bluuebunny/crossref_metadata_2025_split huggingface dataset:
Detection of genome structural variation in normal cells and tissues by single molecule sequencing
Authors: Heid Johanna , Huang Zhenqiu , Lee Moonsook , Makhortov Sergey , Pan Elizabeth , Montagna Cristina , Sun Shixiang , Vijg Jan , Maslov Alexander Y. 
Published: August 2024

AbstractDetecting somatic mutations in normal cells and tissues is notoriously challenging due to their low abundance, orders of magnitude below the sequencing error rate. While several techniques, such as single-cell and single-molecule sequencing, have been developed to identify somatic mutations, they are insufficient for detecting genomic structural variants (SVs), which have a significantly greater impact than single-nucleotide variants (SNVs). We introduce Single-Molecule Mutation Sequencing for Structural Variants (SMM-SV-seq), a novel method combining Tn5-mediated, chimera-free library preparation with the precision of error-corrected next-generation sequencing (ecNGS). This approach enhances SV detection accuracy without relying on independent supporting sequencing reads.Our validation studies on human primary fibroblasts treated with varying concentrations of the clastogen bleomycin demonstrated a significant, up to tenfold and dose-dependent, increase in deletions and translocations 24 hours post-treatment. Evaluating SMM-SV-seq’s performance against established computational tools for SV detection, such as Manta and DELLY, using a well-characterized human cell line, SMM-SV-seq showed precision and recall rates of 61.9% and 85.8%, respectively, significantly outperforming Manta (10% precision, 23% recall) and DELLY (15% precision, 32% recall). Using SMM-SV-seq, we documented clear, direct evidence of negative selection against structural variants over time. After a single 2 Gy dose of ionizing radiation, SVs in normal human primary fibroblasts peaked at 24 hours post-intervention and then declined to nearly background levels by day six, highlighting the cellular mechanisms that selectively disadvantage cells harboring these mutations. Additionally, SMM-SV-seq revealed that BRCA1-deficient human breast epithelial cells are more susceptible to the mutagenic effects of ionizing radiation compared to BRCA1-proficient isogenic control cells, suggesting a potential molecular mechanism for increased breast cancer risk in BRCA1 mutation carriers.SMM-SV-seq represents a significant advancement in genomic analysis, enabling the accurate detection of somatic structural variants in normal cells and tissues for the first time. This method complements our previously published Single-Molecule Mutation sequencing (SMM-seq), effective for detecting single-nucleotide variants (SNVs) and small insertions and deletions (INDELs). By addressing challenges such as self-ligation in library preparation and leveraging a powerful ecNGS strategy, SMM-SV-seq enhances the robustness of our genomic analysis toolkit. This breakthrough paves the way for new research into genetic variability and mutation processes, offering deeper insights that could advance our understanding of aging, cancer, and other human diseases.
ProCogGraph: A Graph-Based Mapping of Cognate Ligand Domain Interactions
Authors: Crown Matthew , Bashton Matthew 
Published: August 2024

AbstractMotivationMappings of domain-cognate ligand interactions can enhance our understanding of the core concepts of evolution and be used to aid docking and protein design. Since the last available cognate-ligand domain database was released, the PDB has grown significantly and new tools are available for measuring similarity and determining contacts.ResultsWe present ProCogGraph, a graph database of cognate-ligand domain mappings in PDB structures. Building upon the work of the predecessor database, PROCOGNATE, we use data-driven approaches to develop thresholds and interaction modes. We explore new aspects of domain-cognate ligand interactions, including the chemical similarity of bound cognate ligands and how domain combinations influence cognate ligand binding. Finally, we use the graph to add specificity to partial EC IDs, showing that ProCogGraph can complete partial annotations systematically through assigned cognate ligands.Availability and ImplementationThe ProCogGraph pipeline, database and flat files are available athttps://github.com/bashton-lab/ProCogGraphandhttps://doi.org/10.5281/zenodo.13165851.Contactmatthew.bashton@northumbria.ac.ukSupplementary informationSupplementary data are available atBioinformaticsonline.
PyBootNet: A Python Package for Bootstrapping and Network Construction
Authors: Akhavan Shayan R. , Kelley Scott T. 
Published: August 2024

