bluuebunny/crossref_metadata_2025_split huggingface dataset:
The somatic mutation landscape of normal gastric epithelium
Authors: Coorens Tim H.H. , Collord Grace , Jung Hyungchul , Wang Yichen , Moore Luiza , Hooks Yvette , Mahbubani Krishnaa , Saeb-Parsy Kourosh , Campbell Peter J. , Martincorena Iñigo , Leung Suet Yi , Stratton Michael R. 
Published: March 2024

ABSTRACTThe landscapes of somatic mutation in normal cells inform on the processes of mutation and selection operative throughout life, permitting insight into normal ageing and the earliest stages of cancer development. Here, by whole-genome sequencing of 238 microdissections from 30 individuals, including 18 with gastric cancer, we elucidate the developmental trajectories of normal and malignant gastric epithelium. We find that gastric glands are units of monoclonal cell populations which accrue ∼28 somatic single nucleotide variants per year, predominantly attributable to endogenous mutational processes. In individuals with gastric cancer, glands often show elevated mutation burdens due to acceleration of mutational processes linked to proliferation and oxidative damage. These hypermutant glands were primarily detected in the gastric antrum and were mostly associated with chronic inflammation and intestinal metaplasia, known cancer risk factors. Unusually for normal cells, gastric epithelial cells often carry recurrent trisomies of specific chromosomes, which are highly enriched in a subset of individuals. Surveying approximately 8,000 gastric glands by targeted sequencing, we found somatic driver mutations in a distinctive repertoire of known cancer genes, includingARID1A, CTNNB1, KDM6AandARID1B. Their prevalence increases with age to occupy approximately 5% of the gastric epithelial lining by age 60 years. Our findings provide insights into the intrinsic and extrinsic influences on somatic evolution in the gastric epithelium, in healthy, precancerous and malignant states.
Transfer and Capture of Envelope Protein Receptor-Binding Domains in the Retroviruses
Authors: Hötzel Isidro 
Published: March 2024

AbstractThe surface subunit (SU) of the envelope protein (Env) or retroviruses is highly variable due to adaptation to different hosts during their long evolutionary history. Several exogenous and endogenous retroviral gamma-like Env have a receptor-binding domain (RBD) in the amino-terminal region of SU that folds independently from the carboxyterminal SU C-domain. Two structurally distinct RBD classes have been described, one that adopts a modified immunoglobulin (Ig)-like domain fold and a second, in the Env of RDR interference group retroviruses, with a distinct β-sheet fold. Here, the distribution of different RBD classes among exogenous and endogenous gammatype Env was determined by phylogenetic analyses of Env and structural modeling of retroviral SU with AlphaFold2. The patterns of RBD distribution indicate multiple RBD transfer events in the retroviruses. In addition, SU structural modeling identified an endogenous alpharetroviral-like Env in mammalian species with an amino-terminal RBD. This RDB has a typical IgV domain fold closely related both structurally and in sequence to the mammalian signal regulatory proteins (SIRP) α, β and γ, indicating, for the first time, acquisition of an RBD from a mammalian gene by the retroviruses. The results described herein indicate intragenicenvrecombination between retroviruses and between retroviruses and their hosts as a major factor in the evolution of retroviral Env.
A Large Language Model Approach to Extracting Causal Evidence across Study Designs for Evidence Triangulation
Authors: Shi Xuanyu , Zhao Wenjing , Chen Ting , Yang Chao , Du Jian 
Published: March 2024

AbstractHealth strategies increasingly emphasize both behavioral and biomedical interventions, yet the complex and often contradictory guidance on diet, behavior, and health outcomes complicates evidence-based decision-making. Evidence triangulation across diverse study designs is essential for establishing causality, but scalable, automated methods for achieving this are lacking. In this study, we assess the performance of large language models (LLMs) in extracting both ontological and methodological information from scientific literature to automate evidence triangulation. A two-step extraction approach—focusing on cause-effect concepts first, followed by relation extraction—outperformed a one-step method, particularly in identifying effect direction and statistical significance. Using salt intake and blood pressure as a case study, we calculated the Convergeny of Evidence (CoE) and Level of Evidence (LoE), finding a trending excitatory effect of salt on hypertension risk, with a moderate LoE. This approach complements traditional meta-analyses by integrating evidence across study designs, thereby facilitating more comprehensive assessments of public health recommendations.
Using machine learning to evaluate the value of genetic liabilities in classification of hypertension within the UK Biobank
Authors: MacCarthy Gideon , Pazoki Raha 
Published: March 2024

