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Prevalence of irritable bowel syndrome and its association with lifestyle factors among medical students in Jordan: a cross-sectional survey
A Stratification Method for Identifying Subgroups at High-Risk for Type 2 Diabetes in sub-Saharan Africa
DER: energy-aware financial task scheduling in multi-cloud environments with privacy constraints
An epifluorescence microscope design for naturalistic behavior and cellular activity in freely moving Caenorhabditis elegans
Abstract Understanding the neural basis of behavior requires imaging cellular activity in freely moving animals, which typically demands expensive, restrictive microscopy setups. To overcome these barriers, we developed Wormspy, a cost-effective, open-source epifluorescence microscopy system for high-magnification imaging and tracking of Caenorhabditis elegans . Wormspy enables the simultaneous recording of neuronal activity and behavioral dynamics without needing the animal to be restrained. We demonstrate its utility in imaging body wall muscles, sensory neurons, and subcellular calcium events within interneuron axons. Our platform reproduces known mutant phenotypes and uncovers, to the best of our knowledge, previously inaccessible sensorimotor correlations. We show that Wormspy provides a robust, modular framework that lowers technical barriers to high-resolution neural imaging, enabling flexible experimental designs for dissecting behavior in freely moving organisms.
Enhanced hydrogen adsorption on boron nickel gold modified Si60 nanocluster via DFT and machine learning analysis
Abstract In this study, we investigated the catalytic potential of silicon-based nanoclusters, specifically Si 60 , for hydrogen evolution reactions (HER), focusing on enhancements via substitutional doping with nickel (Ni) and boron (B), where boron and nickel are incorporated into the Si₅₉ lattice, enabling electronic structure modulation. Using Density Functional Theory (DFT) with the B3LYP functional, we examined hydrogen adsorption behavior on boron- doped, Ni-doped, gold-encapsulated Si₅₉ nanoclusters, denoted as B x dop Ni dop Au enc Si₅₉ (x = 1, 2, 3). Our findings show that doping introduces minimal structural distortion while improving cluster stability and reactivity. Boron-doping notably reduces the energy gap, enhancing electron transfer and promoting hydrogen adsorption. Gibbs free energy analyses confirm somewhat favorable catalytic activity, with ΔG H values ranging from − 0.837 to − 0.848 eV, highlighting the B x dop Ni dop Au enc Si₅₉ engineered doped nanoclusters as promising catalysts. Additionally, machine learning models, particularly ElasticNet Regression (R 2 = 0.9942), accurately predict hydrogen adsorption energies across various surfaces, from pristine H₂@Si₆₀ to B₃- doped systems. This demonstrates the models’ capability to capture structure–property relationships, accelerating catalyst optimization. Computational screening of Si 59 -based nanostructures revealed that H₂@B 2 dop Ni dop Au enc Si₅₉ exhibits a ΔG H value of − 0.836 eV, suggesting comparatively balanced hydrogen adsorption and improved HER catalytic potential among the evaluated systems. Overall, the results suggest that precise doping and surface engineering can significantly enhance the electronic, storage, and catalytic properties of silicon nanoclusters, offering valuable insights for the design of efficient HER catalysts in future sustainable energy technologies.
Integrated genomic analyses identify oncogenic pathway interplay in hepatocarcinogenesis defining specific molecular subtypes
Hybrid IGWO-Dingo optimized DeMoHybridNet model for multi-class leaf disease identification
Kynurenic acid mediates epicardial fat-induced lymphatic metabolic dysfunction in atrial fibrillation
Abstract Atrial fibrillation represents a prevalent cardiac arrhythmia whose pathogenic mechanisms remain incompletely understood. Here, we identify impaired atrial lymphangiogenesis as a critical determinant in atrial fibrillation pathogenesis. Analysis of human left atrial appendage specimens reveals decreased lymphatic vessel density in atrial fibrillation patients compared to those in sinus rhythm. Mechanistically, we demonstrate that epicardial adipose tissues from atrial fibrillation patients secrete kynurenic acid, which acts via GPR35 to disrupt lymphatic endothelial cell metabolism and mitochondrial homeostasis, ultimately promoting endothelial-to-mesenchymal transition. Using an organotypic culture system, we show that epicardial adipose tissue -derived factors directly impair lymphatic vessel formation. In vivo studies utilizing angiotensin II-induced and high-fat diet male mouse models confirm the critical role of lymphatic dysfunction in atrial fibrillation susceptibility. Therapeutic interventions promoting lymphangiogenesis, either through VEGFC administration or weight loss intervention by LY3437943 (the novel triple GIP, GLP-1, and glucagon receptor agonist), significantly attenuate atrial fibrillation inducibility. These findings establish lymphatic dysfunction as a novel pathogenic mechanism in atrial fibrillation and highlight lymphatic vessel formation as a promising therapeutic target.
Generation of a rhesus macaque harboring a multivalent reporter for assessing gene editing outcomes
A modular multi-color fluorescence microscope for simultaneous tracking of cellular activity and behavior
Abstract We present a modular epifluorescence tracking microscope which enables ratiometric imaging of muscles, neurons, and other structures in moving animals. The microscope is assembled entirely from commercial parts within 3 h, making the system broadly accessible. Leveraging the improved brightness and bleaching characteristics of recent genetically encoded indicators and fluorophores, the simple microscope is even suitable for calcium imaging of neurons in behaving animals, as we demonstrate in C. elegans . We also show how muscle dynamics in D. melanogaster larvae can be analyzed and how dual color fluorescence tracking elucidates inter-species interactions by visualizing both predatory nematodes and their prey. Finally, we showcase a configuration for brightfield imaging by tracking tardigrade gait as an example of utility for non-labeled species. The affordability of the hardware and ease of use of the accompanying software make this a suitable tool for education in addition to its use in research.
