bluuebunny/crossref_metadata_2025_split huggingface dataset:
Comprehensive benchmarking of methods for mutation calling in circulating tumor DNA
Authors: Carrié Hanaé , Sim Ngak Leng , Wong Pui Mun , Gan Anna , Lau Yi Ting , Poon Polly , Thangaraju Saranya , Tan Iain , Yap Yoon Sim , Krishnamachari Kiran , Wong Limsoon , Skanderup Anders 
Published: February 2025

AbstractDetection of somatic mutations in cell-free DNA (cfDNA) is challenging due to low variant allele frequencies and pronounced DNA degradation. Here, we present a novel approach and resource for benchmarking of somatic variant calling algorithms in cfDNA samples from cancer patients. Using longitudinally collected cfDNA samples from colorectal and breast cancer patients, we identify patient-matched samples with high and ultra-low circulating tumor DNA (ctDNA) levels. These sample pairs, preserving patient-specific germline and somatic haematopoiesis variant backgrounds, were used to generate dilution series capturing characteristics of bona-fide cfDNA samples. To benchmark the accuracy and limit of detection of 9 somatic variant calling algorithms, we used deep Whole Genome Sequencing (WGS, 150x) and ultra-deep Whole Exome Sequencing (WES, 2,000x) to construct a reference set of ∼37,000 Single Nucleotide Variants and ∼58,000 Insertions/Deletions. We tested methods under variable ctDNA levels and depth of sequencing, generating guidelines for method choice depending on use case. Using a machine learning approach, we further evaluated the potential of fine-tuning individual variant callers, revealing features that may improve accuracy in cfDNA samples. Overall, we present a new resource for benchmarking of somatic variant calling methods in cfDNA, providing insights on method choice to realize the potential of liquid biopsies in precision oncology.
TinkerHap - A Novel Read-Based Phasing Algorithm with Integrated Multi-Method Support for Enhanced Accuracy
Authors: Hartmann Uri , Shaham Eran , Nathan Dafna , Blech Ilana , Zeevi Danny 
Published: February 2025

AbstractPhasing, the assignment of alleles to their respective parental chromosomes, is fundamental to studying genetic variation and identifying disease-causing variants. Traditional approaches, including statistical, pedigree-based, and read-based phasing, face challenges such as limited accuracy for rare variants, reliance on external reference panels, and constraints in regions with sparse genetic variation.To address these limitations, we developed TinkerHap, a novel and unique phasing algorithm that integrates a read-based phaser, based on a pairwise distance-based unsupervised classification, with external phased data, such as statistical or pedigree phasing. We evaluated TinkerHap’s performance against other phasing algorithms using 1,040 parent-offspring trios from the UK Biobank (Illumina short-reads) and GIAB Ashkenazi trio (PacBio long-reads). TinkerHap’s read-based phaser alone achieved higher phasing accuracies than all other algorithms with 95.1% for short-reads (second best: 94.8%) and 97.5% for long-reads (second best: 95.5%). Its hybrid approach further enhanced short-read performance to 96.3% accuracy and was able to phase 99.5% of all heterozygous sites. TinkerHap also extended haplotype block sizes to a median of 79,449 base-pairs for long-reads (second best: 68,303 bp) and demonstrated higher accuracy for both SNPs and indels. This combination of a robust read-based algorithm and hybrid strategy makes TinkerHap a uniquely powerful tool for genomic analyses.
Sheathless elasto-inertial focusing of sub-25 nm particles in straight microchannels
Authors: Tanriverdi Selim , Cruz Javier , Habibi Shahriar , Sych Taras , Costa Martim , Mårtensson Gustaf , Görgens André , EL Andaloussi Samir , Brandt Luca , Tammisola Outi , Sezgin Erdinc , Russom Aman 
Published: February 2025

