Search Results (392)

Metabolic and bariatric surgery (MBS) is an effective treatment for severe obesity, though individual responses vary widely, partly due to genetic predisposition. This study investigates the association of a body mass index (BMI) polygenic score (PGS) with weight loss and metabolic outcomes following surgery. A cohort of 225 patients undergoing MBS was analyzed at baseline (T₀), six (T₆), and twelve (T₁₂) months, with anthropometric and biochemical parameters recorded at each time point. Total weight loss (TWL) and excess weight loss (EWL) percentages were calculated. PGS was computed using the LDpred-grid Bayesian method. The mean age was 45.9 ± 9.4 years. Males had a higher baseline prevalence of type 2 diabetes (T2D) and comorbidities (p < 0.001). Linear regression analysis confirmed an association between PGS and baseline BMI (p = 0.012). Moreover, mediation analysis revealed that baseline BMI mediated the effect of the PGS on %TWL at T₁₂, with an indirect effect (p-value = 0.018). In contrast, high-density lipoprotein-cholesterol (HDL-C) at T₆ and triglycerides (TG) at T₁₂ showed direct associations with the PGS (p-value = 0.004 and p-value = 0.08, respectively), with no significant mediation by BMI. This study showed a BMI-mediated association of PGS with %TWL and a direct association with lipid changes, suggesting its potential integration into personalized obesity treatment. Full article

Cold storage is widely used for the postharvest preservation of fruits and vegetables; however, okra, as a tropical vegetable, is susceptible to chilling injury under low-temperature storage conditions, leading to quality deterioration, reduced nutritional value, and significant economic losses. Nitric oxide (NO), as an important signaling molecule, plays a crucial role in the postharvest preservation of fruits and vegetables. To investigate the effects of different concentrations of nitric oxide on the postharvest quality of okra under cold storage, fresh okra pods were treated with sodium nitroprusside (SNP), a commonly used NO donor, at concentrations of 0 (control), 0.5 (T1), 1.0 (T2), 1.5 (T3), and 2.0 mmol·L⁻¹ (T4). The results showed that low-concentration NO treatment (T1) significantly reduced weight loss, improved texture attributes including hardness, springiness, chewiness, resilience, and cohesiveness, and suppressed the increase in adhesiveness. T1 treatment also effectively inhibited excessive accumulation of cellulose and lignin, thereby maintaining tissue palatability and structural integrity. Additionally, T1 significantly delayed chlorophyll degradation, preserved higher levels of soluble sugars and proteins, and enhanced the activities of key antioxidant enzymes, including superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT), contributing to improved oxidative stress resistance and membrane stability. In contrast, high-concentration NO treatments (T3 and T4) led to pronounced quality deterioration, characterized by accelerated membrane lipid peroxidation as evidenced by increased malondialdehyde (MDA) content and relative conductivity, and impaired antioxidant defense, resulting in rapid texture degradation, chlorophyll loss, nutrient depletion, and oxidative damage. These findings provide theoretical insights and practical guidance for the precise application of NO in extending shelf life and maintaining the postharvest quality of okra fruits. Full article

As power grids continue to expand in scale, the occurrence of cascading failures within them can lead to significant economic losses. Therefore, assessing the criticality of grid nodes is crucial for ensuring the secure and stable operation of power systems and for mitigating losses when cascading failures occur. The classical Local Link Similarity (LLS) algorithm in complex networks evaluates the importance of network nodes from a neighborhood topology perspective, but it suffers from issues such as the excessive weighting of node degrees and the neglect of electrical parameters. Based on the classical algorithm, this paper first develops the Improved Local Link Similarity (ILLS) algorithm by substituting alternative similarity metrics and comparatively evaluating their performance. Building upon the ILLS, we then propose the Electrical LLS (ELLS) algorithm by integrating node power flow and electrical coupling connectivity as multiplicative factors, with optimal combinations determined via simulation experiments. Compared to classical approaches, ELLS demonstrates superior adaptability to power grid contexts and delivers enhanced accuracy in power system node importance assessments. These algorithms are applied to rank the node importance in the IEEE 300-bus system. Their performance is evaluated using the loss-of-load-size metric, comparing ELLS, ILLS, and the classical algorithm. The results demonstrate that under the loss-of-load-size metric, the ELLS algorithm achieves approximately 25% higher accuracy compared to both the ILLS and the classical algorithm, validating its effectiveness. Full article

