bluuebunny/crossref_metadata_2025_split huggingface dataset:
Small-cohort GWAS discovery with AI over massive functional genomics knowledge graph
Authors: Huang Kexin , Zeng Tony , Koc Soner , Pettet Alexandra , Zhou Jingtian , Jain Mika , Sun Dongbo , Ruiz Camilo , Ren Hongyu , Howe Laurence , Richardson Tom G. , Cortes Adrian , Aiello Katie , Branson Kim , Pfenning Andreas , Engreitz Jesse M. , Zhang Martin Jinye , Leskovec Jure 
Published: December 2024

AbstractGenome-wide association studies (GWASs) have identified tens of thousands of disease associated variants and provided critical insights into developing effective treatments. However, limited sample sizes have hindered the discovery of variants for uncommon and rare diseases. Here, we introduce KGWAS, a novel geometric deep learning method that leverages a massive functional knowledge graph across variants and genes to improve detection power in small-cohort GWASs significantly. KGWAS assesses the strength of a variant’s association to disease based on the aggregate GWAS evidence across molecular elements interacting with the variant within the knowledge graph. Comprehensive simulations and replication experiments showed that, for small sample sizes (N=1-10K), KGWAS identified up to 100% more statistically significant associations than state-of-the-art GWAS methods and achieved the same statistical power with up to 2.67× fewer samples. We applied KGWAS to 554 uncommon UK Biobank diseases (Ncase<5K) and identified 183 more associations (46.9% improvement) than the original GWAS, where the gain further increases to 79.8% for 141 rare diseases (Ncase<300). The KGWAS-only discoveries are supported by abundant functional evidence, such as rs2155219 (on 11q13) associated with ulcerative colitis potentially via regulatingLRRC32expression in CD4+ regulatory T cells, and rs7312765 (on 12q12) associated with the rare disease myasthenia gravis potentially via regulatingPPHLN1expression in neuron-related cell types. Furthermore, KGWAS consistently improves downstream analyses such as identifying disease-specific network links for interpreting GWAS variants, identifying disease-associated genes, and identifying disease-relevant cell populations. Overall, KGWAS is a flexible and powerful AI model that integrates growing functional genomics data to discover novel variants, genes, cells, and networks, especially valuable for small cohort diseases.
Potential health and cost impacts of a point-of-care test for neonatal sepsis and possible serious bacterial infections in infants: a modeling analysis in two settings
Authors: Chevalier Joshua M , Hansen Megan A , Grantz Kyra H , Gleeson Birgitta , Blumel Benjamin , Chuchu Veronicah , Khan Shaukat , Sigwebela Ntombi , Chimhini Gwendoline , Fitzgerald Felicity , Ferreyra Cecilia , Nichols Brooke E 
Published: December 2024

AbstractIntroductionSepsis accounts for up to 50% of neonatal deaths in resource-limited countries. Accurate and timely diagnosis could improve clinical outcomes, reduce inappropriate antibiotic use, and provide healthcare cost savings. We aimed to identify the minimum technical specifications and cost required of a point-of-care test (POCT) for neonatal sepsis to be clinically useful in hospital and community levels in low-resource settings.MethodsWe modeled the diagnosis and treatment of two cohorts: hospitalized neonates and infants presenting to primary health care facilities with suspected sepsis. We compared health outcomes, including mortality, length of hospital stays, and acquisition of healthcare-associated infections (HAIs), under a POCT compared to empiric treatment and blood culture across varying test performance, prevalence of bacterial infection and discharge eligibility. A threshold health economic analysis was performed to determine the allowable POCT price to remain cost neutral to the healthcare system.ResultsA POCT could lead to a net reduction in neonatal deaths at both the hospital level (up to 19% of deaths averted compared to baseline) and community level (up to 76% deaths averted) through faster initiation of appropriate therapy and reducing unnecessary hospitalizations and HAIs. Healthcare costs could be reduced substantially with implementation of a POCT (17%–43% of baseline costs saved in hospital and 48%–81% saved in primary healthcare settings across the range of analyzed scenarios), suggesting a POCT costing up to $21 in hospitals and $3 in community settings could be cost neutral.ConclusionsA POCT for neonatal sepsis, even with imperfect accuracy, could substantially improve clinical outcomes by improving time to diagnosis, while also supporting antibiotic de-escalation and stewardship and lowering healthcare costs. However, high clinical sensitivity is required to avoid causing deaths through missed diagnoses due to false negative results and delayed antibiotic initiation.Key QuestionsWhat is already known on this topic?It is known that neonatal sepsis and possible serious bacterial infections in infants are a serious cause of mortality; however, diagnosis to provide proper treatment and care remains difficult.What does this study add?This study generates evidence on what the technical specifications and costs are required of a novel point-of-care test through mathematical modeling.How might this study affect research, practice, or policy?These results can be used as criteria to guide the development of a novel point-of-care test for neonatal sepsis and bacterial infection in infants.
Assessing the mental health literacy of young adults from rural and urban communities in Malawi
Authors: Chitalah Beatrice Cynthia , Nanda Ishani , Nyali Joel , Chirwa Gloria , Jumbe Sandra 
Published: December 2024

