bluuebunny/crossref_metadata_2025_split huggingface dataset:
DecoyFinder: Identification of Contaminants in Sets of Homologous RNA Sequences
Authors: Zhu Mingyi , Zuber Jeffrey , Tan Zhen , Sharma Gaurav , Mathews David H. 
Published: October 2024

AbstractMotivationRNA structure is essential for the function of many non-coding RNAs. Using multiple homologous sequences, which share structure and function, secondary structure can be predicted with much higher accuracy than with a single sequence. It can be difficult, however, to establish a set of homologous sequences when their structure is not yet known. We developed a method to identify sequences in a set of putative homologs that are in fact non-homologs.ResultsPreviously, we developed TurboFold to estimate conserved structure using multiple, unaligned RNA homologs. Here, we report that the positive predictive value of TurboFold is significantly reduced by the presence of contamination by non-homologous sequences, although the reduction is less than 1%. We developed a method called DecoyFinder, which applies machine learning trained with features determined by TurboFold, to detect sequences that are not homologous with the other sequences in the set. This method can identify approximately 45% of non-homologous sequences, at a rate of 5% misidentification of true homologous sequences.AvailabilityDecoyFinder and TurboFold are incorporated in RNAstructure, which is provided for free and open source under the GPL V2 license. It can be downloaded athttp://rna.urmc.rochester.edu/RNAstructure.html
MeNu GUIDE - a metabolite nutrition graph to uncover interactions with disease etiology
Authors: Würf Vivian , Pauling Josch K. 
Published: October 2024

AbstractThe relationship between diet and disease is well-documented, yet the complex interactions among foods, metabolites, and genetics makes research challenging. This study explores the potential insights offered by a knowledge graph that connects nutrition and diseases on a metabolic level. Ten ontologies and data from six databases were merged, resulting in a graph with over 25 million triple statements, stored in a Turtle file and added to a GraphDB repository. SPARQL queries revealed biases towards specific foods and conditions within the integrated databases. Despite these biases, this knowledge graph serves as a proof-of-concept, demonstrating the feasibility of integrating information from diverse resources to yield valuable insights and enabling the drawing of meaningful conclusions. The graph allows efficient identification of disease-related compounds and their food sources and enables the exploration of changes in metabolite concentrations, such as those occurring during food processing. Researchers could use such a knowledge graph to identify biomarkers, help generate new hypotheses, and improve experimental designs. Expanding the graph with automated text-mining and recipe data would further enhance its utility for nutrition research. Such a resource could advance understanding of the molecular mechanisms behind diet-disease relationships, guiding more targeted interventions.
A modular approach to forecasting COVID-19 hospital bed occupancy
Authors: Tobin Ruarai J , Walker Camelia R , Moss Robert , McCaw James M , Price David J , Shearer Freya M 
Published: October 2024

AbstractMonitoring the number of COVID-19 patients in hospital beds was a critical component of Australia’s real-time surveillance strategy for the disease. From 2021–2023, we produced short-term forecasts of bed occupancy to support public health decision making. In this work, we present a model for forecasting the number of ward and intensive care unit (ICU) beds occupied by COVID-19 cases. The model simulates the stochastic progression of COVID-19 patients through the hospital system and is fit to reported occupancy counts using an approximate Bayesian method. We do not directly model infection dynamics — instead taking independently produced forecasts of case incidence as an input — enabling the independent development of our model from that of the underlying case forecast(s). We evaluate the performance of 21-day forecasts of ward and ICU occupancy across Australia’s eight states and territories between March and September 2022, when major waves of the Omicron variant of SARS-CoV-2 were occurring throughout the country. Forecasts were on average biased downwards immediately prior to epidemic peaks and biased upwards post-peak. Forecast performance was best in jurisdictions with the largest population sizes. Our forecasts of COVID-19 hospital burden were reported weekly to national decision-making committees to support Australia’s public health response.
Who is asking ChatGPT health questions? Analysis of a nationally representative Australian community sample
Authors: Ayre Julie , Cvejic Erin , McCaffery Kirsten J 
Published: October 2024

