Browse Articles
Discover research articles across all indexed journals
Preoperative nutritional support in children with Hirschsprung disease: a prospective multicenter open-label randomized controlled trial
Proteinase 3 is involved in presepsin production through neutrophil extracellular trap phagocytosis by macrophages
Protocol for an open labelled observational study in children & adolescents with severe asthma with an eosinophilic phenotype treated with mepolizumab (CASAM)
Introduction Children with severe eosinophilic asthma are at an increased risk of severe exacerbations, medication side effects, impaired lung function, and significantly reduced quality of life. The advent of biologic agents aimed at eosinophilic pathways has significantly improved management options for patients with severe asthma. Mepolizumab, an anti-interleukin-5 monoclonal antibody, was approved in 2018 as an add-on maintenance treatment for patients with severe eosinophilic asthma aged ≥6 years of age. Mepolizumab’s efficacy and safety is well documented in adults, but paediatric data remain limited. This real-world observational study will evaluate the long-term safety and efficacy of mepolizumab in children and adolescents, including those with comorbidities and on concomitant medications to provide a clearer picture of its performance in everyday clinical practice. Methods and analysis Design: CASAM is an open label, multinational (Spain and United Kingdom), multicenter (15 Spanish and 6 UK public institutions) observational cohort study. Sample size: 150 paediatric patients on mepolizumab for SA between 6–17 years of age will be enrolled. Study Duration: Study will be conducted over 36 months (12 months pre mepolizumab initiation and 24 months after initiation). Data Collection: Pseudonymized data (prospective and retrospective) from medical charts will be collected and entered in the electronic case report forms (eCRFs) of the electronic data capture (EDC) system. Primary Outcome: To compare the rates of clinically significant asthma exacerbations in the pre-exposure and the 12-month post-exposure period with mepolizumab treatment. Protocol Version: CASAM Study_Protocol_V2.0_16th November 2023 KCH Registration details: The study is registered with ClinicalTrials.gov (NCT05139381), IRAS number 306475.
Interleukin-27 is antiviral against Zika virus at the maternal-fetal interface
Computational analysis and modeling of climate impact on Pteridium aquilinum (L.) populations
The perinatal mental health experiences of black immigrant mothers in the UK: A qualitative systematic review and thematic synthesis
Introduction Mental health difficulties during and after pregnancy are common worldwide. Women from minoritised ethnic communities are disproportionately affected, as are those affected by migration factors. Research typically treats ethnic minority groups as homogenous despite having potentially different needs and experiences. In the UK, Black women face considerable maternal mental health disparities, warranting further attention. Aim To explore and understand the perinatal mental health (PMH) views and experiences of Black immigrant mothers in the UK, the support that was available to them and, perspectives on support received. Methods MAG Online Library, CINAHL, MEDLINE, PsycINFO and Scopus electronic databases were systematically searched. And thematic synthesis was undertaken with all the studies which met the eligibility criteria. Findings Four studies were retrieved, all focusing on postnatal depression. The synthesis generated three themes: i) perceived causes of PMH difficulties, ii) symptoms, signs and impact of PMH difficulties, iii) available support and coping means. Cultural beliefs permeated across all the themes. Conclusion Black immigrant mothers in the UK face challenges such as lack of support, inadequate information, cultural perceptions, and insufficient help from family, community, and healthcare professionals. Further research is needed that extends beyond postnatal depression and includes parent-infant relationships.
Author Correction: Inactivation of cytidine triphosphate synthase 1 prevents fatal auto-immunity in mice
Edge digital twin for coordinating flexible resources in distribution networks with communication constraints
CABNas-nir: A near-infrared classification for urban pipe network sludge on the fusion algorithm of NAS framework and active learning
Pipe network sludge is a complex pollutant aggregate deposited during long-term operation of urban sewage pipelines, and a key target for pollution control in environmental monitoring systems. Accurate source classification is critical for treatment optimization, pollution tracing, and resource recovery. Traditional methods have drawbacks like long processing time and low efficiency. Near-infrared spectroscopy (NIR) offers a new approach but faces spectral redundancy, limited samples, and biased features. This paper proposes CABNas-nir, a deep neural network under the neural architecture search (NAS) framework, integrating competitive adaptive reweighted sampling (CARS), baseline drift augmentation, and active learning (AL). It selects key spectral features via CARS to remove redundancy, uses baseline drift to generate augmented samples for small-sample issues, employs AL with K-means to select high-value samples, and constructs an optimal convolutional neural network(CNN)+long short-term memory(LSTM) model via NAS. Experiments show 92.86% accuracy, 14.29% higher than support vector machine (SVM,78.57%) and 35.72% higher than that of extreme gradient boosting (XGBoost,57.14%). SHapley Additive exPlanations (SHAP) analysis shows high-contribution spectra in 1400–1700 nm, with 1600–1700 nm significant. This algorithm significantly enhances the robustness of identifying the sources of pipe network sludge, laying a research foundation for the rapid and accurate identification of pipe network sludge.
