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Adaptive cellular evolution in the intestine of hyperdiverse cichlid fishes
Design and evaluation of an intent-based web of things query framework for smart device discovery
Detection of anisotropic cosmic structures on a gigaparsec scale
Ontogenetic emergence of behavioral consistency in a self-fertilizing fish
A deep learning model to predict objective response to TACE and TKI-based therapy in HBV-related uHCC
Genetic diversity of late Neanderthals in northwestern Europe
Abstract Archaeological, osteological and genetic evidence suggests that Neanderthals lived in small groups 1,2 ; however, less is known about whether these groups were part of isolated communities or belonged to larger, well-connected populations 3 . The dense concentration of broadly contemporaneous Neanderthal sites in the Meuse Basin, Belgium 4 , provides a rare opportunity to study regional populations at high resolution. Here we generated genetic data from 27 Neanderthals who lived less than approximately 52,500 years ago from ten archaeological sites in Belgium and France, including a high-coverage genome from a 45,000-year-old individual from Goyet, Belgium. We show that most of these individuals are more closely related to one another than to other contemporaneous late Neanderthals in Europe. Further, some of these individuals carry DNA from a Neanderthal lineage predating the split of late Neanderthals. Although these Neanderthals overlapped temporally with early modern humans in northwestern Europe from around 47,000 years ago, we find no evidence of recent gene flow from modern humans. They also do not show the genetic signatures of mating among close relatives found in Altai Neanderthals, suggesting that they lived in larger or better-connected groups. Moreover, genetic load did not accumulate over time, arguing against progressive genetic deterioration as a driver of Neanderthal extinction.
ACADPro: XAI-student procrastination classification in academia using optuna optimized machine learning models
Adaptive user clustering enhanced BiLSTM-attention for short-term load forecasting in smart distribution networks
Transformer-based classification with enhanced causal explainability from otoscopic images
Abstract Otitis media is a major cause of hearing loss, particularly in children. However, nonspecific symptoms and subjective evaluations make its diagnosis challenging. To address this, we developed transformer-based models to classify tympanic membrane conditions from otoscopic images. This approach aims to enhance diagnostic transparency and reliability in clinical settings. We trained vision transformer (ViT) and Data-efficient Image Transformer (DeiT) models on 454 pediatric and adult otoscopic images. These models performed multi-class classification to distinguish between normal, effusion, and tube conditions. For explainability, we utilized Gradient-weighted Class Activation Map (Grad-CAM), Layer-wise Relevance Propagation (LRP), and Attention Rollout (AR). Furthermore, we introduced a hybrid fusion strategy based on Canonical Correlation Analysis. The framework’s effectiveness was then evaluated using insertion and deletion causal metrics. The ViT model achieved an accuracy of 97.78% (AUC: 0.998), outperforming DeiT, which reached 93.33% (AUC: 0.994). Notably, ViT attained an F1-score of 97.30% for the effusion class. Among the Explainable Artificial Intelligence (AI) methods, the hybrid LRP and AR approach provided the highest explainability. It yielded an average deletion score of 0.3008 and an insertion score of 0.8918, precisely highlighting critical image features for model predictions. In conclusion, integrating transformer-based models with hybrid explainability methods significantly enhances diagnostic transparency. These advancements foster clinician trust and lay a strong foundation for reliable clinical decision support systems.