AbstractChatGPT and other generative artificial intelligence (AI) tools have dramatically changed the health information environment. Discussions about their benefits and risks need clear evidence about who is using them and why. This nationally representative survey estimates that one in ten Australians asked ChatGPT a health question in the past 6 months (95%CI: 8.5%□11.4%), with higher use in key priority groups: people born in a non-English speaking country, who speak a non-English language at home, and who have low health literacy. As usage increases, we need to equip community with knowledge and skills to use these tools safely.
The first near-complete genome assembly of pig: enabling more accurate genetic research
Authors: Cao Caiyun , Miao Jian , Xie Qinqin , Sun Jiabao , Cheng Hong , Zhang Zhenyang , Wu Fen , Liu Shuang , Ye Xiaowei , Zhang Zhe , Wang Qishan , Pan Yuchun , Wang Zhen 
Published: October 2024

AbstractPigs are crucial sources of meat and protein, valuable animal models, and potential donors for xenotransplantation. However, the existing reference genome for pigs is incomplete, with thousands of segments and missing centromeres and telomeres, which limits our understanding of the important traits in these genomic regions. To address this issue, we present a near complete genome assembly for the Jinhua pig (JH-T2T), constructed using PacBio HiFi and ONT long reads. This assembly includes all 18 autosomes and the X and Y sex chromosomes, with only six gaps. It features annotations of 46.90% repetitive sequences, 35 telomeres, 17 centromeres, and 23,924 high-confident genes. Compared to the Sscrofa11.1, JH-T2T closes nearly all gaps, extends sequences by 177 Mb, predicts more intact telomeres and centromeres, and gains 799 more genes and loses 114 genes. Moreover, it enhances the mapping rate for both Western and Chinese local pigs, outperforming Sscrofa11.1 as a reference genome. Additionally, this comprehensive genome assembly will facilitate large-scale variant detection and enable the exploration of genes associated with pig domestication, such asGPAM,CYP2C18,LY9,ITLN2, andCHIA. Our findings represent a significant advancement in pig genomics, providing a robust resource that enhances genetic research, breeding programs, and biomedical applications.
Direct M2 macrophage co-culture overrides viscoelastic hydrogel mechanics to promote fibroblast activation
Authors: Astrab Leilani R. , Skelton Mackenzie L. , Caliari Steven R. 
Published: October 2024

AbstractFibroblast activation drives fibrotic diseases such as pulmonary fibrosis. However, the complex interplay of how tissue mechanics and macrophage signals combine to influence fibroblast activation is not well understood. Here, we use hyaluronic acid hydrogels as a tunable cell culture system to mimic lung tissue stiffness and viscoelasticity. We applied this platform to investigate the influence of macrophage signaling on fibroblast activation. Fibroblasts cultured on stiff (50 kPa) hydrogels mimicking fibrotic tissue exhibit increased activation as measured by spreading as well as type I collagen and cadherin-11 expression compared to fibroblasts cultured on soft (1 kPa) viscoelastic hydrogels mimicking normal tissue. These trends were unchanged in fibroblasts cultured with macrophage-conditioned media. However, fibroblasts directly co-cultured with M2 macrophages show increased activation, even on soft viscoelastic hydrogels that normally suppress activation. Inhibition of interleukin 6 (IL6) signaling does not change activation in fibroblast-only cultures but ameliorates the pro-fibrotic effects of M2 macrophage co-culture. These results underscore the ability of direct M2 macrophage co-culture to override hydrogel viscoelasticity to promote fibroblast activation in an IL6-dependent manner. This work also highlights the utility of using hydrogels to deconstruct complex tissue microenvironments to better understand the interplay between microenvironmental mechanical and cellular cues.
Identification of novel key genes and signaling pathways in hypertrophic cardiomyopathy: evidence from bioinformatics and next generation sequencing data analysis
Authors: Vastrad Basavaraj , Vastrad Chanabasayya 
Published: October 2024

