bluuebunny/crossref_metadata_2025_split huggingface dataset:
Dissecting DNA-mismatch-repair-driven mutational processes in human cells
Authors: Owusu Michel , Menche Jörg , Loizou Joanna , Weghorn Donate 
Published: February 2025

AbstractMismatch repair (MMR) is a crucial DNA repair pathway that maintains genomic integrity by correcting replication errors and various forms of DNA damage. MMR deficiency (MMRd) leads to increased mutation rates, microsatellite instability, and contributes to tumorigenesis in multiple cancer types. Using a CRISPR-Cas9-mediated knockout assay in human isogenic cell lines, we characterised mutational profiles in MMR-deficient cells. Our findings revealed expected increases in mutation burden and the emergence of known MMR-associated mutational signatures. Notably, we identified a previously unconnected process, SBS57, and linked it to germline single-nucleotide polymorphisms and MMR-driven indels in MMRd cells, establishing its association with tensor signature TS27. Comparative analyses ofin vitroMMRd profiles andin vivotumour data uncovered key differences in mutational signatures, highlighting the biological context dependence of MMR-associated mutations. Furthermore, we provide direct experimental evidence that MMR plays a role in repairing 5-methylcytosine deamination, a repair process previously inferred from tumour sequencing data. These findings offer novel insights into MMR deficiency, shedding light on previously uncharacterised mutational mechanisms and their implications in cancer.
Understanding Acute Respiratory Illness in Nepalese Children Under Five: Insights from the 2016 NDHS
Authors: Dhodari Anish , Dhakal Anisha , Pokhrel Joshna , Bhattarai Pragya 
Published: February 2025

AbstractAcute Respiratory Illness (ARI) remains a critical public health challenge for children under five in Nepal, with persistent socioeconomic inequities in disease burden. This cross-sectional study analyzed Nepal’s 2016 Demographic and Health Survey (n=4,887) to identify determinants of ARI using caregiver reported symptoms of rapid breathing and chest-related issues within two weeks of the survey. Weighted logistic regression analyses examined associations between ARI and variables such as wealth quintile, residence type, maternal education, and child age.Nationally, ARI prevalence stood at 2.41%, with pronounced disparities: children from the poorest wealth quintile had 5.6× higher prevalence than the richest (3.32% vs 0.59%), while Province 6 reported the highest regional burden (3.37%). Multivariate analysis confirmed household wealth as the significant predictor (AOR=1.60, 95% CI:0.063–40.836), though wide confidence intervals indicated model overdispersion. Notably, 84.92% of caregivers sought healthcare—primarily through private facilities (32.30%) and pharmacies (27.92%)—highlighting gaps in public sector utilizationThese findings reveal wealth-based health disparities despite Nepal’s progress toward SDG child mortality targets. The results advocate for province-specific interventions in high-burden regions like Province 6, including mobile pneumonia clinics and biomass fuel transition programs. Socioeconomic disparities play a key role in ARI prevalence among children under five in Nepal. Interventions aimed at reducing care-seeking fragmentation while targeting poverty-alleviation strategies to reduce ARI’s disproportionate impact on marginalized populations could be beneficial. Future research should focus on identifying additional risk factors that were not looked into by the NDHS survey and evaluating targeted prevention strategies.
Pathways to suicidal ideation for young people engaged in mental health care
Authors: Varidel Mathew , Hickie Ian B. , An Victor , Cripps Sally , Marchant Roman , Robinson Jo , La Sala Louise , Capon William , Turner Ashlee , Tashevski-Beckwith Alexander , Scott Elizabeth , Iorfino Frank 
Published: February 2025