AbstractMental health literacy is the ability to recognise mental disorders, have knowledge of professional help available, effective self-help strategies, prevention strategies, and skills to support others. Mental health literacy is linked to better help-seeking behaviours and the management of mental illness. The prevalence of mental illness in Malawi is increasing. Assessing mental health literacy in communities crucially helps identify knowledge gaps, informing the development of evidence-based interventions. This study assessed the mental health literacy levels of young adults (16-to-30 years old) in rural and urban communities in Malawi. A cross-sectional national survey was administered to 682 people across 13 districts in Malawi using a self-reporting Mental Health Literacy questionnaire (MHLq) that assessed knowledge of mental health problems, erroneous beliefs/stereotypes, first-aid skills, help-seeking behaviour, and self-help strategies. Most respondents were either unemployed (36%) or enrolled in school (43%). 73% had completed primary or secondary education, 48% knew someone with a mental illness but only 14.1% of this group could specify the illness. The mean mental health literacy score was 111.8 [Standard Deviation (SD) = 13.9]. Individuals with primary and secondary school qualifications had significantly lower scores in Factor 2 (erroneous beliefs/stereotypes) and Factor 3 (First-aid skills and assistance-seeking behaviour) of the MHLq than those with higher education. This research highlights persisting mental health misconceptions, limited knowledge about specific mental illnesses, and low help-seeking behaviour among young adult Malawians. Higher education is linked to a better understanding of mental health. Prioritising community education on causes, signs, treatments, and prognosis of mental illness is crucial for increased mental health literacy.
CancerSpot: A multi-cancer early detection test developed and validated on a retrospective cohort
Authors: Basu Swaraj , Hiremath M Prakash , Rathod Nihesh , Chatterjee Aditi , Vishwanath Divya , Ghosh Arunima , Sanguri Sweta , Chakraborty Sampuran , Tripathi Aastha , Preetha RT , Nair Arya , Kumar Goutham , Sekar Kannadhasan , Yete Subuhi , Bhanumathy G , Bahadur Urvashi , Radhakrishnan Aneesha , Khan Ankita , Kannan S Yasodha , Bollipalli Lavanya , Ghana Pallavi , Ramanathan Aparnaa , Saha Puja , Phalke Sameer , Cantor Charles , Limaye Sewanti , Chandru Vijay , Veeramachaneni Vamsi , Hariharan Ramesh 
Published: December 2024

AbstractNext-generation sequencing (NGS) technologies have transformed biomarker discovery, enabling the detection of disease-associated markers at the earliest stages of illness. In this study, we introduce a blood-based, non-invasive test for multi-cancer detection using cell-free DNA (cfDNA) methylation sequencing. The test employs a novel methylation scoring system derived from sequencing data and integrates machine learning to analyze a retrospective cohort of newly diagnosed cancer cases and controls recruited from multiple centers across India. To enhance robustness, the study includes a substantial proportion of controls with habitual tobacco and alcohol use, ensuring the test’s resilience against confounding factors. The test’s accuracy was further validated through synthetic data augmentation, demonstrating reliability under conditions of random signal perturbation. At an approximate specificity of 97%, the assay achieves sensitivities of 79.3% for Stage I, 78.4% for Stage II, 78.4% for Stage III, and 86.8% for Stage IV cancers in an independent validation cohort. Additionally, the test demonstrates Top 2 Tissue of Origin (TOO) accuracies of 78.3% for Stage I, 79.3% for Stage II, 82.8% for Stage III, and 69.7% for Stage IV cancers. This blood-based test holds considerable promise for early cancer detection, offering a precise test for cancer screening.
Neural Network-Based Assessment of Coronary Angiogram Flow
Authors: Resnick Jesse M. , Assi Ismael Z. , Pastapur Aishwarya , Sankardas Ajit Mullasari , Figueroa C. Alberto , Nallamothu Brahmajee K. 
Published: December 2024

