bluuebunny/crossref_metadata_2025_split huggingface dataset:
AptamerRunner: An accessible aptamer structure prediction and clustering algorithm for visualization of selected aptamers
Authors: Ruiz-Ciancio Dario , Veeramani Suresh , Embree Eric , Ortman Chris , Thiel Kristina W. , Thiel William H 
Published: November 2023

ABSTRACTAptamers are short single-stranded DNA or RNA molecules with high affinity and specificity for targets and are generated using the iterative Systematic Evolution of Ligands by EXponential enrichment (SELEX) process. Next-generation sequencing (NGS) revolutionized aptamer selections by allowing a more comprehensive analysis of SELEX-enriched aptamers as compared to Sanger sequencing. The current challenge with aptamer NGS datasets is identifying a diverse cohort of candidate aptamers with the highest likelihood of successful experimental validation. Herein we present AptamerRunner, an aptamer clustering algorithm that generates visual networks of aptamers that are related by sequence and/or structure. These networks can then be overlayed with ranking data, such as fold enrichment or data from scoring algorithms. The ability to visually integrate data using AptamerRunner represents a significant advancement over existing clustering tools by providing a natural context to depict groups of aptamers from which ranked or scored candidates can be chosen for experimental validation. The inherent flexibility, user-friendly design, and prospects for future enhancements with AptamerRunner has broad-reaching implications for aptamer researchers across a wide range of disciplines.GRAPHICAL ABSTRACT
No evidence for the presence and control of tumor growth by cytoplasmic stress granules in pancreatic cancer
Authors: Libert Maxime , Fain Jean , Bouchart Christelle , Arsenijevic Tatjana , Van Laethem Jean-Luc , Jacquemin Patrick 
Published: November 2023

AbstractCytoplasmic stress granules (SG) are attracting growing attention in cancer research1. As such, a study published in Cell2has certainly served as a trigger for this trend which currently asserts that SG are a relevant therapeutic target. Here, we would like to express a warning about the conclusions of this article, as well as of the subsequent study3, and more generally on a methodological approach frequently used in research studying SG in cancer and which we believe to be misleading.
Copepodamides in marine and freshwater copepods-similar but different
Authors: Arnoldt Sina , Pourdanandeh Milad , Spikkeland Ingvar , Andersson Mats X. , Selander Erik 
Published: November 2023

AbstractMarine copepods, the most abundant group of zooplankton in the worlds oceans, imprint their surrounding waters with chemical cues, called copepodamides. Copepodamides induce defensive traits such as toxin production, bioluminescence, and colony size plasticity in a variety of marine phytoplankton. The role of copepodamides in freshwater ecosystems is, however, unknown. Here we report the consistent presence of copepodamides in copepods from six Swedish lakes. Copepodamide concentrations in freshwater copepods are similar to those of marine copepods, around 0.1 ppt of dry mass in millimetre sized individuals. The composition substantially overlaps with marine copepodamides but is also distinctly different. Freshwater copepods are largely dominated by one of the two subgroups of copepodamides, the dihydro-copepodamides, whereas marine copepods more commonly contain representatives from both subgroups. We describe 10 new copepodamide structures, four of which only found in freshwater copepods. Taxonomic groups had consistent copepodamide profiles across sampling sites and timepoints, supporting the presence of species specific copepodamide signatures. The presence of copepodamides in freshwater environments warrants study into their potential function as predator alarm cues also in freshwater systems.
Only cortical prediction error signals are involved in visual learning, despite availability of subcortical prediction error signals
Authors: Kim Dongho , Wang Zhiyan , Sakagami Masamichi , Sasaki Yuka , Watanabe Takeo 
Published: November 2023