AbstractBackgroundSuicidal thoughts and behaviours (STBs) have a profound impact on individuals, communities, and healthcare systems. A wide range of factors have been shown to be associated with STBs. Within prior research it is also common to distinguish between proximal and distal factors, usually by distinction of short compared to long-term prediction. We frame the distinction between proximal and distal factors on suicidal ideation as direct or indirect dependencies using the inferred structure of probabilistic graphical models (PGMs).MethodsWe used cross-sectional data from a sample of 1020 help-seeking individuals aged 12-25 years from Australia that while engaged in a mental health care, contributed data to a digital platform. We inferred the posterior distribution of the dependency structure assuming both undirected PGMs and Bayesian networks (BNs). We then used the BN analysis to infer the causal effect that changing one variable has on another using a counterfactual query.ResultsWe show that factors encompassing depressed mood, functional impairment, poor social connection, and psychosis-like experiences are proximal. Whereas experiencing a traumatic event, anxiety, insomnia, and unrefreshed sleep are distal factors. Proximal factors tended to have the greatest effect on suicidal ideation, while anxiety symptoms and experiencing a traumatic event were the most influential distal factors.ConclusionsThese relative timings of events and their effects on suicidal ideation could be used to understand the future likelihood of suicidal ideation, and aid planning of targeted interventions.
Neural Networks Accurately Predict Precise Metrics of Hospital Resource Utilization for Total Hip Arthroplasty: A Retrospective Database Study
Authors: Abbas Aazad , Lex Johnathan R. , Toor Jay , Khalil Elias B. , Ravi Bheeshma , Whyne Cari 
Published: February 2025

AbstractBackgroundTotal hip and knee arthroplasties (THAs and TKAs) are some of the most common and successful surgeries. Predicting their duration of surgery (DOS) and length of stay (LOS) has massive implications for costs and resource management. The purpose of this study was to predict the DOS and LOS of THAs using machine learning models (MLMs) based on preoperative factors.MethodsThe American College of Surgeons (ACS) National Surgical and Quality Improvement (NSQIP) database was queried for elective unilateral THA procedures. Multiple MLMs were constructed to predict DOS and LOS. Models were evaluated according to mean squared error (MSE), buffer accuracy, and classification accuracy. To ensure useful predictions, the results of the models were compared to a mean regressor and previous MLM predictions for primary TKAs.Results196,942 patients were included. The neural network had the best MSE, buffer and training accuracies for both DOS and LOS. For DOS testing, the neural network MSE was 0.916, with the 30-minute buffer and ≤120 min, >120 min accuracies being 75.4% and 88.5%. For LOS testing, the neural network MSE was 0.567, with the 1-day buffer and ≤2 days, >2 accuracies being 70.3% and 80.9%. Slightly reduced performance was found for THA compared to TKA for DOS and LOS (3 to 5%), with similar important features identified.ConclusionMLMs based on preoperative factors successfully predicted the DOS and LOS of elective unilateral THAs, with similar performance to TKA. Future work should include operational factors to apply these models to real world resource optimization.
Sex-specific Trends in the Use of Temporary Mechanical Circulatory Support in patients listed for Orthotopic Heart Transplant Before and After the UNOS Allocation System Change
Authors: Cyrille-Superville Nicole , Patel Priyesh A , White Brian N , Patel Snehal R , Garcia Rachel , Rose Heather , Bernado Susan , Harmon Lauren , Nandkeolyar Shuktika , Mishkin Joseph D , Gulati Sanjeev K , Doshi Amar , Frank Theodore A , Devore Adam D 
Published: February 2025

AbstractBackgroundSince the United Network for Organ Sharing (UNOS) allocation system change patients listed for orthotopic heart transplant (OHT) are more likely to be on temporary mechanical circulatory support (tMCS). Limited sex specific data exits for use and outcomes of tMCS since the allocation change.MethodsWe queried the UNOS registry for patients listed for OHT on tMCS from October 1, 2015 to June 28, 2023, comparing baseline characteristics and outcomes between sexes pre- and post-allocation change.ResultsWomen comprised 23% of patients listed for OHT on tMCS before and after the allocation change, despite similar cardiac index (CI) compared with men (pre: 2.03 vs 2.09 L/min m2p=0.21; post: 1.92 vs 1.92 L/min m2p=0.89). Women were significantly younger (54 vs 57 years; p<0.001), had lower BMI (26.9 vs 27.2; p 0.006), were more likely to be on intra-aortic balloon pump (IABP) (67% vs 61% p <0.001) and had shorter waitlist times (13 vs 16 days; p <0.001). Waitlist mortality decreased similarly for both sexes (3.6% vs 3.8%; p= 0.7). There was no significant difference in 1-year post-transplant survival between the sexes in either era (HR: 0.9, 95% CI: 0.76, 1.06 p=0.2), however, 1-year post-transplant survival improved overall for patients bridged with tMCS post allocation change independent of sex (HR 0.70 (95% CI: 0.54 to 0.90; p=0.005).ConclusionDespite an increase in the use of tMCS as a bridge to OHT since the UNOS allocation change, women comprise less than a quarter of patients listed on tMCS despite similar CI, suggesting possible underuse in women. Notably, for those bridged to OHT in the post allocation era, waitlist mortality has improved for both sexes and 1-year post-transplant survival has also improved independent of sex.
Decay and Solid-Liquid Partitioning of Mpox and Vaccinia Viruses in Primary Influent and Settled Solids to Guide Wastewater-Based Epidemiology Practices
Authors: Phaneuf Jacob R. , Cha Gyuhyon , Hatt Janet K. , Konstantinidis Konstantinos T. , Graham Katherine E. 
Published: February 2025