Antimicrobial activity of topcoat formulation based on synthesized new cyclodiphosph(V)azane derivatives as a biocide for protective coatings
Abstract Novel cyclodiphosph(V)azane sulfonamide ligands and their corresponding Cu²⁺ and Cd²⁺ metal complexes were synthesized and evaluated as antimicrobial additives for coating applications. The structures of the prepared compounds were confirmed using standard spectroscopic techniques. The synthesized compounds were incorporated into paint formulations, and the resulting coatings were systematically assessed for their mechanical, physical, and antimicrobial properties. The modified coatings exhibited enhanced physico-mechanical performance, with gloss values of 80–95, hardness ranging from 7 H to 9 H, adhesion improved from 4B to 5B, and impact resistance increased from 1.3 to 2.5 J. Antimicrobial activity was evaluated using the agar well diffusion method against representative Gram-positive and Gram-negative bacteria, as well as fungal strains. The cadmium complex demonstrated the highest activity, with inhibition zones ranging from 31.8 to 46.0 mm, while the copper complex showed moderate activity and the free ligand exhibited selective effects. Although incorporation into the coating matrix led to a reduction in antimicrobial activity, the coatings retained appreciable effectiveness against selected strains. The results indicate that cyclodiphosph(V)azane-based metal complexes are promising multifunctional additives for antimicrobial coatings, combining improved mechanical performance with significant biological activity.
An attention-demanding hunting paradigm engages the superior colliculus–zona incerta circuit mediating analgesia in male mice
Sustainable stabilization of expansive soils for slope applications using enzyme-induced carbonate precipitation and iron ore tailings
Joint clinical and molecular subtyping of COPD with variational autoencoders
Psychological relation of tandem nursing to children’s socio-emotional development and attachment to their caregiver
Abstract In tandem breastfeeding, a mother breastfeeds two children of different ages at the same time. Although it occurs regularly, there is little research on tandem-breastfeeding and its psychological aspects. The present set of two studies fills this research gap. Study 1 follows a qualitative approach to generate relevant psychological topics related to tandem breastfeeding through semi-structured interviews with tandem breastfeeding mothers and mothers who breastfed two children but not in tandem. In the quantitative Study 2, an online questionnaire was generated based on the relevant factors for tandem-breastfeeding identified in Study 1. We found that older children who were not breastfed in tandem changed their focus from the mother to the partner after birth of the younger sibling and rejected their mother, which was not the case for children who were breastfed in tandem. Tandem-breastfeeding mothers showed more attachment parenting and less authoritarian parenting. However, they felt increased anger and aggression towards the older child. The current set of studies provides the first scientific basis for research in psychological aspects of tandem nursing. It stresses the relevance of research in tandem breastfeeding to avoid adverse effects such as anger towards children, while promoting positive effects on the mother-child relationship.
Spring–Summer Caribbean Sea marine heatwaves tied to previous Winter Indian Ocean marine heatwaves
Spatiotemporal distribution of SARS-CoV-2 vaccines and vaccine-related proteins in mice and humans
Abstract Since the emergence of the COVID-19 pandemic, the successful distribution and application of mRNA vaccines have helped to contain the spread of SARS-CoV-2 and saved countless lives worldwide. mRNA vaccines are not only being developed and tested for infectious diseases, but also for numerous new applications, such as cancer therapy. Although the general mechanisms of mRNA vaccinations have been thoroughly studied, data regarding the local anatomical distribution after vaccination have been scarce. Here, we investigated the spatiotemporal distribution of BNT162b2 and mRNA-1273 vaccines in mice and deceased humans. We found that vaccine-related mRNA and spike protein could be detected at the vaccination site of patients and mice, with muscle-associated fibroblasts being a major source of spike protein expression. In contrast, we did not detect expression of vaccine-related spike protein in immune cells at the injection site. While mRNA-vaccine-related mRNA or spike protein could not be detected in extramuscular organs in humans in our study, it was detected in several organs in mice, even up to 7 days after initial vaccination. Together, these data enhance our understanding of mRNA vaccine kinetics and distribution patterns, providing valuable insights to guide scientists in refining future mRNA vaccine-based therapies whenever appropriate.
Dual site targeting of the bacterial 70S ribosome by tetracyclines
Performance of continuous glucose monitoring-based meal detection algorithms in young healthy adults
Abstract Continuous glucose monitoring (CGM) enables automated detection of eating events via meal detection algorithms (MDAs); however, CGM-only MDAs have not been comprehensively evaluated using a shared dataset. We compared nine published CGM-only MDAs using standardized metrics by testing them with CGM data from 16 young, healthy, normal-weight adults under free-living conditions. We employed a per-participant holdout design, with separate training, validation, and testing sets, and assessed performance on the test set (216 meals) using sensitivity, false positives per day (FP/day), and detection time (Δt). Sensitivity ranged from 49 to 90%, FP/day from 0.12 to 2.42, and Δt from 37 to 61 min. Fuzzy logic and simulation-based approaches showed the highest sensitivity (90% and 83%) but slower detection (> 59 min) and higher FP rates (> 1.28/day). Pattern-recognition classifiers (82%, 0.39 FP/day, 44 min; 77%, 0.33, 42 min) and a glucose-insulin-model-based method (77%, 0.22, 41 min) showed more balanced performance, while rate-of-change detectors were faster (37–38 min) but less sensitive (70–72%). No single MDA consistently outperformed others across metrics. Pattern-recognition and physiological modeling approaches demonstrated the most balanced performance, whereas rate-of-change methods enabled faster detection with reduced accuracy. Algorithm choice should reflect application priorities, such as early detection versus reliability.