Tear film alterations are commonly associated with ocular pathology. The tear film plays a vital role in maintaining the optical properties of the cornea and contains essential elements required for healing and preserving the integrity of the ocular surface. As a biological fluid, the tear film is easily collected using non-invasive techniques, making it a promising candidate for analysis and often referred to as an ideal biofluid. Several studies have attempted to identify biomarkers in the tear film that could be linked to systemic or ocular disorders, with the goal of developing tools for diagnosis or even early prevention. The quality and quantity of the tear film are influenced by hormonal status, emotional experiences related to social and familial events, and the work environment. Systemic disorders are often reflected at the ocular level through alterations in the tear film. Obesity is a well-recognized public health concern, extensively studied and investigated, much like other common systemic conditions. The presence of low-grade, chronic inflammation associated with excess body weight has been validated in several studies. The strategies for preventing obesity induced dry eye disease are based on regular physical activity, maintaining adequate hydration through sufficient fluid intake, weight loss, and the supplementation of essential fatty acids. This narrative literature review aims to highlight the tear film alterations associated with obesity. The article is intended for ophthalmologists, general practitioners, nutritionists, and researchers. Full article

Background: The Fit-Model in bodybuilding is a relatively new category designed for women seeking a balanced physique, avoiding excessive muscularity and extreme leanness. This study examined the dietary strategies, body composition changes, and plasma leptin fluctuations of Fit-Model athletes during a seven-week pre-competition phase. Methods: Twelve females (age: 27.6 ± 4.4 years, body mass: 60.0 ± 6.2 kg) preparing for a national championship were monitored for energy and macronutrient intakes, total, lean, and fat mass, plasma leptin levels, and menstrual cycle characteristics. The five highest-ranked athletes were selected to compete at the world championship, allowing for comparisons between national and international athletes. Results: Low carbohydrate intake was reported, and total energy intake decreased from 1700 to 1520 kcal/day approaching the contest day. Athletes experienced an average body mass loss of 4.2 kg, with no clear relationship between final weight or fat mass and competitive success. Plasma leptin levels were markedly low during all 7 weeks of preparation with a further decline before the contest, but did not correlate with either changes in body composition and weight or energy or macronutrient intakes. Menstrual cycle disturbances were prevalent, with only two athletes maintaining regular cycles by the end of the preparation. Conclusions: Fit-Model athletes undergo a considerable decline in body weight and fat mass during the final weeks before the contest, yet these changes do not appear to be decisive for performance outcomes. Persistently low leptin levels and menstrual irregularities call for strategies that balance physique optimization with endocrine health to support both the performance and well-being of athletes. Full article

Deaths occur during the culture of sea bass, and if timely harvesting is not carried out, it will lead to water pollution and the continued spread of sea bass deaths. Therefore, it is necessary to promptly detect dead fish and take countermeasures. Existing object detection algorithms, when applied to the task of detecting dead sea bass, often suffer from excessive model complexity, high computational cost, and reduced accuracy in the presence of occlusion. To overcome these limitations, this study introduces YOLOv8n-Deadfish, a lightweight and high-precision detection model. First, the homemade sea bass death recognition dataset was expanded to enhance the generalization ability of the neural network. Second, the C2f-faster–EMA (efficient multi-scale attention) convolutional module was designed to replace the C2f module in the backbone network of YOLOv8n, reducing redundant calculations and memory access, thereby more effectively extracting spatial features. Then, a weighted bidirectional feature pyramid network (BiFPN) was introduced to achieve a more thorough integration of deep and shallow features. Finally, in order to compensate for the weak generalization and slow convergence of the CIoU loss function in detection tasks, the Inner-CIoU loss function was used to accelerate bounding box regression and further improve the detection performance of the model. The experimental results show that the YOLOv8n-Deadfish model has an accuracy, recall, and mean precision of 90.0%, 90.4%, and 93.6%, respectively, which is an improvement of 2.0, 1.4, and 1.3 percentage points, respectively, over the original base network YOLOv8n. The number of model parameters and GFLOPs were reduced by 23.3% and 18.5%, respectively, and the detection speed was improved from the original 304.5 FPS to 424.6 FPS. This method can provide a technical basis for the identification of dead sea bass in the process of intelligent aquaculture. Full article