ABSTRACTNanoscale biological particles, such as lipoproteins (10–80 nm) or extracellular vesicles (30–200 nm), play pivotal roles in health and disease, including conditions like cardiovascular disorders and cancer. Their effective analysis is crucial for applications in diagnostics, quality control, and nanomedicine development. While elasto-inertial focusing offers a powerful method to manipulate particles without external fields, achieving consistent focusing of nanoparticles (<500 nm) has remained a challenge. In this study, we experimentally demonstrate elasto-inertial focusing of nanoparticles as small as 25 nm using straight high-aspect-ratio microchannels in a sheathless flow. Systematic investigations reveal the influence of channel width, particle size, viscoelastic concentration, and flow rate on focusing behavior. Additionally, through numerical simulations and experimental validation, we provide insights into particle migration dynamics and viscoelastic forces governing nanoparticle focusing. Finally, we successfully focus biological particles, including liposomes (90–140 nm), extracellular vesicles (100 nm), and lipoproteins (10–25 nm), under optimized conditions, showcasing potential applications in medical diagnostics and targeted drug delivery. These findings mark a significant advancement toward size-based high-resolution particle separation, with implications for biomedicine and environmental sciences.
Characterization of bronchovascular-bundle mesenchymal stromal cells regulating antibody-secreting cell niche in rejecting lung allografts
Authors: Patrick McLinden A. , Ibuki Yuta , Tadokoro Kazuki , Walker Natalie M. , Lu Lu , Ke Fang , Vittal Ragini , Farver Carol F. , Welch Joshua D. , Lama Vibha N. 
Published: February 2025

ABSTRACTA transplanted lung offers a permissive milieu for local adaptive immune cell responses. Here, we characterize a transcriptionally and anatomically distinct adult lung-resident mesenchymal stromal population (MSC) that supports a pro-survival niche for antibody-secreting cells in rejecting lung allografts through a novel IL-6 trans-signaling/CXCL12 axis. By using a mouse orthotopic lung transplant model and Blimp1YFP recipients, we identify spatial localization of antibody-secreting cells (ASCs) and terminally differentiated plasma cells (PCs) along the bronchovascular bundles (BVBs). A previously described Foxf1+/Gli1+/Itga8-subset of collagen-expressing MSCs, which forms a 3-dimensional network along the bronchovascular bundles (BVB-MSCs), was found to be the major source of the PC survival factors CXCL12 and IL6. Cxcl12iCre/ERT2R26RtdTomato mice utilized as donors validated the expansion of this population in a rejecting graft and their intimate association with ASCs. CXCL12 expression was increased in allografts and Foxf1+ MSCs isolated from human CLAD patients. IL6 trans signaling/STAT3 signaling axis was shown to upregulate CXCL12 secretion in human MSCs, and Olamkicept-mediated neutralization of IL6 trans-signaling in murine RAS attenuates CXCL12 expression, intra-graft ASC population, and fibrogenesis. Our findings represent the first delineation of specialized CXCL12-expressing stromal cells in adult lungs and demonstrate their contribution to sustaining intragraft ASC niches and allograft fibrogenesis.
Understanding monocyte-driven neuroinflammation in Alzheimer’s disease using human brain organoid microphysiological systems
Authors: Tian Chunhui , Ao Zheng , Cerneckis Jonas , Cai Hongwei , Chen Lei , Niu Henyao , Takayama Kazuo , Kim Jungsu , Shi Yanhong , Gu Mingxia , Kanekiyo Takahisa , Guo Feng 
Published: February 2025

AbstractIncreasing evidence suggests that Alzheimer’s disease (AD) pathogenesis strongly correlates with neuroinflammation. Peripheral monocytes are crucial components of the human immune system that may play a role in neuroinflammation, but their contribution to AD pathogenesis is largely understudied partially due to the lack of appropriate human models. Here, we present human cortical organoid microphysiological systems (hCO-MPSs) for modeling dynamic AD neuroinflammation mediated by monocytes. By incorporating 3D printed devices into an existing cortical organoid protocol, 96 hCO-MPSs can be established with significantly reduced necrosis and hypoxia as well as enhanced viability within a commonly used 96 well plate, and each hCO-MPS consists of a doughnut-shaped hCO and a 3D printed device per well. Using this approach, monocytes from AD patients exhibit higher infiltration, decreased amyloid-beta (Aβ) clearance, and stronger inflammatory responses compared to monocytes from age-matched control donors. Moreover, pro-inflammatory effects such as elevated astrocyte activation and neuronal apoptosis were observed to be induced by AD monocytes. Furthermore, the significant increase in the expression of IL1B and CCL3, both at the transcriptional and protein levels, indicated the pivotal role of these cytokine and chemokine in monocyte-mediated AD neuroinflammation. Our findings provide insight for understanding monocytes’ role in AD pathogenesis, and the user-friendly MPS models we present are compatible with existing laboratory settings, highlighting their potential for modeling neuroinflammation and developing new therapeutics for various neuroinflammatory diseases.
Genome restructuring and lineage diversification ofCryptococcus neoformansduring chronic infection of human hosts
Authors: Montoya Marhiah C. , Wilhoit Kayla , Murray Debra , Perfect John R. , Magwene Paul M. 
Published: February 2025