ABSTRACTPyBootNet is a user-friendly Python package that integrates bootstrapping analysis and correlation network construction. The package offers functions for generating bootstrapped network metrics, statistically comparing network metrics among datasets, and visualizing bootstrapped networks. PyBootNet is designed to be accessible and efficient, with minimal dependencies and straightforward input requirements. To demonstrate its functionality, we applied PyBootNet functions to compare networks within two disparate microbial community datasets: a mouse gut microbiome study and a microbiome study of a built environment. The PyBootNet functions applied include data preprocessing, bootstrapping, correlation matrix calculation, network statistics computation, and network visualization. In both datasets, we show that PyBootNet can generate robust bootstrapped network metrics and identify significant differences in one or more network metrics between pairs of networks. We also show that PyBootNet can create bootstrapped network graphs and identify clusters of nodes that are highly interconnected. We also confirmed its computational efficiency and scalability, which allows it to handle large and complex datasets. PyBootNet provides a powerful and extendible Python bioinformatics solution for bootstrapping analysis and network construction that can be applied to microbial, gene, metabolite and other biological data appropriate for network correlation comparison and analysis.
Cspg4 sculpts oligodendrocyte precursor cell morphology
Authors: Bromley-Coolidge Samantha , Iruegas Diego , Appel Bruce 
Published: August 2024

AbstractThe extracellular matrix (ECM) provides critical biochemical and structural cues that regulate neural development. Chondroitin sulfate proteoglycans (CSPGs), a major ECM component, have been implicated in modulating oligodendrocyte precursor cell (OPC) proliferation, migration, and maturation, but their specific roles in oligodendrocyte lineage cell (OLC) development and myelinationin vivoremain poorly understood. Here, we use zebrafish as a model system to investigate the spatiotemporal dynamics of ECM deposition and CSPG localization during central nervous system (CNS) development, with a focus on their relationship to OLCs. We demonstrate that ECM components, including CSPGs, are dynamically expressed in distinct spatiotemporal patterns coinciding with OLC development and myelination. We found that zebrafish lackingcspg4function produced normal numbers of OLCs, which appeared to undergo proper differentiation. However, OPC morphology in mutant larvae was aberrant. Nevertheless, the number and length of myelin sheaths produced by mature oligodendrocytes were unaffected. These data indicate that Cspg4 regulates OPC morphogenesisin vivo, supporting the role of the ECM in neural development.
Computational Prediction of Multiple Antigen Epitopes
Authors: Viswanathan R. , Carroll M. , Roffe A. , Fajardo J.E. , Fiser A. 
Published: August 2024

AbstractMotivationIdentifying antigen epitopes is essential in medical applications, such as immunodiagnostic reagent discovery, vaccine design, and drug development. Computational approaches can complement low-throughput, time-consuming, and costly experimental determination of epitopes. Currently available prediction methods, however, have moderate success predicting epitopes, which limits their applicability. Epitope prediction is further complicated by the fact that multiple epitopes may be located on the same antigen and complete experimental data is often unavailable.ResultsHere, we introduce the antigen epitope prediction program ISPIPab that combines information from two feature-based methods and a docking-based method. We demonstrate that ISPIPab outperforms each of its individual classifiers as well as other state-of-the-art methods, including those designed specifically for epitope prediction. By combining the prediction algorithm with hierarchical clustering, we show that we can effectively capture epitopes that align with available experimental data while also revealing additional novel targets for future experimental investigations.Contactraji@yu.eduSupplementary informationSupplementary data are available atBioinformaticsonline.
An extension of the Benefit Risk Assessment of VaccinEs (BRAVE) Toolkit to evaluate Comirnaty and Spikevax vaccination in the European Union
Authors: Loedy Neilshan , Dorta Hector G , Abrams Steven , Crèvecoeur Jonas , Morales Daniel R. , Cohet Catherine , Willem Lander , Molenberghs Geert , Hens Niel , Kurz Xavier , Quinten Chantal , Verbeeck Johan 
Published: August 2024