AbstractAdequate blood flow through the coronary tree is critical for maintaining cardiac perfusion. Coronary angiography has the potential to provide rich and dynamic hemodynamic information, however, current strategies to assess flow through the coronary vessels depend on either subjective expert opinion (TIMI flow grade) or laborious frame-by-frame anatomical analysis (TIMI frame count and quantitative flow ratio). Here we present a strategy for automated characterization of bulk flow through the coronary tree using the right coronary artery as an example. We leverage the AngioNet neural network to generate sequential segmentations of angiograms, create time series of the summed segmentation intensities (i.e., a contrast intensity profile), and quantitatively characterize the filling and washout phases of these intensity profiles. We demonstrate that AngioNet-derived frame counts and normalized mean filling slopes of contrast intensity profiles correlate well with manual frame counts and flow grades in both our derivation and validation datasets. Furthermore, the generated washout dynamics appear to provide different information to the traditional frame count and flow grade metrics, which only deal with the initial filling phase, suggesting that washout dynamics of the contrast intensity profiles may capture novel information about the coronary microcirculation.
Platelet bioenergetics correlate with skeletal muscle metabolism in C57BL/6J mice
Authors: Wilkinson Mia S , Ferguson Emily J , Bureau Justin , Veeneman Jennifer LMH , Lima Patricia DA , McGlory Chris , Dunham-Snary Kimberly J 
Published: December 2024

SummarySkeletal muscle insulin resistance is a key step in progression of cardiometabolic disease, and impaired mitochondrial bioenergetics has been implicated. However, mitochondrial bioenergetic research in skeletal muscle is limited by the need for muscle biopsies. We sought to determine if platelet bioenergetics could be used as a minimally invasive surrogate for skeletal muscle bioenergetics. Multiple parameters of mitochondrial respiration, measured by high resolution respirometry, correlated between platelets and gastrocnemius muscle in mice. We propose the coupling state of platelet mitochondria reflects that of skeletal muscle in mice, providing a foundation for future research on using platelets as a liquid biopsy for muscle mitochondrial health in cardiometabolic disease, offering early insights into muscle metabolism to enhance clinical biomarker implementation.Graphical Abstract
Identification of colorectal malignancies enabled by phasor-based autofluorescence lifetime macroimaging and ensemble learning
Authors: Lagarto João L. , Herrando Alberto I. , Rego Rafaela , Fernández Laura , Azevedo José , Domingos Hugo , Vieira Pedro , Parvaiz Amjad , Shcheslavskiy Vladislav I. , Silva Pedro G. , Castillo-Martin Mireia 
Published: December 2024