Obesity is a global health crisis with profound implications for cancer risk, particularly within the gastrointestinal (GI) tract. Mounting evidence demonstrates that excess adiposity contributes to the initiation, progression, and poor outcomes of GI malignancies through a constellation of interrelated mechanisms. This review comprehensively examines the biologic pathways linking obesity to cancers of the esophagus, stomach, colon, liver, pancreas, and gallbladder. Chronic low-grade inflammation, driven by adipose tissue-derived cytokines and immune cell infiltration, plays a central role in tumorigenesis via the activation of NF-κB, STAT3, and other pro-oncogenic signaling cascades. Hyperinsulinemia and insulin resistance increase mitogenic IGF-1 signaling, while dysregulated adipokines, particularly elevated leptin and reduced adiponectin, promote cellular proliferation and impair tumor suppression. Dysbiosis of the gut microbiome and alterations in bile acid metabolism generate carcinogenic metabolites that contribute to DNA damage and immune evasion. Additionally, obesity-induced tissue hypoxia fosters tumor growth through HIF-1α-mediated pathways. We further highlight organ-specific associations, such as visceral adiposity’s role in Barrett’s esophagus and hepatocellular carcinoma emerging from metabolic dysfunction-associated steatotic liver disease (MASLD). Importantly, emerging data suggest that weight loss, achieved via lifestyle, pharmacologic, or surgical interventions, may mitigate these carcinogenic pathways and improve tumor biology. As obesity prevalence continues to rise globally, elucidating its mechanistic ties to GI malignancies is essential for risk stratification, prevention strategies, and personalized care. By integrating epidemiologic and molecular insights, this review underscores the need for multidisciplinary approaches to curb the oncogenic burden of obesity and improve outcomes in GI oncology. Full article

This paper addresses the challenges of sample scarcity and class imbalance in remote sensing image semantic segmentation by proposing a decoupled synthetic sample generation framework based on a latent diffusion model. The method consists of two stages. In the label generation stage, we fine-tune a pretrained latent diffusion model with LoRA to generate semantic label masks from textual descriptions. A novel proportion-aware loss function explicitly penalizes deviations from the desired class distribution in the generated mask. In the image generation stage, we use ControlNet to train a multi-condition image generation network that takes the synthesized mask, along with its text description, as input and produces a realistic remote sensing image. The base Stable Diffusion model’s weights remain frozen during this process, with the trainable ControlNet ensuring that outputs are structurally and semantically aligned with the input labels. This two-stage approach yields coherent image–mask pairs that are well-suited for training segmentation models. Experiments show that models trained on the synthetic samples produced by the proposed method achieve high visual quality and semantic consistency. The proportion-aware loss effectively mitigates the impact of minority classes, boosting segmentation performance on under-represented categories. Results also reveal that adding a suitable proportion of synthetic sample improves segmentation accuracy, whereas an excessive share can cause over-fitting or misclassification. Comparative tests across multiple models confirm the generality and robustness of the approach. Full article

Salmonella infection poses a serious threat to the poultry industry, causing significant economic losses. Under global warming conditions, the underlying molecular mechanisms by which heat stress affects bacterial infections in poultry remain unclear. This study conducted a Salmonella Typhimurium infection under heat stress in Guang Ming broilers. A total of 100 chickens were randomly divided into three groups: control group (CTL), Salmonella Typhimurium (ST) infection group, and heat stress and Salmonella Typhimurium (HS + ST) co-stimulation group. By integrating inflammatory phenotypes, liver transcriptome profiles, and weighted gene co-expression network analysis (WGCNA), we systematically investigated the key regulatory factors through which heat stress affects host susceptibility to Salmonella. The results demonstrated that heat stress reduced body weight gain, exacerbated Salmonella Typhimurium-induced inflammatory responses, and increased mortality. Transcriptome results revealed that heat stress led to excessive inflammatory responses and antioxidant defense imbalances. Combined differential expression analysis and WGCNA identified three hub regulatory genes: PTGDS and WISP2 showed significant correlations with the heterophil/lymphocyte ratio, while SLC6A9 was significantly correlated with serum IL-8 levels. Validation in HD11 cell infection models confirmed the differential expression of these genes under heat stress and Salmonella Typhimurium co-stimulation, indicating their critical roles in host immune regulation. This study elucidates the intrinsic regulatory relationships through which heat stress promotes Salmonella pathogenicity and inflammatory responses, providing important insights for disease-resistant poultry breeding and prevention strategies. Full article