AbstractIntroductionAmid the global COVID-19 pandemic, vaccines were conditionally authorised for human use to protect against severe infection. The BRAVE toolkit, a user-friendly R Shiny application, was developed retrospectively together with the European Medicine Agency (EMA) with the aim of fulfilling the need for flexible tools to assess vaccine benefits and risks during and outside a pandemic situation.MethodThis study employed BRAVE to evaluate the impact of COVID-19 mRNA vaccines across 30 EU/EEA countries by quantifying the number of prevented clinical events (i.e., confirmed infections, hospitalisations, intensive care unit (ICU) admissions, and deaths), using a probabilistic model informed by real-time incidence data and vaccine effectiveness estimates. The analysis assumes fixed population dynamics and behaviour. Additionally, BRAVE assesses risks associated with mRNA-based vaccines (myocarditis or pericarditis) by comparing observed incidence rates in vaccinated individuals with background incidence rates.ResultsmRNA vaccines were estimated to directly prevent 11.150 million (95% Confidence Interval (CI): 10.876 – 11.345) confirmed COVID-19 infections, 0.739 million (95% CI: 0.727 – 0.744) COVID-19 hospitalisations, 0.107 million (95% CI: 0.104 – 0.109) ICU admissions, and 0.187 million (95% CI: 0.182 – 0.189) COVID-19-related deaths in the EU/EEA between 13 December 2020 and 31 December 2021. Despite increased vaccination-associated myocarditis or pericarditis observed in younger men, the benefits of vaccination still outweigh these risks.ConclusionOur study supports the benefit/risk profile of COVID-19 vaccines and emphasises the utility of employing a flexible toolkit to assess risks and benefits of vaccination. This user-friendly and adaptable toolkit can serve as a blueprint for similar tools, enhancing preparedness for future public health crises.
Cross-organ Analysis Reveals Associations between Vascular Properties of the Retina, the Carotid and Aortic Artery, and the Brain
Authors: Ortín Vela Sofía , Bergmann Sven 
Published: August 2024

AbstractVascular properties of the retina are not only indicative of ocular but also systemic cardio- and cerebrovascular health. Yet, the extent to which retinal vascular morphology reflects that in other organs is not well understood. We used morphological vascular phenotypes derived from the brain, the carotid artery, the aorta, and the retina from the UK Biobank, with sample sizes between 18,808 and 68,000 subjects per phenotype. We examined the cross-organ phenotypic and genetic correlations, as well as common associated genes and pathways. White matter hyperintensities positively correlated with carotid intima-media thickness, lumen diameter, and aortic cross-sectional areas but negatively correlated with aortic distensibility. Retinal vascular density showed negative correlations with white matter hyperintensities, intima-media thickness, lumen diameter, and aortic areas, while positively correlating with aortic distensibility. Significant correlations were also observed between other retinal phenotypes and white matter hyperintensities, as well as with aortic phenotypes. Correcting for hypertension reduced the magnitude of these correlations, but the overall correlation structure largely persisted. Genetic correlations and gene enrichment analyses identified potential regulators of these phenotypes, with some shared genetic influence between retinal and non-retinal phenotypes. Our study sheds light on the complex interplay between vascular morphology across different organs, revealing both shared and distinct genetic underpinnings. This highlights the potential of retinal imaging as a non-invasive prognostic tool for systemic vascular health.
Peptide-aware chemical language model successfully predicts membrane diffusion of cyclic peptides
Authors: Feller Aaron L. , Wilke Claus O. 
Published: August 2024

AbstractLanguage modeling applied to biological data has significantly advanced the prediction of membrane penetration for small molecule drugs and natural peptides. However, accurately predicting membrane diffusion for peptides with pharmacologically relevant modifications remains a substantial challenge. Here, we introduce PeptideCLM, a peptide-focused chemical language model capable of encoding peptides with chemical modifications, unnatural or non-canonical amino acids, and cyclizations. We assess this model by predicting membrane diffusion of cyclic peptides, demonstrating greater predictive power than existing chemical language models. Our model is versatile and can be extended beyond membrane diffusion predictions to other target values. Its advantages include the ability to model macromolecules using chemical string notation, a largely unexplored domain, and a simple, flexible architecture that allows for adaptation to any peptide or other macromolecule dataset.
Myo-inositol and total NAA in the hippocampus are linked to CSF tau pathology in cognitively normal older adults
Authors: Noche JA , Vanderlip C , Wright S , Sordo L. , Head E , Stark CEL 
Published: August 2024