AbstractWastewater-based epidemiology (WBE) has proven to be a powerful tool for tracking the spread of viral pathogens, such as SARS-CoV-2, but as WBE has expanded to include new pathogens, such as mpox virus, more data is needed to guide practitioners on how to design WBE campaigns. Here, we investigated the decay rates of heat-inactivated mpox (HI-MPXV) and attenuated vaccinia virus (VV) in primary influent and settled solids collected from a local POTW at 4°C, 22°C, or 35°C using digital PCR. Subsequently, we studied the solid-liquid partitioning of the viruses in primary influent. Over the 30-day study period, we observed no significant difference in log-linear decay rates between viruses (p=0.5258), with significantly higher decay rates in primary influent (0.109-0.144/day) compared to settled solids (0.019-0.040/day) at both 22°C (p=0.0030) and 35°C (p=0.0166). Furthermore, as part of the partitioning experiment, we found that HI-MPXV and VV adsorb to the solids fraction of primary influent at higher intensities than previously studied enveloped viruses (KF= 1,000-31,800 mL/g, n = 1.01-1.41). Likewise, it was determined in the partitioning experiment that a concentration of greater than 103gc/mL in raw influent was needed for the viable quantification of mpox and vaccinia viruses in the clarified liquid fraction of raw primarily influent. Our study provides essential insights into informative sample collection and storage conditions for the analysis of wastewater and for transport modeling studies. Due to the slow decay observed in settled solids at all tested temperatures in the persistence experiment, this matrix may be most suitable for retrospective analyses of community infection of the mpox virus.
Leveraging long-read assemblies and machine learning to enhance short-read transposable element detection and genotyping
Authors: Daigle Austin , Whitehouse Logan S. , Zhao Roy , Emerson JJ , Schrider Daniel R. 
Published: February 2025

ABSTRACTTransposable elements (TEs) are parasitic genomic elements that are ubiquitous across the tree of life and play a crucial role in genome evolution. Advances in long-read sequencing have allowed highly accurate TE detection, though at a higher cost than short-read sequencing. Recent studies using long reads have shown that existing short-read TE detection methods perform inadequately when applied to real data. In this study, we use a machine learning approach (called TEforest) to discover and genotype TE insertions and deletions with short-read data by using TEs detected from long-read genome assemblies as training data. Our method first uses a highly sensitive algorithm to discover potential TE insertion or deletion sites in the genome, extracting relevant features from short-read alignments. To discriminate between true and false TE insertions, we train a random forest model with a labeled ground-truth dataset for which we have calculated the same set of short-read features. We conduct a comprehensive benchmark of TEforest and traditional TE detection methods using real data, finding that TEforest identifies more true positives and fewer false positives across datasets with different read lengths and coverages, while also accurately inferring genotypes and the precise breakpoints of insertions.By learning short-read signatures of TEs previously only discoverable using long reads, our approach bridges the gap between large-scale population genetic studies and the accuracy of long-read assemblies. This work provides a user-friendly tool to study the prevalence and phenotypic effects of TE insertions across the genome.
Latent activity in TnpB revealed by mutational scanning
Authors: Thornton Brittney W. , Weissman Rachel F. , Tran Ryan V. , Duong Brenda T. , Rodriguez Jorge E. , Terrace Cynthia I. , Groover Evan D. , Park Jung-Un , Tartaglia Julia , Doudna Jennifer A. , Savage David F. 
Published: February 2025

