bluuebunny/crossref_metadata_2025_split huggingface dataset:
The landscape of coagulation cascade in pulmonary arterial hypertension
Authors: Xiao Genfa , Lian Guili , Liu Xiaoli , Xie Liangdi 
Published: March 2024

AbstractBackgroundBoth the thrombotic and bleeding events were frequently complicated in pulmonary arterial hypertension (PAH), making recommendations regarding anticoagulation difficult.MethodsThe histopathological examination was performed on the lungs of two PAH models and global coagulation cascade alteration in lung tissue and peripheral venous blood was assessed by RNA sequencing and immunoassay, respectively. The clinical data and plasma samples were collected from PAH patients and controls and plasma coagulation cascade in subject was quantified by both immunoassay and proteomic approach.ResultsRNA sequencing analysis of lung tissues in two PAH models showed the reduced anticoagulants and intrinsic clotting factors and increased tissue factor (TF) expression. The immunoassay assessment of coagulation cascade in PAH models revealed increased TF expression, reduced intrinsic and common clotting factors and decreased anticoagulants antithrombin (AT)-Ⅲ in the peripheral circulation. Additionally, clinical evaluation of hemostatic parameters in PAH patients demonstrated hemostatic deficiency and lower AT-Ⅲ activity. Consistently, proteomic and immunoassay analysis of coagulation cascade in PAH patients revealed the increased extrinsic clotting factors, impairment of intrinsic and common pathways and impairment of AT-Ⅲ anticoagulant pathway.ConclusionsThe activation of extrinsic pathway and impairment of heparin/AT-Ⅲ anticoagulant system are conserved mechanisms for thrombosis across rat and human PAH, restoring its function with heparin supplementation may be a better option for future anticoagulant therapy.Clinical PerspectiveWhat Is New?The activation of extrinsic pathway and impairment of heparin/AT-Ⅲ system were responsible for thrombosis in pulmonary arterial hypertension.Impairment of intrinsic and common pathways, due to reduced plasma levels of clotting factors F10, F11, F2 and vWF, contributed to hemorrhagic complications, such as hemoptysis in PAH patients.What Are the Clinical Implications?Increased risk of bleeding for anticoagulation with warfarin and novel oral anticoagulants may be attributed to further impairment of intrinsic and common pathways in PAH.Restoring function of heparin/ AT-Ⅲ anticoagulant system with heparin supplementation may be a better option for future anticoagulant therapy.
Mathematical Modelling of Oxygenation Dynamics using High-Resolution Perfusion Data – Part 1: Statistical Framework
Authors: Sharabiani Mansour T. A. , Mahani Alireza S. , Issitt Richard W. , Srinivasan Yadav , Bottle Alex , Stoica Serban 
Published: March 2024

AbstractBackgroundBalancing oxygen supply and demand during cardiopulmonary bypass (CPB) is crucial to minimise adverse outcomes. This is managed by adjusting oxygen delivery components – cardiac index (CI), haemoglobin concentration (Hb), arterial oxygen saturation (SaO2) – and metabolic demand through temperature (Temp) changes. The oxygen extraction ratio (OER) responds to these adjustments, affecting oxygen consumption, but this response is not well understood. We aimed to develop a mathematical model to capture OER dynamics during CPB and quantify oxygen demand’s dependence on temperature.MethodsWe developed GARIX, a time-series model predicting minute-by-minute OER changes during CPB, incorporating exogenous variables (CI, Hb, SaO2, Temp) and an equilibrium term representing the difference between oxygen consumption and temperature-dependent oxygen demand, modelled linearly per the van’t Hoff specification (constant Q10). The model was trained on data from 343 CPB operations (20,000 minutes) in 334 paediatric patients at a UK centre (2019–2021). We used variable importance analysis and simulations to study the model’s properties.ResultsThe model shows OER adapts to align oxygen consumption with demand. The adaptive response has a rapid phase (<10 minutes) and a slower phase extending up to several hours. Equilibrium analysis yields Q10= 2.25, indicating oxygen demand doubles with every 8.5°C increase in temperature during CPB.ConclusionsOur model provides a physiologically plausible framework for explaining OER changes during CPB, capturing dynamic adjustments and steady-state oxygen consumption. These findings highlight the value of mathematical modelling in estimating key oxygenation parameters like Q10, given limitations on clinical experimentation.
Following The Evolutionary Paths Of Highly Specific Homophilic Adhesion Proteins
Authors: Wiseglass Gil , Rubinstein Rotem 
Published: March 2024