AbstractClassified as a critical public health threat by the World Health Organization,Cryptococcus neo-formansinfections with significant morbidity and mortality. Reports of cryptococcosis persistence, relapse, and reinfection date back to the 1950s, yet the factors driving chronic infections remain poorly understood. A major challenge is the scarcity of serial patient specimens and detailed medical records to study the simultaneous evolution of the pathogen and host health status. This study provides the first genomic and phenotypic analysis of in-host evolution ofC. neoformansduring chronic infections lasting over a year in six immunocompromised patients. We find fungal genome evolution during persistent infection is characterized by large-scale genome restructuring and increasing genomic heterogeneity. Phenotypic changes show diversification in virulence traits and antifungal susceptibility. Genotypically and phenotypically distinct sub-lineages arise and co-persist within the same tissues, consistent with a model of diversifying selection and niche partitioning in the complex environment of human hosts.
Distinct Cytokine and Cytokine Receptor Expression Patterns Characterize Different Forms of Myositis
Authors: Kirou Raphael A. , Pinal-Fernandez Iago , Casal-Dominguez Maria , Pak Katherine , Preusse Corinna , Dari Dilbe , Del Orso Stefania , Naz Faiza , Islam Shamima , Gutierrez-Cruz Gustavo , Naddaf Elie , Liewluck Teerin , Stenzel Werner , Selva-O’Callaghan Albert , Milisenda Jose C. , Mammen Andrew L. 
Published: February 2025

ABSTRACTObjectiveMyositis is a heterogeneous family of inflammatory myopathies. We sought to define the differential expression of cytokines, cytokine receptors, and immune checkpoint genes in muscle biopsies from patients with different forms of myositis in order to characterize patterns of inflammation in each.MethodsBulk RNA sequencing was performed on muscle biopsy samples from 669 patients, including 105 with dermatomyositis, 80 with immune-mediated necrotizing myopathy (IMNM), 65 with anti-synthetase syndrome, 53 with inclusion body myositis (IBM), 19 with anti-PM/Scl myositis, 310 with other inflammatory or genetic myopathies, and 37 controls with normal tissue (NT). Myositis clinical groups and autoantibody subgroups were analyzed separately. Expression data was analyzed for 338 genes encoding cytokines, cytokine receptors, and immune checkpoints. Myositis group-specific genes were identified from this list by finding genes that were specifically differentially expressed in one group compared to all samples and compared to NT (α<0.001).ResultsIBM patients had the most differentially overexpressed genes (71) among all clinical groups, including 37 that were IBM-specific. Among the top genes were several involved in type 1 inflammation, includingCCL5,CXCR3,CCR5,CXCL9, andIFNG. Anti-Jo1 and anti-PM/Scl patients exhibited differential overexpression of a similar set of genes, while dermatomyositis patients exhibited differential overexpression of a different set of genes involved in type 1 inflammation. IMNM patients had the least number of differentially overexpressed genes with no predominant inflammatory pattern.ConclusionEach myositis clinical group and autoantibody subgroup had differentially overexpressed inflammatory mediators, including a strong type 1 inflammatory gene signature in IBM.Key MessagesInclusion Body Myositis (IBM) muscle biopsies exhibit differential overexpression of a set of genes involved in type 1 inflammation.TheCCL5-CCR5andXCL1-XCL2-XCR1axes are specifically differentially overexpressed in IBM muscle and may contribute to TC1-mediated inflammation.Dermatomyositis, anti-Jo1 myositis, and anti-PM/Scl myositis muscle biopsies also exhibit overexpression of type 1 inflammatory genes, but to a lesser extent than IBM.
Exploring how an e-cigarette intervention influenced tobacco smoking behaviour in people accessing homelessness services: findings from the SCeTCH trial process evaluation
Authors: Ford Allison , McMillan Lauren , Cox Sharon , Soar Kirstie , Pesola Francesca , Notley Caitlin , Brown Rachel , Ward Emma , Gardner Bethany , Varley Anna , Mair Charlotte , Lennon Jessica , Brierley Janine , Edwards Amy , Micthell Danielle , Robson Debbie , Hajek Peter , Tyler Allan , Parrott Steve , Li Jinshuo , Bauld Linda , Dawkins Lynne 
Published: February 2025