AbstractBackground and objectiveHypertension increases the risk of cardiovascular diseases (CVD) such as stroke, heart attack, heart failure, and kidney disease, contributing to global disease burden and premature mortality. Previous studies have utilized statistical and machine learning techniques to develop hypertension prediction models. Only a few have included genetic liabilities and evaluated their predictive values. This study aimed to develop an effective hypertension prediction model and investigate the potential influence of genetic liability for risk factors linked to CVD on hypertension risk using Random Forest (RF) and Neural Network (NN).Materials and methodsThe study included 244,718 participants of European ancestry. Genetic liabilities were constructed using previously identified genetic variants associated with various cardiovascular risk factors through genome-wide association studies (GWAS). The sample was randomly split into training and testing sets at a 70:30 ratio. We used RF and NN techniques to develop prediction models in the training set with or without feature selection. We evaluated the models’ discrimination performance using the area under the curve (AUC), calibration, and net reclassification improvement in the testing set.ResultsThe models without genetic liabilities achieved AUCs of 0.70 and 0.72 using RF and NN methods, respectively. Adding genetic liabilities resulted in a modest improvement in the AUC for RF but not for NN. The best prediction model was achieved using RF (AUC =0.71, Spiegelhalter z score= 0.10, P-value= 0.92, calibration slope=0.99) constructed in stage two.ConclusionIncorporating genetic factors in the model may provide a modest incremental value for hypertension prediction beyond baseline characteristics. Our study highlighted the importance of genetic liabilities for both total cholesterol and LDL within the same prediction model adds value to the classification of hypertension.
Single Turnover Transient State Kinetics Reveals Processive Protein Unfolding Catalyzed byEscherichia coliClpB
Authors: Banwait Jaskamaljot Kaur , Islam Liana , Lucius Aaron L. 
Published: March 2024

SummaryE. coliClpB, andS. cerevisiaeHsp104 are AAA+ motor proteins essential for proteome maintenance and thermal tolerance. ClpB and Hsp104 have been proposed to extract a polypeptide from an aggregate and processively translocate the chain through the axial channel of its hexameric ring structure. However, the mechanism of translocation and if this reaction is processive remains disputed. We reported that Hsp104 and ClpB are non-processive on unfolded model substrates. Others have reported that ClpB is able to processively translocate a mechanically unfolded polypeptide chain at rates over 240 amino acids (aa) per second. Here we report the development of a single turnover stopped-flow fluorescence strategy that reports on processive protein unfolding catalyzed by ClpB. We show that when translocation catalyzed by ClpB is challenged by stably folded protein structure, the motor enzymatically unfolds the substrate at a rate of ∼0.9 aa s-1with a step-size of ∼60 amino acids. We reconcile the apparent controversy by defining enzyme catalyzed protein unfolding and translocation as two distinct reactions with different mechanisms of action. We propose a model where slow unfolding followed by fast translocation represents an important mechanistic feature that allows the motor to rapidly translocate up to the next folded region or rapidly dissociate if no additional fold is encountered.
Evaluating a Novel High-Density EEG Sensor Net Structure for Improving Inclusivity in Infants with Curly or Tightly Coiled Hair
Authors: Mlandu Nwabisa , McCormick Sarah A. , Davel Lauren , Zieff Michal R. , Bradford Layla , Herr Donna , Jacobs Chloë A. , Khumalo Anele , Knipe Candice , Madi Zamazimba , Mazubane Thandeka , Methola Bokang , Mhlakwaphalwa Tembeka , Miles Marlie , Goolam Nabi Zayaan , Negota Rabelani , Nkubungu Khanyisa , Pan Tracy , Samuels Reese , Williams Sadeeka , Williams Simone R. , Avery Trey , Foster Gaynor , Donald Kirsten A. , Gabard-Durnam Laurel J. 
Published: March 2024