AbstractMany adhesion proteins, evolutionarily related through gene duplication, exhibit distinct and precise interaction preferences and affinities crucial for cell patterning. Yet, the evolutionary path by which these proteins, which are highly similar in structure and sequence, acquire new specificity and prevent cross-interactions within their family members remains unknown. To bridge this gap, this study focuses on Drosophila Down syndrome cell adhesion molecule-1 (Dscam1) proteins, which are cell adhesion proteins that have undergone extensive gene duplication. Dscam1 evolved under strong selective pressure to achieve strict homophilic recognition, essential for neuronal self-avoidance and patterning. Through a combination of phylogenetic analysis, ancestral sequence reconstruction, and cell aggregation assays, we studied the evolutionary trajectory of Dscam1 exon 4 across various insect lineages. We demonstrated that recent Dscam1 duplications in the mosquito lineage bind with strict homophilic specificities without any cross-interactions. We found that ancestral and intermediate Dscam1 isoforms were able to maintain their homophilic bindings capabilities, with some intermediate isoforms also engaging in promiscuous interactions with other paralogs. Our results highlight the robust selective pressure for homophilic specificity integral to Dscam1 function within the process of neuronal self-avoidance. Importantly, our study suggests that the path to achieving such selective specificity does not introduce disruptive mutations that prevent self-binding but includes an evolutionary intermediate that demonstrates promiscuous heterophilic interactions. Overall, these results offer insights into evolutionary strategies that underlie adhesion protein interaction specificity.
Exploring structural diversity across the protein universe with The Encyclopedia of Domains
Authors: Lau A. M. , Bordin N. , Kandathil S. M. , Sillitoe I. , Waman V. P. , Wells J. , Orengo C. A. , Jones D. T. 
Published: March 2024

AbstractThe AlphaFold Protein Structure Database (AFDB) contains full-length predictions of the three-dimensional structures of almost every protein in UniProt. Because protein function is closely linked to structure, the AFDB is poised to revolutionise our understanding of biology, evolution and more. Protein structures are composed of domains, independently folding units that can be found in multiple structural contexts and functional roles. The AFDB’s potential remains untapped due to the difficulty of characterising 200 million structures. Here we present The Encyclopedia of Domains or TED, which combines state-of-the-art deep learning-based domain parsing and structure comparison algorithms to segment and classify domains across the whole AFDB. TED describes over 370 million domains, over 100 million more than detectable by sequence-based methods. Nearly 80% of TED domains share similarities to known superfamilies in CATH, greatly expanding the set of known protein structural domains. We uncover over 10,000 previously unseen structural interactions between superfamilies, expand domain coverage to over 1 million taxa, and unveil thousands of architectures and folds across the unexplored continuum of protein fold space. We expect TED to be a valuable resource that provides a functional interface to the AFDB, empowering it to be useful for a multitude of downstream analyses.
The Genomic portrait of the Picene culture: new insights into the Italic Iron Age and the legacy of the Roman expansion in Central Italy
Authors: Ravasini Francesco , Niinemäe Helja , Solnik Anu , de Gennaro Luciana , Montinaro Francesco , Hui Ruoyun , Delpino Chiara , Finocchi Stefano , Giroldini Pierluigi , Mei Oscar , Cilli Elisabetta , Hajiesmaeil Mogge , Pistacchia Letizia , Risi Flavia , Giacometti Chiara , Scheib Christiana Lyn , Tambets Kristiina , Metspalu Mait , Cruciani Fulvio , D’Atanasio Eugenia , Trombetta Beniamino 
Published: March 2024

AbstractBackgroundThe Italic Iron Age was characterized by the presence of various ethnic groups partially examined from a genomic perspective. To explore the evolution of Iron Age Italic populations and the genetic impact of Romanization, we focused on the Picenes, one of the most fascinating pre-Roman civilizations, who flourished on the Middle Adriatic side of Central Italy between the 9thand the 3rdcentury BCE, until the Roman colonization.ResultsWe analyzed more than 50 samples, spanning more than 1,000 years of history from the Iron Age to Late Antiquity. Despite cultural diversity, our analysis reveals no major differences between the Picenes and other coeval populations, suggesting a shared genetic history of the Central Italian Iron Age ethnic groups. Nevertheless, a slight genetic differentiation between populations along the Adriatic and Tyrrhenian coasts can be observed, possibly due to genetic contacts between populations residing on the Italian and Balkan shores of the Adriatic Sea. Additionally, we found several individuals with ancestries deviating from their general population. Lastly, In the Late Antiquity period, the genetic landscape of the Middle Adriatic region drastically changed, indicating a relevant influx from the Near East.ConclusionsOur findings, consistently with archeological hypotheses, suggest genetic interactions across the Adriatic Sea during the Bronze/Iron Age and a high level of individual mobility typical of cosmopolitan societies. Finally, we highlighted the role of the Roman Empire in shaping genetic and phenotypic changes that greatly impacted the Italian peninsula.
Intricate interactions between antiviral immunity and transposable element control inDrosophila
Authors: Mayeux Camille A , Larue Anaïs , Oliveira Daniel S. , Varoqui Marion , Henri Hélène , Rebollo Rita , Kremer Natacha , Chambeyron Séverine , Fablet Marie 
Published: March 2024