Excessive bait wastage is a major issue in aquaculture, leading to higher farming costs, economic losses, and water pollution caused by bacterial growth from unremoved residual bait. To address this problem, we propose a bait residue detection and counting model named YOLOv8-BaitScan, based on an improved YOLO architecture. The key innovations are as follows: (1) By incorporating the channel prior convolutional attention (CPCA) into the final layer of the backbone, the model efficiently extracts spatial relationships and dynamically allocates weights across the channel and spatial dimensions. (2) The minimum points distance intersection over union (MPDIoU) loss function improves the model’s localization accuracy for bait bounding boxes. (3) The structure of the Neck network is optimized by adding a tiny-target detection layer, which improves the recall rate for small, distant bait targets and significantly reduces the miss rate. (4) We design the lightweight detection head named Detect-Efficient, incorporating the GhostConv and C2f-GDC module into the network to effectively reduce the overall number of parameters and computational cost of the model. The experimental results show that YOLOv8-BaitScan achieves strong performance across key metrics: The recall rate increased from 60.8% to 94.4%, mAP@50 rose from 80.1% to 97.1%, and the model’s number of parameters and computational load were reduced by 55.7% and 54.3%, respectively. The model significantly improves the accuracy and real-time detection capabilities for underwater bait and is more suitable for real-world aquaculture applications, providing technical support to achieve both economic and ecological benefits. Full article

In recent years, the continuous development of deep learning has significantly advanced its application in the field of remote sensing. However, the semantic segmentation of high-resolution remote sensing images remains challenging due to the presence of multi-scale objects and intricate spatial details, often leading to the loss of critical information during segmentation. To address this issue and enable fast and accurate segmentation of remote sensing images, we made improvements based on SegNet and named the enhanced model CSNet. CSNet is built upon the SegNet architecture and incorporates a coordinate attention (CA) mechanism, which enables the network to focus on salient features and capture global spatial information, thereby improving segmentation accuracy and facilitating the recovery of spatial structures. Furthermore, skip connections are introduced between the encoder and decoder to directly transfer low-level features to the decoder. This promotes the fusion of semantic information at different levels, enhances the recovery of fine-grained details, and optimizes the gradient flow during training, effectively mitigating the vanishing gradient problem and improving training efficiency. Additionally, a hybrid loss function combining weighted cross-entropy and Dice loss is employed. To address the issue of class imbalance, several categories within the dataset are merged, and samples with an excessively high proportion of background pixels are removed. These strategies significantly enhance the segmentation performance, particularly for small-sample classes. Experimental results from the Five-Billion-Pixels dataset demonstrate that, while introducing only a modest increase in parameters compared to SegNet, CSNet achieves superior segmentation performance in terms of overall classification accuracy, boundary delineation, and detail preservation, outperforming established methods such as U-Net, FCN, DeepLabv3+, SegNet, ViT, HRNe and BiFormert. Full article

Background: Bariatric surgery is an effective treatment for obesity, leading to significant weight loss and improvements in metabolic health. However, massive weight loss often results in excess skin, which can negatively impact body image, psychological well-being, and quality of life. Abdominoplasty is commonly performed after bariatric surgery to address these concerns. Our study aimed to evaluate the effects of post-bariatric abdominoplasty on psychological well-being, body image, social relationships, and sexual functioning in formerly obese patients. Methods: A single-center, cross-sectional recall study was conducted on 35 patients, out of 135 invited, who underwent sleeve gastrectomy followed by abdominoplasty 12–24 months after the initial surgery. Participants completed validated questionnaires assessing psychological well-being, depression, anxiety, self-esteem, body perception, social relationships, and sexual functioning. Pairwise comparisons were performed to assess changes across the preoperative, post-bariatric, and post-abdominoplasty stages. Results: Psychological well-being significantly improved post-bariatric surgery, with further reductions in anxiety and depressive symptoms after abdominoplasty. However, body shape perception and self-esteem improved after bariatric surgery but did not show additional enhancement following abdominoplasty. Social support remained largely unchanged, except for modest improvements in attachment and reliable alliance. Sexual functioning improved significantly after bariatric surgery but showed no further significant gains after abdominoplasty. Conclusions: While abdominoplasty is associated with additional psychological benefits, particularly in reducing anxiety and depressive symptoms, it does not significantly enhance body perception, self-esteem, or sexual functioning beyond the effects of bariatric surgery. These findings highlight the importance of setting realistic patient expectations regarding the benefits of body contouring surgery in post-bariatric care. Full article