AbstractElectroencephalography (EEG) is an important tool in the field of developmental cognitive neuroscience for indexing neural activity. However, racial biases persist in EEG research that limit the utility of this tool. One bias comes from the structure of EEG nets/caps that do not facilitate equitable data collection across hair textures and types. Recent efforts have improved EEG net/cap design, but these solutions can be time-intensive, reduce sensor density, and are more difficult to implement in younger populations. The present study focused on testing EEG sensor net designs over infancy. Specifically, we compared EEG data quality and retention between two high-density saline-based EEG sensor net designs from the same company (Magstim EGI, Whitland, UK) within the same infants during a baseline EEG paradigm. We found that within infants, the tall sensor nets resulted in lower impedances during collection, including lower impedances in the key online reference electrode for those with greater hair heights and resulted in a greater number of usable EEG channels and data segments retained during pre-processing. These results suggest that along with other best practices, the modified tall sensor net design is useful for improving data quality and retention in infant participants with curly or tightly-coiled hair.
Tuning non-linear mechanics in collagen hydrogels modulates cellular morphotypes in three dimensions
Authors: Martinez Marco A. Enriquez , Wang Zhao , Ju Robert J. , Turunen Petri , Mata Jitendra , Gilbert Elliot P. , Lauko Jan , Stehbens Samantha J. , Rowan Alan E. 
Published: March 2024

AbstractCollagen networks contribute to tissue architecture and modulate cellular responses in crowded three-dimensional environments. Therefore, it is the most widely used biological polymer in three-dimensional studies of cellular interactions with the extracellular matrix.In vivo, collagen exists embedded within additional matrix components. Studies have shown that the combination of matrices induces synergistic mechanical interactions, influencing the non-linear mechanical behaviour of collagen networks. However, how cells respond to changes in collagen non-linear elasticity remains largely unknown. By precisely controlling the mechanical behaviour of collagen networks with the biologically inert and semiflexible polymer polyisocyanopeptides, we demonstrate that changes in the non-linear elasticity of collagen induces morphological cell responses that influence how cells migrate, proliferate, and interact with collagen. We found that when collagen rigidifies in the presence of a second component, this induces morphological changes in cell-matrix interactions, resulting in a decrease in migration and the ability of cells to deform collagen matrices. Our results demonstrate that the onset of collagen stiffening is key to inducing intracellular tension which dictates morphological cell responses in three-dimensional collagen networks. We anticipate our findings will prove useful in understanding how cells respond to changes in collagen mechanics when combined in double network systems which better recapitulates tissuesin vivo.
Optogenetic stimulation recruits cortical neurons in a morphology-dependent manner
Authors: Berling David , Baroni Luca , Chaffiol Antoine , Gauvain Gregory , Picaud Serge , Antolík Ján 
Published: March 2024

AbstractSingle-photon optogenetic stimulation is a crucial tool in neuroscience, enabling precise, cell-type-specific modulation of neuronal circuits. Miniaturization of this technique in the form of fully implantable wide-field stimulator arrays enables interrogation of cortical circuits in long-term experiments and promises to enhance Brain-Machine Interfaces for restoring sensory and motor functions. However, for both basic science and clinical applications, it is essential that this technique achieves the precision needed for selective activation of sensory and motor representations at the single-column level. Yet studies report differing and sometimes conflicting neuronal responses within the stimulated cortical areas. While recurrent network mechanisms contribute to complex responses, here we demonstrate that complexity starts already at the level of neuronal morphology. Simulating optogenetic responses in detailed models of layer-2/3 and layer-5 pyramidal neurons, we accounted for realistic physiological dynamics across different stimulation intensities, including threshold, sustained, and depolarization-block responses. Our findings suggest that the spatial distribution of activated neurons from a single stimulator location at the cortical surface can be inhomogeneous and varies with stimulation intensity and neuronal morphology across layers, potentially explaining the observed response heterogeneity in earlier experiments. We found that activation spreads laterally up to several hundred micrometers from the light source due to neuronal morphology. To enhance precision, we explored two strategies: preferentially somatic expression of channelrhodopsin, which was effective only in layer-5 neurons, and narrowing the stimulating light beam, which improved precision in both layers. Our results indicate that, under the right optical setup, single-column precision of stimulation is achievable, and that optical enhancements to the stimulator may offer more significant precision improvements than genetic modifications targeting the soma.
Dysregulated Neurofluid Coupling as a New Noninvasive Biomarker for Primary Progressive Aphasia
Authors: Zeng Xinglin , Zhao Zhiying , Hua Lin , Yuan Zhen 
Published: March 2024

