechanisms. Although a subset of monoclonal antibodies (mAbs) have been shown to restrict replication at the level of virus assembly and release, it remains unclear how potent and pervasive this mechanism of protection is, due in part to the challenge of separating this effect from other aspects of antibody function. To address this question, we developed imaging-based assays to determine how effectively a broad range of mAbs against the IAV surface proteins can specifically restrict viral egress. We find that classically neutralizing antibodies against hemagglutinin are broadly multifunctional, inhibiting virus assembly and release at concentrations one- to twenty-fold higher than the concentrations at which they inhibit viral entry. These antibodies are also capable of altering the morphological features of shed virions, reducing the proportion of filamentous particles. We find that antibodies against neuraminidase and M2 also restrict viral egress, and that inhibition by anti-neuraminidase mAbs is only partly attributable to a loss in enzymatic activity. In all cases, antigen crosslinking – either on the surface of the infected cell, between the viral and cell membrane, or both - plays a critical role in inhibition, and we are able to distinguish between these modes experimentally and through a structure-based computational model. Together, these results provide a framework for dissecting antibody multifunctionality that could help guide the development of improved therapeutic antibodies or vaccines, and that can be extended to other viral families and antibody isotypes.
Iterative Machine Learning for Classification and Discovery of Single-molecule Unfolding Trajectories from Force Spectroscopy Data
Authors: Doffini Vanni , Liu Haipei , Liu Zhaowei , Nash Michael A. 
Published: August 2023

AbstractWe report the application of machine learning techniques to accelerate classification and analysis of protein unfolding trajectories from force spectroscopy data. Using kernel methods, logistic regression and triplet loss, we developed a workflow called Forced Unfolding and Supervised Iterative Online (FUSION) where a user classifies a small number of repeatable unfolding patterns encoded as image data, and a machine is tasked with identifying similar images to classify the remaining data. We tested the workflow using two case studies on a multi-domain XMod-Dockerin/Cohesin complex, validating the approach first using synthetic data generated with a Monte Carlo algorithm, and then deploying the method on experimental atomic force spectroscopy data. FUSION efficiently separated traces that passed quality filters from unusable ones, classified curves with high accuracy, and identified unfolding pathways undetected by the user. This study demonstrates the potential of machine learning to accelerate data analysis, and generate new insights in protein biophysics.
In vivoMapping of Cellular Resolution Neuropathology in Brain Ischemia by Diffusion MRI
Authors: Wu Dan , Turnbill Victoria , Lee Hong-Hsi , Wang Xiaoli , Ba Ruicheng , Walczak Piotr , Martin Lee J. , Fieremans Els , Novikov Dmitry S. , Northington Frances J. , Zhang Jiangyang 
Published: August 2023

AbstractNon-invasive mapping of cellular pathology can provide critical diagnostic and prognostic information. Recent developments in diffusion MRI have produced new tools for examining tissue microstructure at a level well below the imaging resolution. Here, we report the use of diffusion time (t)-dependent diffusion kurtosis imaging (tDKI) to simultaneously assess the morphology and transmembrane permeability of cells and their processes in the context of pathological changes in hypoxic-ischemic brain (HI) injury. Through Monte Carlo simulations and cell culture organoid imaging, we demonstrate feasibility in measuring effective size and permeability changes based on the peak and tail oftDKI curves. In a mouse model of HI,in vivoimaging at 11.7T detects a marked shift of thetDKI peak to longertin brain edema, suggesting swelling and beading associated with the astrocytic processes and neuronal neurites. Furthermore, we observed a faster decrease of thetDKI tail in injured brain regions, reflecting increased membrane permeability that was associated with upregulated water exchange upon astrocyte activation at acute stage as well as necrosis with disrupted membrane integrity at subacute stage. Such information, unavailable with conventional diffusion MRI at a singlet,can predict salvageable tissues. For a proof-of-concept,tDKI at 3T on an ischemic stroke patient suggested increased membrane permeability in the stroke region. This work therefore demonstrates the potential oftDKI forin vivodetection of the pathological changes in microstructural morphology and transmembrane permeability after ischemic injury using a clinically translatable protocol.
Predicting cell types with supervised contrastive learning on cells and their types
Authors: Heryanto Yusri Dwi , Zhang Yao-zhong , Imoto Seiya 
Published: August 2023