AbstractSignificanceColorectal cancer (CRC) remains one of the most frequent cancers and a leading contributor to cancer-associated mortality globally. CRCs are often diagnosed at an advanced stage, which leads to high mortality and morbidity. This outcome is exacerbated by high rates of recurrence and postoperative complications that contribute substantially to poor prognosis. Advancements in endoscopic assessment have improved CRC prevention, early detection, and surveillance over the years. Yet, CRC remains one of the most significant health challenges of the 21st century. Label-free optical spectroscopy methods have long been explored as potential partners to endoscopy, not only to enhance diagnostic accuracy but also to confer predictive capabilities to endoscopic evaluations.AimWe investigated the potential of time-resolved autofluorescence measurements excited at 375 nm and 445 nm to correctly classify benign and malignant tissues in CRC surgical specimens from 117 patients.ApproachMultiparametric autofluorescence lifetime data were collected in two distinct datasets, which were used for training (n = 73) and testing (n = 44) a supervised ensemble learning classification model, with standard histopathology assessment serving as ground truth.ResultsUsing 5-fold cross-validation, we achieved 82.6 ± 0.02% sensitivity, 90.4 ± 0.01% specificity, 87.4 ± 0.01% accuracy, and 0.941 ± 0.004 area under the curve (AUC) for training data. Evaluation on unseen test data yielded similar results, with 85.2% sensitivity, 84.5% specificity, 84.8% accuracy, and 0.915 AUC.ConclusionsWhile preliminary, our findings underscore the potential impact of AI-assisted autofluorescence lifetime measurements in advancing CRC prevention, early detection, and surveillance efforts.
Glucagon-like peptide-1 receptor agonists (GLP-1RA) for neuroprotection following aneurysmal subarachnoid haemorrhage (aSAH): a scoping review protocol
Authors: Thomas Matt , Mastitskaya Svetlana , Parker Sam , Cookson Ruth , Holmes Lucy , Marsh Aidan , Ramesh Aravind , Rudd Sarah , Teo Mario , Mortimer Alex 
Published: December 2024

AbstractObjectiveThe objective of this scoping review is to understand the extent and type of evidence in relation to the use of glucagon-like peptide-1 receptor agonists (GLP1-RA) for neuroprotection in aneurysmal subarachnoid haemorrhage (aSAH).IntroductionThe individual and societal costs of aSAH remain high. Effective neuroprotection would reduce morbidity and mortality but there are uncertainties around both established and emerging therapies. GLP1-RA show promise as neuroprotective drugs in other forms of acute and chronic brain injury and could be repurposed for aSAH.Inclusion criteriaAnimal and human studies of the use of GLP1-RA for aSAH will be included. Key exclusions are traumatic or non-aneurysmal subarachnoid haemorrhage, or the use of multi-agonist drugs.MethodsSearches will conducted in Embase (Ovid), Medline (Ovid), Cochrane Central Register of Controlled Trials (Wiley) and the World Health Organisation’s International Clinical Trials Registry Platform with no limits applied. Studies for data extraction will be identified by two independent reviewers after screening of titles and abstracts then full text review of potentially relevant articles against inclusion criteria. Data will be extracted by two independent reviewers using a charting tool based on the Joanna Briggs Institute template. A narrative review and summary of findings will be presented.
Identification of coxsackievirus A24 variant during an acute hemorrhagic conjunctivitis outbreak in coastal Kenya, 2024
Authors: Lambisia Arnold W. , Morobe John Mwita , Moraa Edidah , Mwarumba Salim , Korir Fredrick K.N. , Athman Raila Seif , Kiptui Rebecca , Mbee Micheal , Mugo Nelly , Amoth Patrick , Muange Penny , Houldcroft Charlotte J. , Barasa Edwine , Mwangangi Joseph , Githinji George , Holmes Edward C. , Ochola-Oyier Lynette Isabella , Agoti Charles N. 
Published: December 2024

AbstractBackgroundIn early 2024, a surge in acute hemorrhagic conjunctivitis (AHC), also referred as “red eye” disease, was observed in coastal Kenya, prompting the Ministry of Health to issue an outbreak alert. Herein, we investigated the etiology of this outbreak.MethodsOcular swabs were obtained from 13 individuals presenting with AHC at a Mombasa clinic in early February 2024. Ten of these were analyzed using bacterial cultures, and all 13 using a pan-adenovirus quantitative PCR (qPCR) and metagenomic sequencing. Potential viral etiology was confirmed by a specific qPCR, amplicon sequencing and phylogenetic analysis.ResultsBacterial cultures yielded no growth except in three samples where non-pathogenic bacteria were detected. All 13 samples were adenovirus qPCR negative.Metagenomic sequencing detected coxsackievirus A24 variant (CA24v) in three of the 13 samples. CA24v detections were confirmed by both CA24v specific qPCR and amplicon sequencing of an approximately 450 nucleotide long VP4/2 junction genomic region. Phylogenetic analysis of the VP4/2 sequences showed that they were closely related to CA24v genotype IV.ConclusionThe AHC epidemic in coastal Kenya in early 2024 was likely caused by CA24v. Metagenomic sequencing is a powerful tool for identifying potential causative agents of new disease outbreaks.
AER-270 and TGN-020 are not aquaporin-4 water channel blockers
Authors: Unger Lucas , Wagner Kim , Steffen Jonas H , Wind Malene Lykke , Al-Jubair Tamim , Zou Hongjun , Clarke-Bland Charlotte , Murray Rebecca , Qureshi Bareerah , Lundström Susanna , Gaetani Massimiliano , Poyner David , Ayub Hoor , Wheatley Mark , Gourdon Pontus , Yool Andrea J , Törnroth-Horsefield Susanna , Bill Roslyn M , Salman Mootaz M. , Kitchen Philip 
Published: December 2024