AbstractObjectiveAccumulation of pathological tau is one of the primary causes of Primary Progressive Aphasia (PPA). The glymphatic system is crucial for removing metabolic waste from the brain, whereas the underlying mechanism on the interplay between impairments in glymphatic clearance and PPA is poorly understood. Therefore, the aim of this study is to investigate the role that dysregulated macroscopic cerebrospinal fluid (CSF) movement plays in the pathology of PPA.Methods56 PPA patients and 94 healthy controls (HCs) participated this work. The coupling strength between blood-oxygen-level-dependent (BOLD) signals in the gray matter and CSF flow within the subarachnoid space and ventricular system was calculated by using Pearson correlation and made comparison between the two groups. Its associations with clinical characteristics including scores from Clinical Dementia Rating (CDR), Mini-Mental State Exam, Geriatric Depression Scale and with morphological measures in the hippocampus and entorhinal cortex were also quantified.ResultsThe PPA group exhibited decreased global BOLD and CSF coupling as compared to that of HCs, indicating impaired glymphatic functions of the patients (p= 0.006). More importantly, it was discovered that BOLD-CSF coupling of PPA group rather than that of the HCs demonstrated significant correlations with the CDR scores (p= 0.04), hippocampal volume (p= 0.005), and entorhinal cortex thickness (p= 0.04).InterpretationThe measured decoupling between global brain activation (hemodynamic response) and CSF flow and its association with symptomology and brain structural changes in PPA revealed the glymphatic dysregulation in PPA. Herein, this evidence supports the potential role of BOLD-CSF coupling as a noninvasive biomarker for the detection and prediction of PPA.
Multi-way modelling of oral microbial dynamics and host-microbiome interactions during induced gingivitis
Authors: van der Ploeg G.R. , Brandt B.W. , Keijser B.J.F. , van der Veen M.H. , Volgenant C.M.C. , Zaura E. , Smilde A.K. , Westerhuis J.A. , Heintz-Buschart A. 
Published: March 2024

AbstractGingivitis - the inflammation of the gums - is a reversible stage of periodontal disease. It is caused by dental plaque formation due to poor oral hygiene. However, gingivitis susceptibility involves a complex set of interactions between the oral microbiome, oral metabolome and the host. In this study, we investigated the dynamics of the oral microbiome and its interactions with the salivary metabolome during experimental gingivitis in a cohort of 41 systemically healthy participants. We use Parallel Factor Analysis (PARAFAC), which is a multi-way generalization of Principal Component Analysis (PCA) that can model the variability in the response due to subjects, variables and time. Using the modelled responses, we identified microbial subcommunities with similar dynamics that connect to the magnitude of the gingivitis response. By performing high level integration of the predicted metabolic functions of the microbiome and salivary metabolome, we identified pathways of interest that describe the changing proportions of Gram-positive and Gram-negative microbiota, variation in anaerobic bacteria, biofilm formation and virulence.
Transcriptional Determinism and Stochasticity Contribute to the Complexity of Autism AssociatedSHANKFamily Genes
Authors: Lu Xiaona , Ni Pengyu , Suarez-Meade Paola , Ma Yu , Forrest Emily Niemitz , Wang Guilin , Wang Yi , Quiñones-Hinojosa Alfredo , Gerstein Mark , Jiang Yong-hui 
Published: March 2024