AbstractTransposable elements (TEs) are parasite DNA sequences that are controlled by RNA interference pathways in many organisms. In insects, antiviral immunity is also achieved by the action of small RNAs. In the present study, we analyzed the impacts of an infection with Drosophila C Virus (DCV) and found that TEs are involved in a dual response: on the one hand TE control is released upon DCV infection, and on the other hand TE transcripts help the host reduce viral replication. This discovery highlights the intricate interactions in the arms race between host, genomic parasites, and viral pathogens.Significance statementTransposable elements (TEs) are widespread components of all genomes. They were long considered as mere DNA parasites but are now acknowledged as major sources of genetic diversity and phenotypic innovations. UsingDrosophilaC virus, here we show that TEs are at the center of defense and counter-attack between host and virus. On the one hand, TE control is released upon viral infection, and on the other hand, TE transcripts help the host reduce viral replication. To our knowledge, this is the first time such a complex host-pathogen interaction involving TEs is shown.
Machine learning methods applied to classify complex diseases using genomic data
Authors: Segura Magdalena Arnal , Bini Giorgio , Krithara Anastasia , Paliouras George , Tartaglia Gian Gaetano 
Published: March 2024

ABSTRACTComplex diseases pose challenges in disease prediction due to their multifactorial and polygenic nature. In this work, we explored the prediction of two complex diseases, multiple sclerosis (MS) and Alzheimer’s disease (AD), using machine learning (ML) methods and genomic data from UK Biobank. Different ML methods were applied, including logistic regressions (LR), gradient boosting decision trees (GB), extremely randomized trees (ET), random forest (RF), feedforward networks (FFN), and convolutional neural networks (CNN). The primary goal of this research was to investigate the variability of ML models in classifying complex diseases based on genomic risk. LR was the most robust method across folds and diseases, whereas deep learning methods (FFN and CNN) exhibited high variability. When comparing the performance of polygenic risk scores (PRS) with ML methods, PRS consistently performed at an average level. However, PRS still offers several practical advantages over ML methods. Despite implementing feature selection techniques to exclude non-informative and correlated predictors, the performance of ML models did not improve significantly, underscoring the ability of ML methods to achieve optimal performance even in the presence of correlated features due to linkage disequilibrium. Upon applying explainability tools to extract information about the genomic features contributing most to the classification task, the results confirmed the polygenicity of MS. The prevalence of HLA gene annotations among the top genomic features on chromosome 6 aligns with their significance in the context of MS. Overall, the highest-prioritized genomic variants were identified as expression or splicing quantitative trait loci (eQTL or sQTL) located in non-coding regions within or near genes associated with the immune response and MS. In summary, this research offers deeper insights into how ML models discern genomic patterns related to complex diseases.
Structural and genetic diversity in the secreted mucins,MUC5ACandMUC5B
Authors: Plender Elizabeth G. , Prodanov Timofey , Hsieh PingHsun , Nizamis Evangelos , Harvey William T. , Sulovari Arvis , Munson Katherine M. , Kaufman Eli J. , O’Neal Wanda K. , Valdmanis Paul N. , Marschall Tobias , Bloom Jesse D. , Eichler Evan E. 
Published: March 2024