AbstractINTRODUCTIONUnderstanding relationships betweenin vivoneurometabolic changes and Alzheimer’s disease (AD) pathology in the hippocampus, a region vulnerable to early changes in AD, will support early diagnosis.METHODSTwo studies using1H-MRS examined concentrations of myo-inositol (MI), total creatine (tCr) and total NAA (tNAA) in the hippocampus. The first study compared hippocampal metabolite concentrations in healthy young and older adults and the second study assessed relationships between hippocampal metabolites and cerebrospinal fluid (CSF) measurements of Aβ42, phosphotau 181 (pTau181), and total tau (t-Tau) while adjusting for demographic covariates and spectral characteristics (linewidth, signal- to-noise ratio) in a separate group of older adults ranging from cognitively normal (CN) to AD-dementia.RESULTSHippocampal MI, but not tCr or tNAA, was increased in cognitively normal older versus young adults. Within the second older adult group, MI and tNAA, but not tCr, were linked to increases in CSF pTau181 and t-Tau, but not Aβ42.DISCUSSIONTau deposition in cognitively normal individuals is associated with biochemical changes related to glial reactivity and neural integrity in the hippocampus.
Centrocortin potentiates co-translational localization of its mRNA to the centrosome via dynein
Authors: Zein-Sabatto Hala , Brockett Jovan S. , Jin Li , Husbands Christian A. , Lee Jina , Fang Junnan , Buehler Joseph , Bullock Simon L. , Lerit Dorothy A. 
Published: August 2024

AbstractCentrosomes rely upon proteins within the pericentriolar material to nucleate and organize microtubules. Several mRNAs also reside at centrosomes, although less is known about how and why they accumulate there. We previously showed that localCentrocortin(Cen) mRNA supports centrosome separation, microtubule organization, and viability inDrosophilaembryos. Here, usingCenmRNA as a model, we examine mechanisms of centrosomal mRNA localization. We find that while the Cen N’-terminus is sufficient for protein enrichment at centrosomes, multiple domains cooperate to concentrateCenmRNA at this location. We further identify an N’-terminal motif within Cen that is conserved among dynein cargo adaptor proteins and test its contribution to RNA localization. Our results support a model whereby Cen protein enables the accumulation of its own mRNA to centrosomes through a mechanism requiring active translation, microtubules, and the dynein motor complex. Taken together, our data uncover the basis of translation-dependent localization of a centrosomal RNA required for mitotic integrity.SummaryEnrichment ofCentrocortin(Cen) mRNA at centrosomes is required for mitotic fidelity. This study describes a mechanism underlying co-translationalCenmRNA targeting involving microtubules, the dynein motor, and a highly conserved dynein binding motif within theCencoding sequence.
New limit on dark photon kinetic mixing in the
0.2–1.2  μeV
mass range from the Dark E-field Radio experiment
Authors: Levine Joseph , Godfrey Benjamin , Tyson J. Anthony , Tripathi S. Mani , Polin Daniel , Aminaei Amin , Kolner Brian H. , Stucky Paul 
Published: August 2024

We report new limits on the kinetic mixing strength of the dark photon spanning the mass range 0.21−1.24  μeV corresponding to a frequency span of 50–300 MHz. The Dark E-field Radio experiment is a wideband search for dark photon dark matter. In this paper we detail changes in calibration and upgrades since our proof-of-concept pilot run. Our detector employs a wide-bandwidth E-field antenna moved to multiple positions in a shielded room, a low noise amplifier, wideband analog-to-digital converter, followed by a 224-point fast Fourier transform. An optimal filter searches for signals with Q≈106. In nine days of integration, this system is capable of detecting dark photon signals corresponding to a kinetic mixing strength ε several orders of magnitude lower than previous limits. We find a 95% exclusion limit on ε over this mass range between 6×10−15 and 6×10−13, tracking the complex resonant mode structure in the shielded room.

