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Correction: Miniaturized scalable arrayed CRISPR screening in primary cells enables discovery at the single donor resolution
An integrated renewable energy and machine learning framework for techno economic analysis of water and energy nexus management in arid climates
An intelligent community-based system for healthcare prioritisation
Morphological and molecular identification of endophytic fungi from roots of epiphyte orchid Aerides odorata Lour in Sabah
Biologically inspired neural network layer with homeostatic regulation and adaptive repair mechanisms
Integrated zooplankton and heavy metal analysis as indicators of pollution threats in freshwater ecosystems of West Bengal
Impact of tongue fat volume on obstructive sleep apnea in non-obese patients
Abstract Evidence suggests excess head and neck adipose tissue contributes to OSA, particularly in obese patients. Surgical treatments are often ineffective in this subset of the population. We sought to investigate the role of tongue fat in the normal and overweight populations. In this prospective cohort study, patients underwent overnight polysomnography and MRI using a Dixon sequence. Volumetric reconstruction evaluated the size and distribution of tongue fat deposits in subjects with and without sleep apnea. The study included 86 patients; mean age of 42.2 (SD 11.2) years, 16% female. Average BMI 27.5 kg/m 2 (SD 2.9), with 18.6% ( n = 16) normal BMI, 61.6% ( n = 53) overweight, 19.8% ( n = 17) obese. Logistic regression lines showed positive associations for BMI and age with AHI. No significant correlation was found between tongue fat volume or fraction and increased AHI nor presence of OSA. Although tongue volume and fat fraction were higher in patients with AHI ≥ 5 events per hour, the difference was not statistically significant. This study suggests that tongue fat does not play a significant role in the pathophysiology of OSA in the non-obese (BMI < 30) patient population. Therefore, selective treatments targeting tongue fat should focus on obese and morbidly obese patients.
Adiponectin receptor agonist, AdipoRon, restores hepatic clock gene expression in PCOS-associated NAFLD
Classical and quantum approaches to probabilistic modeling of fire occurrence in anthracite grade coal
Effects of resistance training and aerobic training on improving the composition of middle-aged adults with obesity in an interventional study
Abstract This study investigated the effectiveness of a resistance and aerobic training model among 71 middle-aged participants aged 30–60 (mean age 44.27 ± 8.67 years; mean BMI 27.94 ± 3.92 kg/m²) with obesity, comprising 36 males and 35 females (male/female ratio ≈ 1.03:1). Participants were categorized into four groups based on their self-reported training regimens: dietary-only (Group C), aerobic fat oxidation (Group F), high-intensity interval training (Group H), and resistance training (Group R). Subjects followed their specialized routines through online and offline sources for at least 12 weeks. Groups F, H, and R demonstrated statistically lower body weight as well as waist-to-hip ratio and body fat percent levels, when assessed against Group C (P < 0.01). The combination of resistance training with specific benefits produced larger reductions in waist-to-hip ratio, together with android fat mass, primarily observed among male participants (P < 0.01). The participants in Group H demonstrated the greatest decrease in body fat percentage among female subjects (P < 0.01), even though Group R participants achieved beneficial results, although their adherence level was less than ideal. Participants from all experimental groups maintained similar levels of muscle mass. The hybrid online and offline approach effectively enhanced adherence and engagement, demonstrating its scalability and potential for managing obesity.
Intelligent pear variety classification models based on Bayesian optimization for deep learning and its interpretability analysis
Integrated pore structure analysis and methane adsorption and desorption investigation in deep multi seam coal systems
Nationwide longitudinal analysis of COVID-19 hospitalisation burden in immunocompromised patients
Communal music as a tool to improve positive affect after social ostracism or negative autobiographical memory recollection
The impact of relative deprivation on mental health among middle-aged and older adults in China: a multiple chain mediation model
Abstract This study, grounded in the theoretical frameworks of social comparison and institutional trust, employs a multiple mediation model to elucidate the mediating mechanisms of social justice and social trust in the relationship between relative deprivation and mental health. Using data from 3777middle-aged and older adults in the Chinese General Social Survey, we conducted OLS regression and bootstrap analyses. The results demonstrate that relative deprivation among middle-aged and older adults not only is negatively correlated with mental health, but is also indirectly associated with mental health through two mediating variables: social justice and social trust. Furthermore, bootstrap analysis reveals a significant serial mediation pathway from relative deprivation through social justice to social trust, with an effect size of −0.002. These findings suggest that interventions targeting reduced relative deprivation, enhanced perceptions of social justice, and strengthened social trust may effectively improve mental health outcomes in this population.
Development of a deep learning model for survival prediction in heart failure: competing risk and frailty model
Dipole antenna incorporated with metasurface and cavity reflector for wideband circular polarisation and high gain
Comparison of lower body joint kinematics during change of direction tasks estimated using a markerless and a markerbased method
Abstract Marker-based (MB) motion capture systems face challenges like marker loss, soft tissue artifacts, and manual processing. Markerless (ML) motion capture systems might be particularly advantageous for capturing dynamic, non-linear movements like change of direction (COD) movements. The agreement between MB and ML systems for lower extremity joint kinematics during COD tasks was evaluated. Nineteen athletes performed cutting movements in 5 directions at 3 intensities. Data was captured using infrared and video cameras. Joint angles were computed, and the agreement was assessed using prediction band and extended Bland-Altman (BA) methods. Knee joint angles showed the smallest random and systematic errors (bias = 4.34°, area = 3102.57 deg·stance%; BA: bias = 3.34°, limits of agreement (LoA) = ± 11.38°) compared to ankle and hip joint angles. Flexion/extension angles displayed a smaller random error (area = 2919.74 deg·stance%; LoA = ± 10.71°) compared to ab-/adduction (area = 3477.70 deg·stance%; LoA ± 12.16°) and internal/external rotation angles (area = 4630.68 deg·stance%; LoA = ± 15.75°). Slower and straight-line movements demonstrated stronger agreement than sharper, non-linear directions. These findings provide valuable insight for researchers and practitioners when placing ML data in the context of existing data, with particular care when considering highly dynamic, non-linear movements or internal/external rotation angles.