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Acute physiological and pupillary responses during power snatch and clean & jerk training sessions in elite female weightlifters
Abstract Individual training programs are essential for healthy weightlifting. To investigate the adaptive response of vital functions and pupil diameter to olympic style weightlifting training performed in elite female weightlifters. The study was conducted with twenty elite female weightlifters in the preparation period for competitions. Weightlifters were given 90-minute training sessions with 75% and 100% maximum weight loaded on two different days. Systolic and diastolic blood pressure, oxygen saturation, pulse, respiratory rate, body temperature, and mean pupil diameter values, were measured during the rest, power snatch, clean & jerk movement and cool down phases of 75% and 100% maximum weight loaded training. Shapiro Wilk test, Friedman’s two-way analysis and Sperman correlation used for statistical analyses ( P < 0.05). All vital values were significantly different in at least one measurement time from the other measurement times in groups ( p ≤ 0.001). In the power snatch phase, all the vital signs were different from the rest and cool down phases in both training groups ( p < 0.001, respectively). In 100% maximum weight training group, there was a significant positive correlation between max clean & jerk and systolic blood pressure of basal ( r = 0.37), power snatch phase ( r = 0.27) and cool down phase ( r = 0.44). It can be said that different maximum weight power snatch and clean & jerk weightlifting trainings affect vital functions and mean pupil diameter changes and weightlifting performance within physiological limits, in weightlifters, and this may be a reference in arranging a training program. Continuous monitoring of athletes’ training-induced autonomic outcomes may contribute to individual arrangements for safe sports and high performance.
Modified protein selection strategy based on Escherichia coli’s Hitchhiker transport and validation through selection of nanobodies targeting bovine interferon gamma
Spatial joint modelling of multivariate longitudinal outcomes and cure proportion using latent Gaussian model with application to dataset on HIV/AIDS patients
HIV heart inflammation is mediated by HIV infected myeloid cells, HIV-tat secretion, and aberrant function of Connexin43-containing channels
Dual coordinate attention (DCA) network for accurate cerebral vascular endothelium segmentation in OCT images
Assessing the impact of groundwater abstraction and concrete dam fractures on saltwater intrusion using numerical modeling and interpretable machine learning
Awareness and knowledge of obstetricians about prenatal findings of inherited metabolic disorders
Correction: Engineering dielectric properties and charge transport in PANI/CuO nanocomposites via microstructural control
Comprehensive enhancement of blasting performance and dust suppression in open-pit mines using a modified mudstone–fly ash geopolymer stemming material
Scope of the grain biofortification in relation to food security
An ensemble hybrid and explainable AI (XAI) framework for zero false-positive islanding detection in distribution networks
Association of COVID-19 vaccines and antibody response in individuals with prior Coronavirus infection
Abstract Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) was one of the worst pandemics and viral infections affecting humans across the globe. Many non-pharmaceutical and pharmacological interventions were initiated to prevent the spread of infection and control the disease transmission. Covishield and Covaxin were among the most common vaccines given in India to control the spread of the coronavirus and its variants among the public. To evaluate the efficacy of COVID-19 vaccines in increasing serum and salivary IgA antibody levels and how they are correlated to patients’ demographics, medical conditions, and previous history of coronavirus infection in the Udupi district, Karnataka, India. 127 participants who received two doses of the COVID-19 vaccine were recruited. Anti-SARS-CoV-2 IgA antibodies specific to COVID-19 in serum and saliva were measured by ELISA. The mean serum IgA levels were compared at 0–6 months, 6–12 months, and > 12 months. The IgA levels were compared with age, gender, history of COVID-19 infection, timing of vaccination, body mass index, and comorbidities. The mean serum IgA levels in individuals with a history of COVID-19 (12.59 ± 5.67 μg/ml) were higher than those without a history of infection (8.5 ± 7.20 μg/ml). Among those with a history of COVID-19 infection, 8.1% were infected before the vaccination, and 91.9% were infected post-vaccination. Serum IgA levels were lower in participants under 30 years of age (5.27 ± 3.14 μg/mL) compared to participants above 30 years of age (8.93 ± 4.56 μg/mL) (P = 0.001). Antibody levels were influenced by age, presence of comorbidities, and history of coronavirus infection. Individuals with prior COVID-19 infection showed higher serum IgA antibody levels. Serum and salivary IgA levels were even detected in a group of participants with more than 12 months post-vaccination period.