ABSTRACTBackgroundSmoking prevalence among people experiencing homelessness is high. This study explored the factors which influenced potential smoking abstinence among participants receiving an e-cigarette (EC) intervention within the Smoking Cessation Trial in Centres for Homelessness (SCeTCH) across Great Britian.MethodsUsing the Capability Opportunity Motivation – Behaviour (COM-B) model, hypothesised and emerging mediators were explored quantitatively via measures in baseline and follow-up questionnaires (n=239) and qualitatively via interviews with homelessness centre staff (n=16) and participants (n=31) who received an EC starter pack and 4-week e-liquid supply. We purposively sampled 8 centres for interviews, representing varied regions and participant vaping/smoking and sociodemographic status. Quantitative measures were analysed descriptively. Qualitative data were analysed thematically. Data from the two approaches were mapped onto the COM-B for combined analysis and reporting.ResultsAfter receiving the intervention, participants demonstrated high capability to use EC and appreciation of EC for harm reduction. Some participants reported dissatisfaction with vaping. Opportunity for behaviour change was strengthened by perceived acceptability to vape and social support beyond the centre but hindered by a smoking culture and perceived lack of staff support. Motivation was enhanced by EC efficacy belief, pride from cutting down, and financial benefits of vaping, but negatively impacted by challenging personal circumstances.ConclusionFor people accessing homelessness support centres, smoking abstinence remains challenging. More intensive support and a variety of approaches to support smoking cessation, particularly those which address the psychosocial factors which hinder smoking abstinence, may be required. Future research should focus on how this can be achieved.
Long-term memory formation impacts dietary energy intake but not metabolic rate in honeybees
Authors: Watrobska Cecylia M. , Codd Jonathan , Portugal Steven J. , Leadbeater Ellouise 
Published: February 2025

AbstractThe brain is energetically expensive. Energy availability may, therefore, determine whether costly cognitive processes such as long-term memory can be expressed. However, there is a limited understanding of the metabolic costs associated with long-term memory formation. Here, we explored the potential induced costs of long-term memory formation using honeybees (Apis mellifera) as a model species. We monitored the sucrose intake of bees over the 20-hour period following a classical spaced olfactory conditioning protocol that induced long-term memory formation, relative to a control group that experienced the same reward schedule but no odour pairing. Bees in the experimental treatment drank significantly more sucrose than controls. We then tested whether the increased energy demands of long-term memory formation showed parallel increases in metabolic rate, by measuring carbon dioxide production in groups of bees at four timepoints following conditioning (1-hour, 4-hours, 24-hours and 72-hours). We found no change in metabolic rate between learning and control groups across all time points. Our results suggest that the cost of long-term memory formation does not translate to increases in metabolic rate, despite an increase in dietary energy intake. Constraints on the expression of cognitive traits may, therefore, be unlikely when energy is unrestricted and can be compensated.
Direct mechanical communication of cellular to nuclear shape in oocytes
Authors: Vos Bart E. , Vadapalli Yamini , Muenker Till , Jentoft Ida Marie Astad , Todisco Elena , Eskandari Mohammad Amin , Schuh Melina , Lenart Peter , Betz Timo 
Published: February 2025