AbstractHypertrophic cardiomyopathy (HCM) is a global health problem characterized by left ventricle become thick and stiff with effect of indication including chest pain, fluttering, fainting and shortness of breath. In this investigation, we aimed to identify diagnostic markers and analyzed the therapeutic potential of essential genes. Next generation sequencing (NGS) dataset GSE180313 was obtained from the Gene Expression Omnibus (GEO) database and used to identify differentially expressed genes (DEGs) in HCM. DEGs were screened using the DESeq2 Rbioconductor tool. Then, Gene Ontology (GO) and REACTOME pathway enrichment analyses were performed. Moreover, a protein-protein interaction (PPI) network of the DEGs was constructed, and module analysis was performed. Next, miRNA-hub gene regulatory network and TF-hub gene regulatory network were constructed and analyzed. Finally, diagnostic values of hub genes were assessed by by receiver operating characteristic (ROC) curve analysis. By performing DEGs analysis, total 958 DEGs (479 up regulated genes and 479 down regulated genes) were successfully identified from GSE180313, respectively. GO and REACTOME pathway enrichment analyses revealed that GO functions and signaling pathways were significantly enriched including response to stimulus, multicellular organismal process, metabolism and extracellular matrix organization. The hub genes of FN1, SOX2, TUBA4A, RPS2, TUBA1C, ESR1, SNCA, LCK, PAK1 and APLNR might be associated with HCM. The hub gens of FN1 and TPM3, together with corresponding predicted miRNAs (e.g., hsa-mir-374a-5p and hsa-miR-8052), and SH3KBP1 and ESR1 together with corresponding predicted TFs (e.g PRRX2 and STAT3) were found to be significantly correlated with HCM. This investigation could serve as a basis for further understanding the molecular pathogenesis and potential therapeutic targets of HCM.
Reactive Oxygen Detoxification Contributes toMycobacterium abscessusAntibiotic Survival
Authors: Bates Nicholas A. , Rodriguez Ronald , Drwich Rama , Ray Abigail , Stanley Sarah A. , Penn Bennett H. 
Published: October 2024

ABSTRACTWhen a population of bacteria encounter a bactericidal antibiotic most cells die rapidly. However, a sub-population, known as “persister cells”, can survive for prolonged periods in a non-growing, but viable, state. Persister cell frequency is dramatically increased by stresses such as nutrient deprivation, but it is unclear what pathways are required to maintain viability, and how this process is regulated. To identify the genetic determinants of antibiotic persistence in mycobacteria, we carried out transposon mutagenesis high-throughput sequencing (Tn-Seq) screens inMycobacterium abscessus(Mabs). This analysis identified genes essential in both spontaneous and stress-induced persister cells, allowing the first genetic comparison of these states in mycobacteria, and unexpectedly identified multiple genes involved in the detoxification of reactive oxygen species (ROS). We found that endogenous ROS were generated following antibiotic exposure, and that the KatG catalase-peroxidase contributed to survival in both spontaneous and starvation-induced persisters. We also found that that hypoxia significantly impaired bacterial killing, and notably, in the absence of oxygen, KatG became dispensable. Thus, the lethality of some antibiotics is amplified by toxic ROS accumulation, and persister cells depend on detoxification systems to remain viable.
Analysis of the functioning of temporary dialysis catheters in patients with COVID-19
Authors: Ponte Bruno Jeronimo , Dib Viviane Galli , Oliveira Portela Felipe Soares , Magnani Arthur Souza , Silva Marcela Juliano , Pinheiro Lucas Lembrança , Wolosker Nelson 
Published: October 2024

2.AbstractIntroductionPatients with acute renal failure requiring hemodialysis should use temporary hemodialysis catheters (THC) due to the urgency and potential reversibility of the condition. So far, three studies in North America indicate a higher risk of catheter-related issues in COVID-19 patients needing hemodialysis. This study examines the functionality and complications of temporary hemodialysis access in COVID-19 patients at a Brazilian hospital.MethodologyA prospective analysis was conducted at a COVID-19 referral center between May and July 2020. During this time, the Vascular Surgery team implanted temporary hemodialysis catheters in 107 patients. The patients were followed, and demographic and clinical characteristics that could be correlated with catheter malfunction were analyzed.ResultsOf the 107 patients studied, 22 (20,6%) experienced complications related to the catheter. Eighteen (16,8%) had malfunctions, and 4 (3,7%) had infections. Five patients evolved with unfavorable clinical conditions and did not undergo catheter replacement. Thirteen patients with malfunctions had catheter tip thrombosis as the cause of the malfunction. Among the variables analyzed, only the need for orotracheal intubation(p 0,009), deep vein thrombosis(p 0,01), and a history of a previous catheter(p 0,002)were found to be correlated with a higher risk of malfunctioning.ConclusionThe rate of temporary high-flow catheter malfunction in patients with COVID-19 is similar to that in patients without this disease. Previous catheter use, the necessity for OTI, and venous thrombosis were the main predictors of catheter malfunction.
An open annotated dataset and baseline machine learning model for segmentation of vertebrae with metastatic bone lesions from CT
Authors: Haouchine Nazim , Hackney David B. , Pieper Steve D. , Wells William M. , Sanhinova Malika , Balboni Tracy A. , Spektor Alexander , Huynh Mai A. , Kozono David E. , Doyle Patrick , Alkalay Ron N. 
Published: October 2024