Quantum electrodynamics of photonic time crystals
Eye tracking as a novel approach to cognitive assessment in DOC patients based on evidence from a multicenter clinical trial
Expression of Concern: Escalating spread of SARS-CoV-2 infection after school reopening among students in hotspot districts of Oromia Region in Ethiopia: Longitudinal study
Connecting algorithmic fairness and fair outcomes in a sociotechnical simulation case study of AI-assisted healthcare
Coupling geometric morphometrics and machine learning for mandibular sex estimation in Late Pleistocene and Late Modern populations
Abstract Accurate sex estimation is crucial for studying both modern and ancient human populations, yet methods are often limited to well-preserved skeletons. Here, we combine Geometric Morphometrics (GM) and Machine Learning (ML) to assess mandibular sexual dimorphism and classify sex across a wide chronological and geographic range to bracket the potential of this approach. Sixty-seven individuals from the modern, identified Luis Lopes collection (Portugal) and 18 Late Pleistocene individuals from Jebel Sahaba (Sudan) were surface scanned. Anatomical landmark coordinates were extracted and analyzed with GM, and ML models were trained on a subset of the modern sample to predict sex in both the remaining modern individuals and the Late Pleistocene specimens. GM revealed significant sexual dimorphism in all samples, and ML achieved high intrapopulation classification accuracy. However, predictions were less reliable when applied across the temporally and geographically distant Jebel Sahaba population, reflecting interpopulation differences in mandibular size and shape. These results demonstrate that while GM–ML approaches are powerful tools for sex estimation within populations, caution is required when extending models to other populations.
Anticodon-edited tRNA enables translational readthrough of COL4A5 premature termination codons
Alport syndrome is caused by variants in COL4A3 , COL4A4 , or COL4A5 , which encode the α3α4α5 chains of type IV collagen. These variants result in defects in the glomerular basement membrane (GBM) and impaired kidney function. Nonsense variants result in truncated proteins lacking the NC1 domain, thereby preventing proper GBM assembly and function and causing the most severe forms of the disease. Restoring full-length protein expression represents a potential therapeutic strategy for Alport syndrome and related disorders. Anticodon-edited transfer RNAs (ACE-tRNAs), which promote premature termination codon (PTC) readthrough, have shown promise in diseases such as cystic fibrosis, but their application in Alport syndrome remains unexplored. To assess the potential of ACE-tRNAs for PTC readthrough of COL4A5 nonsense variants, we employed a C-terminal NanoLuc-fused COL4A5 reporter system in which luminescence is produced only upon full-length protein translation. We introduced ACE-tRNAs into HeLa and 293T cells expressing one of four COL4A5 nonsense variants ( S36X, R1563X, S1632X, and R1683X ) identified in patients with X-linked Alport syndrome. Readthrough efficiency was evaluated via NanoLuc luminescence and western blotting. Furthermore, we assessed the efficiency of ACE-tRNA-restored α3α4α5 heterotrimer formation using a split NanoLuc-based assay. Our results show that application of ACE-tRNAs led to restored C-terminal luminescence across all four COL4A5 nonsense variants, indicating successful readthrough and full-length translation. Moreover, the restored COL4A5 proteins formed α3α4α5 heterotrimers. These findings support ACE-tRNA-mediated nonsense suppression as a promising therapeutic strategy for Alport syndrome, with the potential to restore GBM integrity in patients harboring nonsense variants.
SPLiCR-seq: A CRISPR-Based Screening Platform for RNA splicing Identifies Novel Regulators of IRE1α-XBP1 Signaling Under ER Stress
Development and validation of a risk prediction model for postoperative urinary retention after gynecologic abdominal-pelvic surgery
Exercise mitigates high-fat diet-induced cardiac dysfunction via APOE genotype- and immune-dependent mechanisms: A photon-counting CT study in adult mice
Background Cardiovascular dysfunction frequently accompanies aging and is often worsened by adverse lifestyle factors and genetic susceptibility. The apolipoprotein E ( APOE ) gene modulates susceptibility to cardiovascular disease, but how exercise and diet interact with APOE genotype remains insufficiently understood. We investigate the cardioprotective potential of exercise in humanized APOE -targeted replacement mice on control and high-fat diet, using photon-counting computed tomography (PCCT) and deep learning-based image segmentation. Methods This study included 251 male and female mice in mid-to-late life of APOE2 , APOE3 , and APOE4 genotypes with variation in humanized NOS2 ( HN ) mediated innate immune response, exercise status (exercised vs. sedentary) and diet (control vs. high-fat). Mice underwent in vivo cine cardiac PCCT imaging following contrast enhancement with liposomal iodine nanoparticles. Stroke volume, ejection fraction, and myocardial mass were derived from automated segmentation of cardiac structures using a 3D U-Net model. We assessed main and interaction effects of genotype, sex, HN status, age, exercise and diet using generalized linear models, while Mann-Whitney U tests assessed effects of exercise within stratified subgroups. Results Exercise was a significant predictor of improvement in several cardiac functional metrics with a large effect size. The interaction between exercise and diet was a significant predictor of reduced body mass and myocardial mass. Stratified analyses found that exercise improves cardiac functional metrics in APOE4 mice on both diets, and APOE3 mice primarily on control diet, while benefitting HN mice more than non-HN mice. Conclusions Voluntary exercise can partially rescue cardiac dysfunction induced by high-fat diet in adult APOE -targeted replacement mice, with benefits modulated by genotype, sex, and HN status. APOE4 and HN mice benefitted most from exercise. Contrast-enhanced PCCT combined with deep learning segmentation enables scalable, minimally invasive cardiac phenotyping and reveals interaction effects that are critical for designing precision lifestyle interventions in genetically at-risk populations.