ABSTRACTThe secreted mucins MUC5AC and MUC5B play critical defensive roles in airway pathogen entrapment and mucociliary clearance by encoding large glycoproteins with variable number tandem repeats (VNTRs). These polymorphic and degenerate protein coding VNTRs make the loci difficult to investigate with short reads. We characterize the structural diversity ofMUC5ACandMUC5Bby long-read sequencing and assembly of 206 human and 20 nonhuman primate (NHP) haplotypes. We find that humanMUC5Bis largely invariant (5761-5762aa); however, seven haplotypes have expanded VNTRs (6291-7019aa). In contrast, 30 allelic variants ofMUC5ACencode 16 distinct proteins (5249-6325aa) with cysteine-rich domain and VNTR copy number variation. We groupedMUC5ACalleles into three phylogenetic clades: H1 (46%, ∼5654aa), H2 (33%, ∼5742aa), and H3 (7%, ∼6325aa). The two most common humanMUC5ACvariants are smaller than NHP gene models, suggesting a reduction in protein length during recent human evolution. Linkage disequilibrium (LD) and Tajima’s D analyses reveal that East Asians carry exceptionally largeMUC5ACLD blocks with an excess of rare variation (p<0.05). To validate this result, we used Locityper for genotypingMUC5AChaplogroups in 2,600 unrelated samples from the 1000 Genomes Project. We observed signatures of positive selection in H1 and H2 among East Asians and a depletion of the likely ancestral haplogroup (H3). In Africans and Europeans, H3 alleles show an excess of common variation and deviate from Hardy-Weinberg equilibrium, consistent with heterozygote advantage and balancing selection. This study provides a generalizable strategy to characterize complex protein coding VNTRs for improved disease associations.
NONEXPRESSOR OF PATHOGENESIS-RELATED GENEScontrol Huanglongbing tolerance by regulating immune balance in citrus plants
Authors: Sarkar Poulami , El-Mohtar Choaa , Turner Donielle , Welker Stacy , Robertson Cecile J. , Orbovic Vladimir , Mou Zhonglin , Levy Amit 
Published: March 2024

AbstractHuanglongbing (HLB) is a devastating citrus disease caused by the phloem-resident bacterial pathogenCandidatusliberibacter asiaticus (CLas).CLas infection of susceptible varieties triggers unbalanced immune responses, leading to overaccumulation of callose and reactive oxygen species (ROS), which in turn causes phloem plugging and HLB symptom development. Interestingly, some citrus relatives exhibit little or no symptoms in the presence ofCLas, a phenomenon termed HLB tolerance. Moreover, overexpression of theArabidopsis thaliana NPR1(AtNPR1) gene in susceptible varieties has been shown to confer robust HLB tolerance. However, the mechanisms underlying HLB tolerance remain enigmatic. Here, we show that overexpression ofAtNPR1suppressesCLas- andPseudomonas syringaepv.maculicolaES4326 (Psm)-induced overaccumulation of callose and ROS in citrus andArabidopsis, respectively. Importantly, we found that knocking out of theArabidopsisnegative immune regulators,AtNPR3andAtNPR4, and silencing of theirCitrus sinensisorthologCsNPR3, similarly suppressPsm- andCLas-induced callose and ROS overaccumulation, respectively, and that silencing ofCsNPR3also enhances HLB tolerance. These results reveal a conserved role of theNPR1/NPR3/NPR4-mediated signaling pathway in regulating plant immune balances and provide mechanistic support for overexpression ofAtNPR1or silencing ofAtNPR3/AtNPR4orthologs in citrus as a long-term solution to the HLB disease.
Targeting PIKfyve-driven lipid homeostasis as a metabolic vulnerability in pancreatic cancer
Authors: Cheng Caleb , Hu Jing , Mannan Rahul , Bhattacharyya Rupam , Rossiter Nicholas J. , Magnuson Brian , Wisniewski Jasmine P. , Zheng Yang , Xiao Lanbo , Li Chungen , Awad Dominik , He Tongchen , Bao Yi , Zhang Yuping , Cao Xuhong , Wang Zhen , Mehra Rohit , Morlacchi Pietro , Sahai Vaibhav , Pasca di Magliano Marina , Shah Yatrik M. , Ding Ke , Qiao Yuanyuan , Lyssiotis Costas A. , Chinnaiyan Arul M. 
Published: March 2024