AbstractPrecision of transcription is critical because transcriptional dysregulation is disease causing. Traditional methods of transcriptional profiling are inadequate to elucidate the full spectrum of the transcriptome, particularly for longer and less abundant mRNAs.SHANK3is one of the most common autism causative genes. Twenty-fourShank3mutant animal lines have been developed for autism modeling. However, their preclinical validity has been questioned due to incompleteShank3transcript structure. We applied an integrative approach combining cDNA-capture and long-read sequencing to profile theSHANK3transcriptome in human and mice. We unexpectedly discovered an extremely complexSHANK3transcriptome. SpecificSHANK3transcripts were altered inShank3mutant mice and postmortem brains tissues from individuals with ASD. The enhancedSHANK3transcriptome significantly improved the detection rate for potential deleterious variants from genomics studies of neuropsychiatric disorders. Our findings suggest the stochastic transcription of genome associated withSHANKfamily genes.
Indiscriminate activities of different Henipavirus polymerase complex proteins allow for efficient minigenome replication in hybrid systems
Authors: Li Xiao , Yang Yanling , López Carolina B. 
Published: March 2024

ABSTRACTThe henipaviruses, including Nipah virus (NiV) and Hendra virus (HeV), are biosafety level 4 (BSL-4) zoonotic pathogens that cause severe neurological and respiratory disease in humans. To study the replication machinery of these viruses we developed robust minigenome systems that can be safely used in BSL-2 conditions. The nucleocapsid (N), phosphoprotein (P), and large protein (L) of henipaviruses are critical elements of their replication machinery and thus essential support components of the minigenome systems. Here, we tested the effects of diverse combinations of the replication support proteins on the replication capacity of the NiV and HeV minigenomes by exchanging the helper plasmids coding for these proteins among the two viruses. We demonstrate that all combinations including one or more heterologous proteins were capable of replicating both the NiV and HeV minigenomes. Sequence alignment showed identities of 92% for the N protein, 67% for P, and 87% for L. Notably, variations in amino acid residues were not concentrated in the N-P and P-L interacting regions implying that dissimilarities in amino acid composition among NiV and HeV polymerase complex proteins may not impact their interactions. The observed indiscriminate activity of NiV and HeV polymerase complex proteins is different from related viruses, which can support replication of heterologous genomes only when the whole polymerase complex belongs to the same virus. This newly observed promiscuous property of the henipavirus polymerase complex proteins could potentially be harnessed to develop universal anti-henipavirus antivirals.IMPORTANCEGiven the severity of disease induced by Hendra and Nipah viruses in humans and the continuous emergence of new henipaviruses as well as henipa-like viruses, it is necessary to conduct more comprehensive investigation of the biology of henipaviruses and their interaction with the host. The replication of henipaviruses and the development of antiviral agents can be studied in systems that allow experiments to be performed under biosafety level 2 conditions. Here, we developed two robust minigenome systems for Nipah virus (NiV) and Hendra virus (HeV) that provide a convenient alternative system for studying NiV and HeV replication. Using these systems, we demonstrate that any combinations of the three polymerase complex proteins of NiV and HeV could effectively initiate the replication of both viral minigenomes, which suggest that the interaction regions of the polymerase complex proteins could be effective targets for universal and effective anti-henipavirus interventions.
The 3’-untranslated regions of yeast ribosomal protein mRNAs determine paralog incorporation into ribosomes and recruit factors necessary for specialized functions
Authors: Singh Raman K. , Crawford Robert A. , Mall Dheerendra P. , Pavitt Graham D. , Gerst Jeffrey E. 
Published: March 2024

AbstractRibosome heterogeneity arises via the differential incorporation of ribosomal protein (RP) paralogs, post-transcriptionally modified rRNA, post-translationally modified RPs, and ribosome-associated proteins (RAPs) into ribosomes. This has led to the hypothesis that heterogeneous or “specialized” ribosomes, which translate specific mRNA subsets, confer key roles in cell growth and development. While proven examples of functional ribosome heterogeneity in eukaryotes exist, there is no comprehensive analysis of specialized ribosome formation. We employed yeast RP paralog deletion libraries and high-throughput screening to investigate the functional specificity and redundancy between paralogs under various growth conditions. Composition and translatome analyses verified paralog specificity in the assembly and function of ribosomes specialized for growth on different carbon sources, and identified a novel RAP required for the efficient translation of peroxisomal proteins. Importantly, we also show that the mechanism by which specific RP paralogs incorporate into ribosomes requires their unique 3’-untranslated regions to yield ribosomes that differ in composition and function.Graphical Abstract