Published by the American Physical Society
2024
Unveiling the marketer's lens: exploring experiences and perspectives on AI integration in marketing strategies
Authors: Elhajjar Samer 
Published: August 2024

PurposeThis research paper examines the perspectives of marketing professionals on the impact of AI on marketing strategies.Design/methodology/approachThrough interviews with 34 marketers in Singapore, the study uncovers the benefits, challenges, and potential risks associated with AI implementation.FindingsThe findings reveal improved efficiency, enhanced customer insights, and personalized marketing experiences as benefits of AI. Challenges identified include skill gaps, ethical considerations, resource constraints, and resistance to change.Originality/valueThe research provides important implications for marketers and companies, guiding decision-making and promoting the responsible adoption of AI in marketing strategies.
Modulating variables impacting the intersection of health and environmental concerns in organic food purchasing decisions
Authors: Xu Ming , Xu Qiang , Wei Sheng , Gu Xufei , Liu Furong 
Published: August 2024

PurposeThe increasing focus of consumers on health and environmental sustainability continues to drive the demand for organic food. Despite the recognized importance of health and environmental concerns, the differential impact of these factors on organic food purchasing decisions is evident, indicating the presence of moderating variables. This investigation attempts to delineate these contingencies within the realms of socio-environmental and individual factors, paying particular attention to subjective norms, uncertainty, and egoistic values.Design/methodology/approachUsing the convenience sampling method, the primary data sample was collected by a professional market research consulting firm and included 1876 usable respondents from China. Hierarchical multiple regression analysis was utilized to verify the model and test the relationships between the constructs.FindingsThe results indicated that the path from environmental concern to organic food purchase intention was significantly influenced by subjective norms and uncertainty, both of which enhance this relationship. In contrast, egoistic values appeared to dampen this effect. Uncertainty also emerged as a key factor in the link between health concerns and organic food purchase intention, albeit with an opposite impact, weakening the relationship.Practical implicationsThis study provides useful insights for academics and marketers to understand the complex phenomenon of organic consumer behavior. This result indicates that marketers can target reference groups to develop organic food marketing strategies.Originality/valueFew studies have proposed and validated a model with these moderating factors collectively to study the purchase intention of organic food consumers in China.
How immersive technologies impact behavioral responses in destination marketing: the role of physiological arousal, presence, and age
Authors: Di Dalmazi Michele , Mandolfo Marco , Guixeres Jaime , Alcañiz Raya Mariano , Lamberti Lucio 
Published: August 2024

Purpose
This paper aims to investigate the effectiveness of immersive virtual reality (VR) media and the influence of user’s age in the context of destination marketing by exploring their impact on cognition (presence), affection (arousal), and behavioral (intention to visit and intention to recommend the destination) outcomes.

Design/methodology/approach
A laboratory experiment was conducted to compare the impact of using immersive VR (vs. 2D desktop) to experience a 360-degree virtual tour of Valencia on consumers’ behavior. The sample included 187 participants. Both self-reported and physiological measures were collected during the experimentation.

Findings
Results showed that participants in the immersive condition experienced a stronger sense of presence and higher physiological arousal than those exposed to nonimmersive content. Presence significantly mediated both the intention to visit and the intention to recommend the promoted venue. Physiological arousal mediated the relationship between media typology and the intention to recommend the destination. Upon introducing age as a moderating variable, the effect of physiological arousal on behavioral outcomes proves to be significant.

Practical implications
The study presents destination marketing organizations with a compelling use case for immersive technologies. It also offers design principles, potential applications and targeting strategies for VR marketing in hospitality management.

Originality/value
To the best of the authors’ knowledge, this study is the first to investigate the combined effect of physiological arousal and presence on behavioral intentions in VR destination marketing, while also examining the impact of age as an individual characteristic.