AbstractAutomatic analysis of pathologic vertebrae from computed tomography (CT) scans could significantly improve the diagnostic management of patients with metastatic spine disease. We provide the first publicly available annotated imaging dataset of cancerous CT spines to help develop artificial intelligence frameworks for automatic vertebrae segmentation and classification. This collection contains a dataset of 55 CT scans collected on patients with various types of primary cancers at two different institutions. In addition to raw images, data include manual segmentations and contours, vertebral level labeling, vertebral lesion-type classifications, and patient demographic details. Our automated segmentation model uses nnU-Net, a freely available open-source framework for deep learning in healthcare imaging, and is made publicly available. This data will facilitate the development and validation of models for predicting the mechanical response to loading and the resulting risk of fractures and spinal deformity.
Antibiotic use in the past 8 years and gut microbiota composition
Authors: Baldanzi Gabriel , Larsson Anna , Sayols-Baixeras Sergi , Dekkers Koen F. , Hammar Ulf , Nguyen Diem , Graells Tíscar , Ahmad Shafqat , Volpiano Camila Gazolla , Meric Guillaume , Järhult Josef D. , Tängdén Thomas , Ludvigsson Jonas F. , Lind Lars , Sundström Johan , Michaëlsson Karl , Ärnlöv Johan , Kennedy Beatrice , Orho-Melander Marju , Fall Tove 
Published: October 2024

ABSTRACTBACKGROUNDDisruptions in gut microbiota have been implicated in cardiometabolic disorders and other health outcomes. Antibiotics are known gut microbiota disruptors, but their long-term consequences on taxonomic composition of the gut microbiome remain underexplored.MethodsWe investigated associations between register-based oral antibiotic use over 8 years and gut microbiota composition assessed with fecal shotgun metagenomics in 15,131 adults from the Swedish population-based studies SCAPIS, MOS, and SIMPLER. We applied multivariable regression models with the number of prescriptions in three pre-specified periods before fecal sampling (<1 year, 1–4, 4–8 years) as the main exposures and adjusted for sociodemographics, lifestyle, and comorbidities. Secondary analyses included participants with only one antibiotic course or none.ResultsAntibiotic use <1 year before fecal sampling was associated with the greatest reduction in gut microbiota species diversity; however, antibiotic use 1–4 years and 4–8 years earlier was also associated with decreased diversity. Clindamycin, fluoroquinolones, and flucloxacillin accounted for most of the associations between antibiotic use and the abundance of individual species across all periods. Use of these three antibiotics 4–8 years earlier was associated with altered abundance of 10–14% of the species studied; use of penicillin V, extended-spectrum penicillins, and nitrofurantoin were associated with altered abundance of only a few species. Similar results were found when comparing one antibiotic course 4–8 years before sampling vs. none in the past 8 years.CONCLUSIONCommonly prescribed antibiotics like clindamycin, fluoroquinolones, and the narrow-spectrum flucloxacillin appear to have long-lasting consequences for the gut microbiota.
Integrated cell type-specific analysis of blood and gut identifies matching eQTL for 140 IBD risk loci and entrectinib as possible repurposing candidate
Authors: Perée Hélène , Petrov Viacheslav A , Tokunaga Yumie , Kvasz Alexander , Vieujean Sophie , Regimont Sarah , Mni Myriam , Wéry Marie , Azarzar Samira , Jacques Sophie , Fouillien Nicolas , Karim Latifa , Deckers Manon , Detry Emilie , Mayer Alice , Stephan Raafat , Harshman Keith , Mizoro Yasutaka , Reenaers Catherine , Van Kemseke Catherine , Warling Odile , Labille Virginie , Kropp Sophie , Poncin Maxime , Moreau Anne Catherine , Servais Benoit , Joly Jean-Philippe ,   SYSCID Consortium,   BRIDGE Consortium, Coppieters Wouter , Dermitzakis Emmanouil , Louis Edouard , Georges Michel , Takeda Haruko , Rahmouni Souad 
Published: October 2024