Water hazard prevention technology for confined mining beneath dual extremely thin aquicludes in roof and floor
Long-term associations between animal-source food consumption and breast and prostate cancer incidence based on cointegration and ARIMAX models
A multi-step short-term photovoltaic power prediction model based on an improved whale migration algorithm
Seismological analysis of the tectonic evolution of the Laji Shan fault from the 2023 Jishishan MS 6.2 earthquake
Effect of biopolymer and plant fiber on soil-water characteristics of sandy soil
Deep optimization-guided hybrid neural network for accurate detection and segmentation of white matter hyperintensities in clinical MRI images
Abstract White matter hyperintensities (WMHs) are common radiological findings in brain magnetic resonance imaging (MRI) and are strongly associated with neurological disorders such as stroke, dementia, and multiple sclerosis. Accurate detection and segmentation of WMHs are crucial for early diagnosis, disease progression analysis, and treatment planning. However, manual delineation of WMHs is labour-intensive, time-consuming, and prone to inter-observer variability, which limits its practicality in large-scale clinical and research settings. Deep learning has shown promise in automating WMH analysis; however, challenges remain due to heterogeneous lesion sizes, low contrast boundaries, and imaging noise. We propose a Deep Optimization-Guided Hybrid Neural Network (DOGHNN) that combines Inception-v3, ResNet-50, and Practical Swarm Optimization (PSO) for enhanced WMH segmentation. Inception-v3 is employed to capture multi-scale lesion features, enabling the detection of both small punctate and large confluent WMHs. ResNet-50 is integrated to extract deep contextual representations, leveraging residual learning to distinguish true lesions from surrounding tissue and artifacts. Finally, PSO is incorporated as an optimization strategy to iteratively refine fusion weights, segmentation thresholds, and key parameters, minimizing segmentation loss and improving boundary delineation. This hybrid approach ensures both fine-grained lesion sensitivity and robust global feature learning. The DOGHNN framework was evaluated on benchmark WMH MRI datasets with diverse lesion loads and anatomical complexities. Comparative experiments showed superior performance over baseline deep learning models. Quantitative evaluation yielded a maximum precision of 93.2%, recall of 91.5%, dice score 91.1%, and f1-score of 90.5% were achieved by the suggested DOGHNN, and Hausdorff distance of 6.5, confirming its robustness and reliability. By combining multi-scale learning, residual contextual modelling, and optimization-driven refinement, the DOGHNN framework delivers accurate and efficient WMH segmentation. This approach holds strong potential for clinical integration, supporting automated neuroimaging workflows and improving diagnostic decision-making in neurological care.
Integrated UPLC, bioinformatics, and in vitro analyses reveal Yiqihuoxue decoction (GSC) alleviates vascular aging by promoting autophagy
Abstract Vascular aging constitutes a predominant risk factor for cardiovascular pathologies. Traditional Chinese Medicine (TCM) employs various formulations to mitigate age-related vascular dysfunction, among which Yiqihuoxue decoction (GSC) is clinically utilized for managing cardiovascular conditions in elderly patients. Our prior work demonstrated GSC’ s capacity to delay vascular aging in mice models and attenuate senescence in vascular endothelial cells, though its mechanistic basis remained unresolved. To address this, we conducted multi investigation combining Ultra-Performance Liquid Chromatography (UPLC), network pharmacology, and molecular dynamics (MD) simulations. UPLC identified 130 bioactive compounds in GSC, while integrative analyses (mass spectrometry, literature mining, and target prediction) revealed 792 putative targets. Intersection with 2,539 vascular aging-associated targets yielded 422 shared candidates, suggesting GSC’ s polypharmacological potential. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses highlighted autophagy-related pathways, notably PI3K/Akt and SIRT1 signaling. Cellular validation experiments in senescent human umbilical vein endothelial cells (HUVECs) demonstrated that GSC restored cell morphology and reduced SA-β-gal activity ( p < 0.05). GSC alleviated G0/G1 phase cell cycle arrest, restored mitochondrial membrane potential, and suppressed ROS accumulation. Autophagy profiling indicated that GSC promoted autophagic flux, as evidenced by increased LC3B puncta formation in immunofluorescence assays and autophagosome accumulation observed via transmission electron microscopy. Mechanistically, GSC exerted anti-senescence effects via coordinated regulation of the SIRT1-autophagy axis and PI3K/AKT pathway inhibition. Western blotting confirmed dose-dependent upregulation of SIRT1 and downregulation of p-PI3K/p-AKT ( p < 0.05), consistent with network pharmacology predictions. This study established GSC as a multi-component, multi-target intervention against vascular aging, with autophagy modulation serving as a central mechanism. These findings will provide a theoretical foundation for developing GSC-based therapies targeting age-related cardiovascular diseases.