AbstractAquaporin-4 (AQP4) is the most abundant water channel protein in the brain. It controls water homeostasis, facilitates glymphatic function and is a drug target for brain edema following injury or stroke. Dysregulation of brain water homeostasis affects millions of people every year leading to death, disability and cognitive decline, for which no medicines are available. Two compounds, AER-270 and TGN-020, are sold as AQP4 inhibitors and a prodrug of AER-270 is currently in a phase I human trial. However, the direct effect of these compounds on AQP4 function has not been unequivocally demonstrated. Our data across multiple cellular and molecular assay systems demonstrate, unexpectedly, that AER-270 and TGN-020 do not inhibit AQP4. Although we observed an apparent inhibitory effect of AER-270 and TGN-020 in theXenopus laevisoocyte assay, there was no effect in assays using reconstituted recombinant AQP4 or mammalian cells expressing exogenous or endogenous AQP4. We identify alternative mechanisms of action for both molecules that may explain previously reportedin vivoresults that were interpreted in the context of AQP4 inhibition. Overall, we conclude that AER-270 and TGN-020 should not be used to investigate the AQP4-dependence of biological processes in the brain.
A novel SUN1-ALLAN complex coordinates segregation of the bipartite MTOC across the nuclear envelope during rapid closed mitosis in Plasmodium
Authors: Zeeshan Mohammad , Blatov Igor , Yanase Ryuji , Ferguson David J. P. , Pashley Sarah L. , Chahine Zeinab , Botté Yoshiki Yamaryo , Mishra Akancha , Marché Baptiste , Bhanvadia Suhani , Hair Molly , Batra Sagar , Markus Robert , Brady Declan , Bottrill Andrew , Vaughan Sue , Botté Cyrille Y. , Le Roch Karine , Holder Anthony A. , Tromer Eelco C. , Tewari Rita 
Published: December 2024

AbstractMitosis in eukaryotes involves reorganization of the nuclear envelope (NE) and microtubule-organizing centres (MTOCs). During male gametogenesis in Plasmodium, the causative agent of malaria, mitosis is exceptionally rapid and highly divergent. Within 8 min, the haploid male gametocyte genome undergoes three replication cycles (1N to 8N), while maintaining an intact NE. Axonemes assemble in the cytoplasm and connect to a bipartite MTOC-containing nuclear pole (NP) and cytoplasmic basal body, producing eight flagellated gametes. The mechanisms coordinating NE remodelling, MTOC dynamics, and flagellum assembly remain poorly understood.We identify the SUN1-ALLAN complex as a novel mediator of NE remodelling and bipartite MTOC coordination duringPlasmodiummale gametogenesis. SUN1, a conserved NE protein, localizes to dynamic loops and focal points at the nucleoplasmic face of the spindle poles. ALLAN, a divergent allantoicase, has a location like that of SUN1, and these proteins form a unique complex, detected by live-cell imaging, ultrastructural expansion microscopy, and interactomics. Deletion of either SUN1 or ALLAN genes disrupts nuclear MTOC organization, leading to basal body mis-segregation, defective spindle assembly, and impaired spindle microtubule-kinetochore attachment, but axoneme formation remains intact. Ultrastructural analysis revealed nuclear and cytoplasmic MTOC miscoordination, producing aberrant flagellated gametes lacking nuclear material. These defects block development in the mosquito and parasite transmission, highlighting the essential functions of this complex.