AbstractTnpB is an evolutionarily diverse family of RNA-guided endonucleases associated with prokaryotic transposons. Due to their small size and putative evolutionary relationship to Cas12s, TnpB holds significant potential for genome editing and mechanistic exploration. However, most TnpBs lack robust gene-editing activity, and unbiased profiling of mutational effects on editing activity has not been experimentally explored. Here, we mapped comprehensive sequence-function landscapes of a TnpB ribonucleoprotein and discovered many activating mutations in both the protein and RNA. Single-position changes in the RNA outperform existing variants, highlighting the utility of systematic RNA scaffold mutagenesis. Leveraging the mutational landscape of the TnpB protein, we identified enhanced protein variants from a combinatorial library of activating mutations. These variants increased editing in human cells andN. benthamianaby over two-fold and fifty-fold relative to wild-type TnpB, respectively. In total, this study highlights unknown elements critical for regulation of endonuclease activity in both the TnpB protein and the RNA, and reveals a surprising amount of latent activity accessible through mutation.
Type VI secretion phenotypic heterogeneity ensures trade-off between antibacterial activity and resistance in EnteroaggregativeE. coli
Authors: Taillefer Boris , Schattenberg Florian , Doan Thierry , Müller Susann , Cascales Eric 
Published: February 2025

ABSTRACTThe type VI secretion system (T6SS) is a nanoweapon deployed by bacteria to deliver effectors into target cells, allowing niche colonization or host invasion. In entero-aggregativeEscherichia coli(EAEC), the expression of the T6SS gene cluster is responsive to iron starvation by the Fur regulator, and to Dam-dependent methylation. However, fluorescence microscopy recordings showed that the T6SS displays heterogeneous expression in a clonal population. The population is composed of three types of cells in a stable equilibrium: non producers (OFF), producers, and assemblers (ON). Single-cell analyses further showed that the activation state is transmitted to the progeny, but the overall distribution respects the equilibrium suggesting a genetic control of heterogeneity. Mutagenesis of Fur-binding boxes and GATC sites revealed that specific promoter elements control this heterogeneity. Phenotypic characterization of the ON and OFF subpopulations demonstrated that ON cells eliminate susceptible target cells, whereas OFF cells survive attacks from T6SS-defensive bacteria. The heterogeneity of EAEC T6SS is therefore an attenuation strategy conferring a trade-off between antibacterial efficiency and survival in polymicrobial environments.
Breath Volatile Flux Reveals Age-Dependent Metabolic Markers for Breast Cancer Detection
Authors: Issitt Theo , Turvill James , Piper Jenny , Redeker Kelly 
Published: February 2025

AbstractBreast cancer remains a dominant health risk for women globally with early detection a primary indicator for successful treatment and survival. Current approaches for diagnosis are invasive, costly, and accuracy can be improved. Breath testing using volatile organic compounds (VOCs) as biomarkers presents an exciting avenue for non-invasive cancer diagnosis. However, breath sampling for cancer diagnosis has not yet delivered reliable biomarkers or technology. This is, in-part due to methodology, which introduces confounding factors when attempting to scale to diverse patient populations. We utilize a novel approach to human clinical breath sampling, in which we quantify breath volatile flux. Breath volatile flux considers inhaled air alongside exhaled air to generate a dynamic breath profile which enhances our ability to identify compounds metabolized in humans. We present a novel breath collection platform into which breast cancer clinic patients, in a pilot study of 60 women, provided 5 mins duration breath samples for analysis by gas chromatography mass spectrometry (GC-MS). GC methods targeted a suit of 11 previously identified compounds alongside non-targeted scans. When examining the data across the entire cohort, butanone was the only significantly altered (increased) breath volatile and was able to separate benign tumour and cancer patients from normal patients. However, patient age was observed as a primary confounding factor and reduced the accuracy of butanone’s diagnostic potential. When age was controlled for, chloroform, styrene and isopropyl alcohol acted as indicators of breast cancer health status. Furthermore, once age was accounted for and cancer patients were identified, grade of cancer was indicated by chloroform and DMS fluxes. Using the top 5 discriminate compounds and receiver operator curves we were able to identify cancer from normal patients with area under the curve of 93.4%, grade 2/3 cancers from normal patients with 97.6% AUC, and benign from normal patients with 90.5% AUC. This study suggests that volatile flux measurements from breath allows successful identification, and separation of, cancer, benign tumour and healthy patients.
Use of Computational Phenotypes for Predicting Genetic Subgroups of Cerebral Palsy
Authors: Alkuraya Imen , Almansa Alexandra Santana , Eleonu Azubuike , Avillach Paul , Poduri Annapurna , Srivastava Siddharth 
Published: February 2025