AbstractPancreatic ductal adenocarcinoma (PDAC) subsists in a nutrient-deregulated microenvironment, making it particularly susceptible to treatments that interfere with cancer metabolism12. For example, PDAC utilizes and is dependent on high levels of autophagy and other lysosomal processes3-5. Although targeting these pathways has shown potential in preclinical studies, progress has been hampered by the challenge of identifying and characterizing favorable targets for drug development6. Here, we characterize PIKfyve, a lipid kinase integral to lysosomal functioning7, as a novel and targetable vulnerability in PDAC. In human patient and murine PDAC samples, we discovered thatPIKFYVEis overexpressed in PDAC cells compared to adjacent normal cells. Employing a genetically engineered mouse model, we established the essential role of PIKfyve in PDAC progression. Further, through comprehensive metabolic analyses, we found that PIKfyve inhibition obligated PDAC to upregulatede novolipid synthesis, a relationship previously undescribed. PIKfyve inhibition triggered a distinct lipogenic gene expression and metabolic program, creating a dependency onde novolipid metabolism pathways, by upregulating genes such asFASNandACACA. In PDAC, the KRAS-MAPK signaling pathway is a primary driver ofde novolipid synthesis, specifically enhancingFASNandACACAlevels. Accordingly, the simultaneous targeting of PIKfyve and KRAS-MAPK resulted in the elimination of tumor burden in a syngeneic orthotopic model and tumor regression in a xenograft model of PDAC. Taken together, these studies suggest that disrupting lipid metabolism through PIKfyve inhibition induces synthetic lethality in conjunction with KRAS-MAPK-directed therapies for PDAC.
A Genome-wide Association Study Identifies Novel Genetic Variants Associated with Neck or Shoulder Pain in the UK Biobank (N = 441,757)
Authors: Tao Yiwen , Pan Qi , Cai Tengda , Lu Zen Haut , Haque Mainul , Dottorini Tania , Colvin Lesley A , Smith Blair H , Meng Weihua 
Published: March 2024

AbstractNeck and shoulder pain are prevalent musculoskeletal disorders that significantly impact the quality of life for a substantial portion of the global population. Studies have shown that women are more susceptible than men. This study aims to discover genetic variants associated with neck or shoulder pain through a genome-wide association study (GWAS), using data from 441,757 participants in the UK Biobank. The primary GWAS revealed five significant genetic loci (including two novel) associated with neck or shoulder pain, with the most significant single nucleotide polymorphism (SNP) being rs9889282 (p= 2.63 x 10-12) nearCA10on chromosome 17. Two novel significant associations were detected on chromosomes 18 and 14, with the top SNPs being rs4608411 (p= 8.20 x 10-9) nearTCF4and rs370565192 (p= 3.80 x 10-8) inDCAF5, respectively. The female-specific GWAS identified two significant loci including one nearCA10and one nearLINC02770on chromosome 1 with the top SNP being rs5779595 (p= 3.57 x 10-8). The male-specific GWAS identified one locus inSLC24A3on chromosome 20 with the top SNP being rs16980973 (p= 6.52 x 10-9). The tissue expression analysis revealed a significant association between brain tissues and neck or shoulder pain. In summary, this study has identified novel genetic variants for neck or shoulder pain. Sex stratified GWAS also suggested that gender played a role in the occurrence of the phenotype.
Cell type profile variation in menstrual effluent by sample collection method identified using methylation cytometry
Authors: Vlasac Irma M. , Stolrow Hannah G. , Thayer Zaneta M. , Christensen Brock C. , Rivera Luisa 
Published: March 2024

AbstractMenstrual effluent cell profiles have potential as noninvasive biomarkers of female reproductive and gynecological health and disease. We used DNA methylation-based cell type deconvolution (methylation cytometry) to identify cell type profiles in self-collected menstrual effluent. During the second day of their menstrual cycle healthy participants collected menstrual effluent using a vaginal swab, menstrual cup, and pad. Immune cell proportions were highest in menstrual cup samples, and epithelial cells were highest in swab samples. Our work demonstrates the feasibility and utility of menstrual effluent cell profiling in population-level research using remotely collected samples and DNA methylation.
Identifying therapeutic targets for rheumatoid arthritis by genomics-driven integrative approaches
Authors: Zhang Jie , Fang Xinyu , Wu Jingwei , Zhang Zixing , Mu Min , Ye Dongqing 
Published: March 2024

SummaryGenomics-driven drug discovery framework holds promise in developing novel therapeutic targets. Here, we leveraged large-scale genomic data including genome-wide association studies (GWAS), rare variant burden tests in exome sequencing studies (Exome), and protein quantitative trait loci (pQTL), to prioritize potential therapeutic targets and identify opportunities for drug repositioning in rheumatoid arthritis (RA). We found that prioritized genes covering two approved RA treatment targets (IL6R and CD86), and five targets tested in clinical trials for RA. Eighteen proteins were identified as having causalities with RA risk, three out of them showed strong support for colocalization. Bromodomain-containing protein 2 (BRD2) was nominated as one of the most promising candidates for clinical translation as its wide expression in joint synovial tissues and validation in observational analyses associating with RA incidence. Collectively, our systematic screening of candidate drug targets from different genetically informed approaches, and provided a comprehensive insight into therapeutic strategies for RA.