Background: The global rise in obesity rates has led to an increase in bariatric procedures, resulting in more patients needing relief from excess skin through body contouring surgeries (BCS), such as abdominoplasty. Although these procedures are generally considered safe, they can be associated with notable perioperative complications, including increased Hb-loss (hemoglobin loss) and drainage fluid volumes. Thus, this study analyzed risk factors for prolonged fluid secretion after abdominoplasty. Methods: We retrospectively analyzed 505 body contouring procedures performed between January 2018 and December 2023 at the Department of Plastic Surgery at the University Clinic of St. Poelten. The investigation focused on postoperative Hb-loss, drainage fluid volumes and hemoglobin levels in patients, comparing those with and without prior bariatric surgery. Statistical analyses utilized the t-test for Equality of Means, while correlation analyses were conducted using Spearman Rho and the Mann–Whitney U test. Results: Bariatric patients demonstrated markedly reduced hemoglobin levels both preoperatively (13.24 g/dL) and postoperatively (10.68 g/dL) compared to their non-bariatric counterparts (14.02 g/dL preoperatively and 11.71 g/dL postoperatively; p < 0.001). The prevalence of anemia was likewise substantially higher in the bariatric cohort, rising from 14.52% preoperatively to 82.48% postoperatively, versus 6.25% and 61.25%, respectively, in the non-bariatric group (p = 0.001). Moreover, prior bariatric surgery was significantly associated with increased postoperative drainage volume (p = 0.009) and prolonged operative time (p = 0.002). Notably, extended hospital stays exhibited a strong correlation with postoperative anemia (p = 0.005). Conclusions: Collectively, our findings underscore the potential risk of increased hemoglobin loss at BCS after bariatric weight loss. Tailored hemoglobin management and nutritional strategies are essential to improve the outcomes and safety of post-bariatric BCS. Meticulous preoperative identification of hematological discrepancies and adequate patient preparation are imperative for positive postoperative patient safety. Full article

Rice (Oryza sativa L.) is a staple crop that provides essential nutrients and energy; however, it is sensitive to heat stress, posing a threat to sustainable productivity. Heat stress can cause delayed germination in progeny, increased oxidative stress, reduced biomass accumulation, and excessive water loss. Notably, heat stress memory induced through heat priming can be inherited, potentially strengthening heat tolerance in subsequent generations. This study examined the effects of heat priming and heat stress on delayed germination, shoot length, and shoot fresh and dry weight under elevated-temperature conditions. The results showed that while heat stress delayed germination in progeny, heat priming significantly accelerated germination rates. Furthermore, heat stress elevated oxidative stress levels, thereby hindering biomass synthesis. In contrast, heat priming helped maintain low levels of reactive oxygen species (ROS) and malondialdehyde (MDA), contributing to greater biomass accumulation. These findings suggest that heat priming enhances transgenerational heat tolerance in rice, leading to faster germination, higher biomass accumulation, and improved ROS homeostasis in progeny. Full article

Radix astragali is a homologous plant of medicine and food with a variety of health benefits. However, our previous study showed that blue mold, caused by Penicillium polonicum, is the most important postharvest disease of fresh R. astragali during storage. Ozone, as a strong oxidizing agent, can effectively control the occurrence of postharvest diseases in fruits and vegetables. Nevertheless, there are few research studies on the effect of ozone-treated fresh Chinese traditional medicine. In this study, we investigated the effect of ozone gas on the postharvest blue mold development, mycotoxin accumulation, and main active component contents in fresh R. astragali infected by P. polonicum, and analyzed the possible action mechanism on ROS metabolism. The result indicates that ozone application significantly inhibited the development of postharvest blue mold caused by P. polonicum infection, reduced the disease incidence, disease index, and weight loss rate, maintained the main active ingredients in fresh R. astragali by activating ROS metabolism, enhanced the antioxidant enzymatic activity, thus avoiding oxidative damage caused by excessive ROS accumulation, and maintained the integrity of the cell membrane, ultimately controlling the occurrence of blue mold of R. astragali. Moreover, ozone treatment also maintained the contents of the main active ingredients in R. astragali before 14 d during P. polonicum infection. In addition, the amount of active ingredients of astragaloside I, calycosin-7-glucoside, and ononin in the ozone-treated group was higher than that in the control group during the storage period. We speculate that, under the action of ozone, astragaloside IV was converted into astragaloside II by oxidative modification and astragaloside II was further oxidized to astragaloside I, resulting in the accumulation of astragaloside I. Similarity, the hydrogen atoms (-H) on the benzene ring in formononetin were oxidized to phenolic hydroxyl groups (-OH) to generate calycosin, which was further converted into calycosin-7-glucoside, resulting in calycosin-7-glucoside accumulation. This study will provide the theoretical basis for ozone commercial application to control the occurrence of postharvest diseases of R. astragali. Full article