AbstractThe mechanical properties of the cytoplasm and nucleoplasm are crucial for the correct and robust functioning of a cell and play a key role in understanding how mechanical signals are transferred to the nucleus. Here, we demonstrate remarkable shape mimicry between the cellular and nuclear shape of oocytes, following the externally applied deformation without direct contact between the cell cortex and the nucleus. This effect arises from a surprisingly soft and fluid-like nucleoplasm that is barely resisting any external strain, while the viscoelastic cytoplasm drives shape transmission. Comparative studies in jellyfish, starfish, and mouse oocytes reveal that lower cytoplasmic elasticity in jellyfish leads to reduced nuclear shape mimicry, highlighting the role of cytoplasmic mechanics in nuclear deformation.Significance StatementMechanosensing of the nucleus is, in addition to chemical signalling, an important factor in gene expression. Although nuclei are often thought to be rigid inclusions in the cytoplasm of a cell, we show that in oocytes nuclei are much more deformable. Using a combination of intranuclear, intracellular and extracellular measurements, we attribute our findings to a fine balance between the soft nucleoplasm surrounded by an elastic shell and the viscoelastic properties of the cytoplasm.
RNA Knowledge-Graph analysis through homogeneous embedding methods
Authors: Torgano Francesco , Gomez Mauricio Soto , Zignani Matteo , Gliozzo Jessica , Cavalleri Emanuele , Mesiti Marco , Casiraghi Elena , Valentini Giorgio 
Published: February 2025

AbstractMotivationWe recently introduced RNA-KG, an ontology-based knowledge graph that integrates biological data on RNAs from over 60 public databases. RNA-KG captures functional relationships and interactions between RNA molecules and other biomolecules, chemicals, and biomedical concepts such as diseases and phenotypes, all represented within graph-structured bio-ontologies. We present the first comprehensive computational analysis of RNA-KG, evaluating the potential of graph representation learning and machine learning models to predict node types and edges within the graph.ResultsWe performed node classification experiments to predict up to 81 distinct node types, and performed both generic and specific edge prediction tasks. Generic edge prediction focused on identifying the presence of an edge irrespective of its type, while specific edge prediction targeted specific interactions between ncRNAs, e.g. miRNA-miRNA or siRNA-mRNA, or relationships between ncRNA and biomedical concepts, e.g. miRNA-disease or lncRNA-Gene Ontology term relationships. Using embedding methods for homogeneous graphs, such as LINE and node2vec, in combination with machine learning models like decision trees and random forests, we achieved balanced accuracy exceeding 90% for the 20 most common node types and over 80% for most specific edge prediction tasks. These results show that simple embedding methods for homogeneous graphs can successfully predict nodes and edges of the RNA-KG, paving the way to discover novel ncRNA interactions and laying the foundation for further exploration and utilization of this rich information source to enhance prediction accuracy and support further research into the “RNA world”.Code AvailabilityPython code to reproduce the experiments is available athttps://github.com/AnacletoLAB/RNA-KG_homogeneous_emb_analysis
diffONT: predicting methylation-specific PCR biomarkers based on nanopore sequencing data for clinical application
Authors: Meyer Daria , Barth Emanuel , Wiehle Laura , Marz Manja 
Published: February 2025

AbstractDNA methylation is known to act as biomarker applicable for clinical diagnostics, especially in cancer detection. Methylation-specific PCR (MSP) is a widely used approach to screen patient samples fast and efficiently for differential methylation. During MSP, methylated regions are selectively amplified with specific primers. With nanopore sequencing, knowledge about DNA methylation is generated during direct DNA sequencing, without any need for pretreatment of the DNA. Multiple methods, mainly developed for whole-genome bisulfite sequencing (WGBS) data, exist to predict differentially methylated regions (DMRs) in the genome. However, the predicted DMRs are often very large, and not sufficiently discriminating to generate meaningful results in MSP creating a gap between theoretical cancer marker research and practical application, as no tool currently provides methylation difference predictions tailored for PCR-based diagnostics. Here we presentdiffONT, which predicts differentially methylated primer regions, directly suitable for MSP primer design and thus allowing a direct translation into practical approaches.diffONTtakes into account (i) the specific length of primer and amplicon regions, (ii) the fact that one condition should be unmethylated, and (iii) a minimal required amount of differentially methylated cytosines within the primer regions. Based on two nanopore sequencing data sets we compared the results ofdiffONTtometilene,DSSandpycoMeth. We show that the regions predicted bydiffONTare more specific towards hypermethylated regions and more usable for MSP.diffONTaccelerates the design of methylation-specific diagnostic assays, bridging the gap between theoretical research and clinical application.