AbstractGenes whose expression is affected in a consistent manner by GWAS-identified risk variants and the disease process, constitute preferred drug targets. We herein combine integrated cis-eQTL analysis in 27 blood cell populations and 43 intestinal cell types of the ileum, colon and rectum, and information on gene expression in patients, to search for putative drug targets for inflammatory bowel disease (IBD). We detect >95K cis-eQTL that affect >13K e-genes and cluster in >24K regulatory modules (RM). We uncover matching RM for 140 risk loci, implicating >300 e-genes not previously connected to IBD, and find 152 IBD-matching e-genes whose expression is perturbed in the blood or gut of patients. We identify entrectinib, a small molecule inhibiting the NRLP3 inflammasome by binding NEK7, as a promising repurposing candidate for IBD.
Optimizing Clinical Data Availability: Extracting Pulmonary Embolism Diagnoses from Radiology Impressions with GPT-4o
Authors: Mahyoub Mohammed , Dougherty Kacie , Shukla Ajit 
Published: October 2024

AbstractBackgroundPulmonary embolism (PE) is a life-threatening condition that requires timely diagnosis to reduce mortality. Radiology reports, particularly the Impression sections, play a critical role in diagnosing PE. However, manually extracting this information from large volumes of reports is challenging. This study aims to develop an advanced natural language processing (NLP) system using GPT-4o to automatically extract PE diagnoses from radiology report impressions, enhancing clinical workflows and decision-making.Materials and MethodsWe developed two text classification models: a fine-tuned Clinical Longformer (as a baseline model) and GPT-4o. Models were trained using 1,000 radiology report impressions and validated on 200 samples, with a post-deployment evaluation conducted using 500 operational records. The primary dataset was sourced from an electronic medical record relational database, and key metrics such as sensitivity, specificity, and F1 score were used to evaluate model performance.ResultsGPT-4o achieved superior performance with 100% sensitivity, specificity, and F1 score, outperforming the Clinical Longformer. Post-deployment, GPT-4o continued to perform flawlessly, identifying all positive PE cases without false positives or false negatives. The model successfully streamlined the clinical workflow, reducing the burden of manual review and enhancing diagnostic accuracy.
Molecular and cell phenotype programs in oral epithelial cells directed by co-exposure to arsenic and smokeless tobacco
Authors: Das Samrat , Thakur Shefali , Cahais Vincent , Virard François , Claeys Liesel , Renard Claire , Cuenin Cyrille , Cros Marie-Pierre , Keïta Stéphane , Venuti Assunta , Sirand Cécilia , Ghantous Akram , Herceg Zdenko , Korenjak Michael , Zavadil Jiri 
Published: October 2024

ABSTRACTChronic arsenic exposure can lead to various health issues, including cancer. Concerns have been mounting about the enhancement of arsenic toxicity through co-exposure to various prevalent lifestyle habits. Smokeless tobacco products are commonly consumed in South Asian countries, where their use frequently co-occurs with exposure to arsenic from contaminated groundwater. To decipher thein vitromolecular and cellular responses to arsenic and/or smokeless tobacco, we performed temporal multi-omics analysis of the transcriptome and DNA methylome remodelling in exposed hTERT-immortalized human normal oral keratinocytes (NOK), as well as arsenic and/or smokeless tobacco genotoxicity and mutagenicity investigations in NOK cells and in human p53 knock-in murine embryonic fibroblasts (Hupki MEF). RNAseq results from acute exposures to arsenic alone and in combination with smokeless tobacco extract revealed upregulation of genes with roles in cell cycle changes, apoptosis and inflammation responses. This was in keeping with global DNA hypomethylation affecting genes involved in the same processes in response to chronic treatment in NOK cells. At the phenotypic level, we observed a dose-dependent decrease in NOK cell viability, induction of DNA damage, cell cycle changes and increased apoptosis, with the most pronounced effects observed under arsenic and SLT co-exposure conditions. Live-cell imaging experiments indicated that the DNA damage likely resulted from induction of apoptosis, an observation validated by a lack of exome-wide mutagenesis in response to chronic exposure to arsenic and/or smokeless tobacco. In sum, our integrative omics study provides novel insights into the acute and chronic responses to arsenic and smokeless tobacco (co-)exposure, with both types of responses converging on several key mechanisms associated with cancer hallmark processes. The generated rich catalogue of molecular programs in oral cells regulated by arsenic and smokeless tobacco (co-)exposure may provide bases for future development of biomarkers for use in molecular epidemiology studies of exposed populations at risk of developing oral cancer.