AbstractIntroductionEmerging evidence suggests that 20–30% of cases of cerebral palsy (CP) may have a genetic cause. Our group previously identified subsets of patients with CP or CP-masquerading conditions who warrant genetic testing, including those with regression or progressive neurological symptoms (CP masqueraders) and those without any known risk factors for CP (cryptogenic CP). Recognition of these subgroups in clinical settings remains challenging.MethodsTo address this challenge, we developed and evaluated a computational phenotyping approach using ICD- 9/ICD-10 billing codes to automatically identify patients with unexplained CP or CP-masquerading conditions who may benefit from genetic testing. We applied this computational phenotyping approach to a cohort of 250 participants from the Boston Children’s Hospital CP Sequencing Study, aimed at identifying genetic causes in CP and CP-masquerading conditions.ResultsManual review served as the gold standard, identifying 8% as CP masqueraders, 42% as cryptogenic CP, and 50% as non-cryptogenic CP. Computational phenotyping based on ICD-9/10 codes achieved a sensitivity of 95%, specificity of 72%, positive predictive value of 77%, and negative predictive value of 94% in identifying cases warranting genetic testing.ConclusionsOur findings demonstrate the feasibility of using computational phenotyping to identify patients with CP or CP- masquerading conditions who warrant genetic testing. Further studies are needed to evaluate the effectiveness and real-world application of this tool in larger healthcare systems. Nonetheless, the computational phenotyping approach holds promise as a possible clinical decision support that could be integrated into electronic health record systems, enhancing clinical workflows and facilitating actionable genetic diagnoses.
Causal association of long COVID with brain structure changes: Findings from a 2-sample Mendelian randomization study
Authors: Li Hui , Yang Yihe , Ding Pingjian , Xu Rong 
Published: February 2025

AbstractNearly 7.5% U.S. adults have long COVID. Recent epidemiological studies indicated that long COVID, is significantly associated with subsequent brain structure changes. However, it remains unknown if long COVID is causally associated with brain structure change. Here we applied two Mendelian Randomization (MR) methods – Inverse Variance Weighting MR method (IVW) for correlated instrument variables and Component analysis-based Generalized Method of Moments (PC-GMM) – to examine the potential causal relationships from long COVID to brain structure changes. The MR study was based on an instrumental variable analysis of data from a recent long COVID genome-wide association study (GWAS) (3,018 cases and 994,582 controls), the Enhancing NeuroImaging Genetics through Meta Analysis (ENIGMA) (Global and regional cortical measures, N = 33,709; combined hemispheric subcortical volumes, N = 38,851), and UK Biobank (left/right subcortical volumes, N = 19,629). We found no significant causal relationship between long COVID and brain structure changes. As we gain more insights into long COVID and its long-term health outcomes, future works are necessary to validate our findings and understand the mechanisms underlying the observed associations, though not causal, of long COVID with subsequent brain structure changes.
Exposure to bullying engages social distress circuits in the adolescent and adult brain
Authors: Paranko Birgitta , Garandeau Claire , Seppälä Kerttu , Putkinen Vesa , Santavirta Severi , Hirvonen Jussi , Salmivalli Christina , Nummenmaa Lauri 
Published: February 2025

AbstractDespite advances in understanding the psychological and social consequences of peer victimization, the immediate effects of bullying on the central nervous system remain elusive. Here we mapped the neural responses to simulated bullying in adolescents and adults and tested whether these responses are associated with real-life victimization experiences. Fifty-one adolescents aged 11–14 years, and 47 adults underwent a functional MRI (fMRI) while watching first-person videos of bullying (victimization) in the school environment, as well as neutral and positive social interactions in a similar setting. Exposure to bullying versus positive social interaction engaged the socio-emotional and threat response systems, as well as regions related to social cognition, sensory and interoceptive processing, and motor control. These responses were consistent across adolescents and adults and dependent on the current and past victimization experiences of the participants. This large-scale activation of neural systems subserving socioemotional, somatosensory, and interoceptive processing highlights how peer victimization evokes a severe stress and alarm state in the central nervous system.