AbstractBoth the midbrain systems, encompassing the ventral striatum (VS), and the cortical systems, including the dorsal anterior cingulate cortex (dACC), play roles in reinforcing and enhancing learning. However, the specific contributions of signals from these regions in learning remains unclear. To investigate this, we examined how VS and dACC are involved in visual perceptual learning (VPL) through an orientation discrimination task. In the primary experiment, subjects fasted for 5 hours before each of 14 days of training sessions and 3 days of test sessions. Subjects were rewarded with water for accurate trial responses. During the test sessions, BOLD signals were recorded from regions including VS and dACC. Although BOLD signals in both areas were associated with positive and negative RPEs, only those in dACC associated with negative RPE showed a significant correlation with performance improvement. Additionally, no significant correlation was observed between BOLD signals associated with RPEs in VS and dACC. These results suggest that although signals associated with positive and negative RPEs from both midbrain and cortical systems are readily accessible, only RPE signals in the prefrontal system, generated without linking to RPE signals in VS, are utilized for the enhancement of VPL.
Azole resistance: Insights from Y132 substitutions inCandidasterol 14α-demethylase
Authors: Rao R. Shyama Prasad , Pinto Larina , Suravajhala Renuka , Shenoy Belle Damodara , Ghate Sudeep D. 
Published: November 2023

AbstractBackgroundAzole-resistantCandidainfections are on the rise. Resistant substitutions at Y132 in sterol 14α-demethylase, the key target of azole drugs, are frequent. However, it is unclear why only some Y132 substitutions are favoured or how they exert differential effects on different azoles.Materials and MethodsReported instances of Y132 substitutions were collected from the literature. Extensive molecular dynamics simulations of sterol 14α-demethylase bound to fluconazole or VT1161 (VT1) were performed, and the ligand-binding free energies were computed to quantify the effects of various Y132 substitutions on azole binding/interactions.ResultsThree azole-resistant substitutions, Y to C/F/H, were reported at residue position 132 in sterol 14α-demethylase. The Y132H was the most common substitution inC. albicans, while it was Y132F in other species. Ligand-binding free energies were -13.81 kcal/mol and -35.04 kcal/mol for fluconazole and VT1, respectively. There were differences in the ligand-binding free energies after substitutions compared to the wild type protein.ConclusionY132F and Y132H were the most frequent substitutions inCandidasterol 14α-demethylase. Far higher binding free energy of fluconazole in comparison with VT1 might partly explain its susceptibility to azole-resistant substitutions. The results give key insights into azole resistance, and antifungal drug discovery and optimization.
ScRNAbox: Empowering Single-Cell RNA Sequencing on High Performance Computing Systems
Authors: Thomas R.A. , Fiorini M.R. , Amiri S. , Fon E.A. , Farhan S.M.K. 
Published: November 2023

AbstractMotivationSingle-cell RNA sequencing (scRNAseq) offers powerful insights, but the surge in sample sizes demands more computational power than local workstations can provide. Consequently, high-performance computing (HPC) systems have become imperative. Existing web apps designed to analyze scRNAseq data lack scalability and integration capabilities, while analysis packages demand coding expertise, hindering accessibility.ResultsIn response, we introduce scRNAbox, an innovative scRNAseq analysis pipeline meticulously crafted for HPC systems. This end-to-end solution, executed via the SLURM workload manager, efficiently processes raw data from standard and Hashtag samples. It incorporates quality control filtering, sample integration, clustering, cluster annotation tools, and facilitates cell type-specific differential gene expression analysis between two groups.ImplementationOpen-source code and comprehensive usage instructions with examples are available athttps://neurobioinfo.github.io/scrnabox/site/.Supplementary InformationSupplementary data are available at Bioinformatics online.
Development and Analysis of Multiscale Models for Tuberculosis: From Molecules to Populations
Authors: Nanda Pariksheet , Budak Maral , Michael Christian T. , Krupinsky Kathryn , Kirschner Denise E. 
Published: November 2023

AbstractAlthough infectious disease dynamics are often analyzed at the macro-scale, increasing numbers of drug-resistant infections highlight the importance of within-host modeling that simultaneously solves across multiple scales to effectively respond to epidemics. We review multiscale modeling approaches for complex, interconnected biological systems and discuss critical steps involved in building, analyzing, and applying such models within the discipline of model credibility. We also present our two tools: CaliPro, for calibrating multiscale models (MSMs) to datasets, and tunable resolution, for fine- and coarse-graining sub-models while retaining insights. We include as an example our work simulating infection withMycobacterium tuberculosisto demonstrate modeling choices and how predictions are made to generate new insights and test interventions. We discuss some of the current challenges of incorporating novel datasets, rigorously training computational biologists, and increasing the reach of MSMs. We also offer several promising future research directions of incorporating within-host dynamics into applications ranging from combinatorial treatment to epidemic response.
Gut protectiveKlebsiellaspecies promotes microbiota recovery and pathobiont clearance while preventing inflammation
Authors: Cabral Vitor , Oliveira Rita A. , Correia Margarida B. , Pedro Miguel F. , Ubeda Carles , Xavier Karina B. 
Published: November 2023