ABSTRACTSingle-cell RNA-sequencing (scRNA-seq) is a powerful technique that provides high-resolution expression profiling of individual cells. It significantly advances our understanding of cellular diversity and function. Despite its potential, the analysis of scRNA-seq data poses considerable challenges relate to multicollinearity, data imbalance, and batch effect. One of the pivotal tasks in single-cell data analysis is cell type annotation, which classifies cells into discrete types based on their gene expression profiles. In this work, we propose a novel modeling formalism for cell type annotation with a supervised contrastive learning method, named SCLSC (SupervisedContrastiveLearning forSingleCell). Different from the previous usage of contrastive learning in single cell data analysis, we employed the contrastive learning for instance-type pairs instead of instance-instance pairs. More specifically, in the cell type annotation task, the contrastive learning is applied to learn cell and cell type representation that render cells of the same type to be clustered in the new embedding space. Through this approach, the knowledge derived from annotated cells is transferred to the feature representation for scRNA-seq data. The whole training process becomes more efficient when conducting contrastive learning for cell and their types. Our experiment results demonstrate that the proposed SCLSC method consistently achieves superior accuracy in predicting cell types compared to four state-of-the-art methods. SCLSC also performs well in identifying cell types in different batch groups. The simplicity of our method allows for scalability, making it suitable for analyzing datasets with a large number of cells. In a real-world application of SCLSC to monitor the dynamics of immune cell subpopulations over time, SCLSC demonstrates a capability to discriminate cell subtypes of CD19+ B cells that were not present in the training dataset.
Haplotype Function Score improves biological interpretation and cross-ancestry polygenic prediction of human complex traits
Authors: Song Weichen , Shi Yongyong , Lin Guan Ning 
Published: August 2023

AbstractWe propose a new framework for human genetic association studies: at each locus, a deep learning model (in this study, Sei) is used to calculate the functional genomic activity score for two haplotypes per individual. This score, defined as the Haplotype Function Score (HFS), replaces the original genotype in association studies. Applying the HFS framework to 14 complex traits in the UK Biobank, we identified 3,619 independent HFS-trait associations with a significance of p<5×10−8. Fine-mapping revealed 2,699 causal associations, corresponding to a median increase of 63 causal findings per trait compared with SNP-based analysis. HFS-based enrichment analysis uncovered 727 pathway-trait associations and 153 tissue-trait associations with strong biological interpretability, including “circadian pathway-chronotype” and “arachidonic acid-intelligence”. Lastly, we applied LASSO regression to integrate HFS prediction score with SNP-based polygenic risk scores, which showed an improvement of 16.1% to 39.8% in cross-ancestry polygenic prediction. We concluded that HFS is a promising strategy for understanding the genetic basis of human complex traits.
Crystal Structure of Histone Deacetylase 6 Complexed with (R)-Lipoic Acid, an Essential Cofactor in Central Carbon Metabolism
Authors: Watson Paris R. , Stollmaier Juana Goulart , Christianson David W. 
Published: August 2023

AbstractThe enzyme cofactor (R)-lipoic acid plays a critical role in central carbon metabolism due to its catalytic function in the generation of acetyl-CoA, which links glycolysis with the tricarboxylic acid cycle. This cofactor is also essential for the generation of succinyl CoA within the tricarboxylic acid cycle. However, the biological functions of (R)-lipoic acid extend beyond metabolism owing to its facile redox chemistry. Most recently, the reduced form of (R)-lipoic acid, (R)-dihydrolipoic acid, has been shown to inhibit histone deacetylases (HDACs) with selectivity for the inhibition of HDAC6. Here, we report the 2.4 Å-resolution X-ray crystal structure of the HDAC6–(R)-dihydrolipoic acid complex, and we report a dissociation constant (KD) of 350 nM for this complex as determined by isothermal titration calorimetry. The crystal structure illuminates key affinity determinants in the enzyme active site, including thiolate-Zn2+coordination and S-π interactions in the F583-F643 aromatic crevice. This study provides the first visualization of the connection between HDAC function and the biological response to oxidative stress: the dithiol moiety of (R)-dihydrolipoic acid can serve as a redox-regulated pharmacophore capable of simultaneously targeting the catalytic Zn2+ion and the aromatic crevice in the active site of HDAC6.