Assessment of visual performance and colour vision awareness among graphic designers in Ghana
Sex-specific CT-derived reference cutoffs for body composition in healthy Brazilian adults: a multicenter study
In silico design of novel CTL based multi epitope vaccine for esophageal cancer using immunoinformatics and molecular docking
Abstract Esophageal cancer is an aggressive malignancy with high morbidity, mortality, and limited durable treatment options due to tumor heterogeneity, immune evasion, and recurrence. This study addresses these challenges by computationally designing a novel CTL-based multi-epitope vaccine using experimentally validated epitopes from cancer-testis antigens (NY-ESO-1 and MAGE-A family), which are overexpressed in esophageal squamous cell carcinoma. To the best of our knowledge, this represents one of the most comprehensive in silico investigations for esophageal cancer, uniquely integrating experimentally validated epitopes with advanced immunoinformatics, high-resolution structural modeling, molecular dynamics, and immune simulation strategies. Nine experimentally validated CTL epitopes were retrieved from IEDB and rigorously evaluated for antigenicity (VaxiJen), toxicity (ToxinPred), allergenicity (AllerTOP), and IFN-γ induction (IFNepitope). A 253-amino-acid multi-epitope construct was assembled with AAY/EAAAK linkers, PADRE adjuvant, and 5 S rRNA-derived TLR4 agonist. Physicochemical properties were assessed (ProtParam, SOLpro); secondary/tertiary structures predicted (SOPMA, trRosetta); and validated (ProSA, Ramachandran). B-cell epitopes were predicted with ElliPro. Molecular docking (ClusPro) with TLR4, 100-ns MD simulations (GROMACS), and MM/GBSA binding free energy calculations were performed. Immune responses were simulated using C-ImmSim, and population coverage was analyzed via IEDB. The vaccine construct demonstrated excellent stability (instability index 31.16), solubility (0.577), and antigenicity (VaxiJen 0.5734; non-allergenic). It exhibited a predominantly α-helical structure (64.43%) with high model quality (ProSA Z-score: − 6.33). Strong TLR4 binding was confirmed (–910.7 kJ/mol, stable RMSD ~ 0.29 nm, MM/GBSA − 110.76 kcal/mol). Immune simulations predicted robust IgG/IgM responses, memory cell formation, and elevated IFN-γ (> 4 × 10⁵ ng/mL). Global population coverage reached 50.02%. This novel CTL-based multi-epitope vaccine candidate is stable, immunogenic, and capable of eliciting strong anti-tumor immunity. It provides a promising computational platform for esophageal cancer immunotherapy, warranting experimental validation and clinical translation.
Optical cooling by interfacial charge transfer in 2D heterostructures
Pulmonary carcinogenic effects of subchronic inhalation exposure with long-term follow-up to polyhexamethylene guanidine phosphate in rats
The role of type VI secretion system in resistance and pathogenicity of Acinetobacter baumannii
Synthesis, characterization, and catalytic performance of cobalt and nickel-substituted polyoxometalates organic-inorganic nanohybrids
Green synthesis of copper nanoparticles using Satureja khuzestanica plant and investigation of its antifungal properties: Candida albicans and Candida tropicalis, an in vitro study
Optimal control strategies and parameter estimation with a time delay dengue model using Penang Hospital data
Exploration of the efficacy and multivariate analysis of 5G remote rehabilitation intervention based on peer education model for patients after coronary intervention
Abstract This study aims to investigate the effects of a peer education-based model utilizing 5G remote rehabilitation guidance with wearable smart devices on patients with coronary heart disease undergoing percutaneous coronary intervention (PCI), along with the influence of various cross-factors. A total of 174 patients who underwent PCI between July 2024 and July 2025 were randomly assigned to a control group (n = 87) and a 5G group (n = 87), both receiving 12 months of follow-up. The control group received phase I and II cardiac rehabilitation, personalized exercise plans, and routine follow-up. In addition to this, the 5G group received remote rehabilitation guided by wearable devices. Clinical indicators, cardiopulmonary exercise capacity, psychological status, and the impact of different variables on the risk of adverse cardiovascular events were compared between the two groups. Overall adherence in this study was 87.88% from baseline to the end of the 12-month follow-up. Thecontrol group showed improvements in both LDL-C and LVEF levels post-intervention (P K 0.05). Furthermore, patients receiving 5G intervention demonstrated significant improvements in TC andLVEF ( P < 0.01). Changes in VO2 peak and METs were also significantly greater in the 5G groupcompared to the control group (VO2 peak: d = 0.61, P < 0.001; METs: d = 0.78, P < 0.001). Additionally, the improvement in VO2AT after 5G intervention was significantly superior to that ofconventional intervention (d = 0.22, P = 0.035). Both groups exhibited a significant decrease inGAD-7 scores post-intervention (control group: A = -2.69, P < 0.001; 5G group: A = − 2.99,P K 0.001), with the 5G group showing a greater degree of GAD-7 improvement. For PSQl, the controlgroup showed no significant change post-intervention (A = − 0.96, P = 0.176), while the 5G groupexhibited a significant reduction in PSQl scores (A = − 3.58, P < 0.001). The 5G group also revealedassociations between age, urban resident basic medical insurance, and cardiac function classificationwith the incidence of adverse events ( P < 0.01). Negative binomial regression analysis indicated thatyounger patients and those with better cardiac function had a lower risk of adverse events, and thisprotective effect was more pronounced in the 5G intervention group. Low body weight significantlyincreased the risk of adverse events, and male sex in the 5G intervention group, male gender and smoking were significantly associated with the occurrence of adverse events ( P < 0.05). The 5G remote personalized exercise rehabilitation intervention based on peer education effectively improves cardiopulmonary function and quality of life in patients post-PCI and helps prevent adverse events. This study provides a theoretical basis for the rehabilitation intervention and management of coronary heart disease patients after PCI.