AbstractThe microbiota inhabiting the mammalian gut serves as a protective barrier against pathogen invasion through a mechanism known as colonization resistance. Antibiotic treatments can inadvertently disturb the gut microbiota, compromising colonization resistance and increasing host’s susceptible to infections. Non-pneumoniae Klebsiellaspp. members of the gut microbiota play a crucial role in colonization resistance and clearance from the gut of pathogenicEnterobacteriaceaefollowing antibiotic-induced perturbations. Specifically,Klebsiellastrain ARO112 a gut microbiota isolate, can effectively resist and clearEscherichia colicolonization after antibiotic-induced dysbiosis.We assessed the potential ofKlebsiellasp ARO112 to promote clearance ofEnterobacteriaceaepathobiont Adherent-InvasiveE. coli(AIEC) in an Inflammatory Bowel Disease (IBD) mouse model susceptible to inflammatory episodes. In antibiotic-treated IBD-predisposed mice infected with the AIEC,Klebsiellasp. ARO112 promoted a faster recovery of gut microbiota members potentially involved in butyrate production and accelerated pathobiont clearance. Functionally, ARO112-driven microbiota recovery promoted higher butyrate levels and prevented intestinal inflammation compared to untreated animals. Conversely, treatment with the well-known probioticE. coliNissle 1917 enhanced AIEC colonization and inflammation. Furthermore, we assessed the safety of ARO112 as a potential next-generation probiotic; phenotypic comparison of ARO112 against closely relatedEnterobacteriaceaerevealed its lower pathogenic potential, including being more recalcitrant to antibiotic resistance acquisition.Overall, our results showing thatKlebsiellasp. ARO112 can resolve infections while contributing to the promotion of intestinal health, underscore its potential as a biotherapy agent that can disrupt inflammation-treatment-infection cycles. This potential extends beyond IBD patients, encompassing individuals with other inflammatory-based conditions related to microbiota imbalances.
COVID-19-related research data availability and quality according to the FAIR principles: A meta-research study
Authors: Sofi-Mahmudi Ahmad , Raittio Eero , Khazaei Yeganeh , Ashraf Javed , Schwendicke Falk , Uribe Sergio E. , Moher David 
Published: November 2023

AbstractBackgroundAs per the FAIR principles (Findable, Accessible, Interoperable, and Reusable), scientific research data should be findable, accessible, interoperable, and reusable. The COVID-19 pandemic has led to massive research activities and an unprecedented number of topical publications in a short time. There has not been any evaluation to assess if this COVID-19-related research data complied with FAIR principles (or FAIRness) so far.ObjectiveOur objective was to investigate the availability of open data in COVID-19-related research and to assess compliance with FAIRness.MethodsWe conducted a comprehensive search and retrieved all open-access articles related to COVID-19 from journals indexed in PubMed, available in the Europe PubMed Central database, published from January 2020 through June 2023, using themetareadrpackage. Usingrtransparent, a validated automated tool, we identified articles that included a link to their raw data hosted in a public repository. We then screened the link and included those repositories which included data specifically for their pertaining paper. Subsequently, we automatically assessed the adherence of the repositories to the FAIR principles using FAIRsFAIR Research Data Object Assessment Service (F-UJI) andrfujipackage. The FAIR scores ranged from 1–22 and had four components. We reported descriptive analysis for each article type, journal category and repository. We used linear regression models to find the most influential factors on the FAIRness of data.Results5,700 URLs were included in the final analysis, sharing their data in a general-purpose repository. The mean (standard deviation, SD) level of compliance with FAIR metrics was 9.4 (4.88). The percentages of moderate or advanced compliance were as follows: Findability: 100.0%, Accessibility: 21.5%, Interoperability: 46.7%, and Reusability: 61.3%. The overall and component-wise monthly trends were consistent over the follow-up. Reviews (9.80, SD=5.06, n=160), and articles in dental journals (13.67, SD=3.51, n=3) and Harvard Dataverse (15.79, SD=3.65, n=244) had the highest mean FAIRness scores, whereas letters (7.83, SD=4.30, n=55), articles in neuroscience journals (8.16, SD=3.73, n=63), and those deposited in GitHub (4.50, SD=0.13, n=2,152) showed the lowest scores. Regression models showed that the most influential factor on FAIRness scores was the repository (R2=0.809).ConclusionThis paper underscored the potential for improvement across all facets of FAIR principles, with a specific emphasis on enhancing Interoperability and Reusability in the data shared within general repositories during the COVID-19 pandemic.
Two Septin Complexes Mediate Actin Dynamics During Cell Wound Repair
Authors: Stjepić Viktor , Nakamura Mitsutoshi , Hui Justin , Parkhurst Susan M. 
Published: November 2023

ABSTRACTCells have robust wound repair systems to prevent further damage or infection and to quickly restore cell cortex integrity when exposed to mechanical and chemical stress. Actomyosin ring formation and contraction at the wound edge are major events during closure of the plasma membrane and underlying cytoskeleton during cell wound repair. Here, we show that all fiveDrosophilaSeptins are required for efficient cell wound repair. Based on their different recruitment patterns and knockdown/mutant phenotypes, two distinct Septin complexes, Sep1-Sep2-Pnut and Sep4-Sep5-Pnut, are assembled to regulate actin ring assembly, contraction, and remodeling during the repair process. Intriguingly, we find that these two Septin complexes have different F-actin bending activities. In addition, we find that Anillin regulates the recruitment of only one of two Septin complexes upon wounding. Our results demonstrate that two functionally distinct Septin complexes work side-by-side to discretely regulate actomyosin ring dynamics during cell wound repair.
Transcriptional profile of the rat cardiovascular system at single cell resolution
Authors: Arduini Alessandro , Fleming Stephen J. , Xiao Ling , Hall Amelia W. , Akkad Amer-Denis , Chaffin Mark , Bendinelli Kayla J. , Tucker Nathan R. , Papangeli Irinna , Mantineo Helene , Babadi Mehrtash , Stegmann Christian M. , García-Cardeña Guillermo , Lindsay Mark E. , Klattenhoff Carla , Ellinor Patrick T. 
Published: November 2023

AbstractBackgroundDespite the critical role of the cardiovascular system, our understanding of its cellular and transcriptional diversity remains limited. We therefore sought to characterize the cellular composition, phenotypes, molecular pathways, and communication networks between cell types at the tissue and sub-tissue level across the cardiovascular system of the healthy Wistar rat, an important model in preclinical cardiovascular research. We obtained high quality tissue samples under controlled conditions that reveal a level of cellular detail so far inaccessible in human studies.Methods and ResultsWe performed single nucleus RNA-sequencing in 78 samples in 10 distinct regions including the four chambers of the heart, ventricular septum, sinoatrial node, atrioventricular node, aorta, pulmonary artery, and pulmonary veins (PV), which produced an aggregate map of 505,835 nuclei. We identified 26 distinct cell types and additional subtypes, including a number of rare cell types such as PV cardiomyocytes and non-myelinating Schwann cells (NMSCs), and unique groups of vascular smooth muscle cells (VSMCs), endothelial cells (ECs) and fibroblasts (FBs), which gave rise to a detailed cell type distribution across tissues. We demonstrated differences in the cellular composition across different cardiac regions and tissue-specific differences in transcription for each cell type, highlighting the molecular diversity and complex tissue architecture of the cardiovascular system. Specifically, we observed great transcriptional heterogeneities among ECs and FBs. Importantly, several cell subtypes had a unique regional localization such as a subtype of VSMCs enriched in the large vasculature. We found the cellular makeup of PV tissue is closer to heart tissue than to the large arteries. We further explored the ligand-receptor repertoire across cell clusters and tissues, and observed tissue-enriched cellular communication networks, including heightenedNppa-Npr1/2/3signaling in the sinoatrial node.ConclusionsThrough a large single nucleus sequencing effort encompassing over 500,000 nuclei, we broadened our understanding of cellular transcription in the healthy cardiovascular system. The existence of tissue-restricted cellular phenotypes suggests regional regulation of cardiovascular physiology. The overall conservation in gene expression and molecular pathways across rat and human cell types, together with our detailed transcriptional characterization of each cell type, offers the potential to identify novel therapeutic targets and improve preclinical models of cardiovascular disease.
Antibiotic resistance alters the ability ofPseudomonas aeruginosato invade the respiratory microbiome
Authors: Lindon Selina , Shah Sarah , Gifford Danna R. , Gomis Font Maria A. , Kaur Divjot , Oliver Antonio , MacLean R. Craig , Wheatley Rachel M. 
Published: November 2023

AbstractThe emergence and spread of antibiotic resistance in bacterial pathogens is a global health threat. One important unanswered question is how antibiotic resistance influences the ability of a pathogen to invade the host-associated microbiome. Here we investigate how antibiotic resistance impacts the ability of the opportunistic bacterial pathogenPseudomonas aeruginosato invade the respiratory microbiome, by measuring the ability ofP. aeruginosaspontaneous antibiotic resistant mutants to invade pre-established cultures of commensal respiratory microbes. We find that commensal respiratory microbes tend to inhibit the growth ofP. aeruginosa, and antibiotic resistance is a double-edged sword that can either help or hinder the ability ofP. aeruginosato overcome this inhibition. The directionality of this help or hinderance depends on bothP. aeruginosagenotype and respiratory microbe identity. Antibiotic resistance facilitates the invasion ofP. aeruginosaintoStaphylococcus lugdunensis,yet impairs invasion intoRothia mucilaginosaandStaphylococcus epidermidis.Streptococcusspecies provide the strongest inhibition toP. aeruginosainvasion, and this is maintained regardless of antibiotic resistance genotype. Our study demonstrates how antibiotic resistance can alter the ability of a bacterial pathogen to invade the respiratory microbiome and suggests that attempts to manipulate the microbiome should focus on promoting the growth of commensals that can provide robust inhibition of both wildtype and antibiotic resistant pathogen strains.
GTExome: Modeling commonly expressed missense mutations in the human genome
Authors: Hoffman Jill , Tan Henry , Sandoval-Cooper Clara , de Villiers Kaelyn , Reed Scott M. 
Published: November 2023

AbstractA web application, GTExome, is described that quickly identifies, classifies, and models missense mutations in commonly expressed human proteins. GTExome can be used to categorize genomic mutation data with tissue specific expression data from the Genotype-Tissue Expression (GTEx) project. Commonly expressed missense mutations in proteins from a wide range of tissue types can be selected and assessed for modeling suitability. Information about the consequences of each mutation is provided to the user including if disulfide bonds, hydrogen bonds, or salt bridges are broken, buried prolines introduced, buried charges are created or lost, charge is swapped, a buried glycine is replaced, or if the residue that would be removed is a proline in the cis configuration. Also, if the mutation site is in a binding pocket the number of pockets and their volumes are reported. The user can assess this information and then select from available experimental or computationally predicted structures of native proteins to create, visualize, and download a model of the mutated protein using Fast and Accurate Side-chain Protein Repacking (FASPR). For AlphaFold modeled proteins, confidence scores for native proteins are provided. Using this tool, we explored a set of 9,666 common missense mutations from a variety of tissues from GTEx and show that most mutations can be modeled using this tool to facilitate studies of proteinprotein and protein-drug interactions. The open-source tool is freely available athttps://pharmacogenomics.clas.ucdenver.edu/gtexome/Author SummaryGTExome greatly simplifies the process of studying the three-dimensional structures of proteins containing missense mutations that are critical to understanding human health. In contrast to current state-of-the-art methods, users with no external software or specialized training can rapidly produce three-dimensional structures of any possible mutation in nearly any protein in the human exome. Accomplishing this requires reliance on AlphaFold based structural models. We therefore compared the protein models created by GTExome where possible to known experimental structures. We find that by avoiding specific mutations, the majority of proteins are amenable to being modeled by GTExome with similar results to the direct use of AlphaFold.