Search Results (973)

Objectives: Prediabetes is characterized by elevated blood glucose levels associated with insulin resistance, increasing the risk of progression to type 2 diabetes mellitus (T2DM) and cardiovascular disease. High-intensity interval training (HIIT) has emerged as an effective non-pharmacological strategy to improve insulin sensitivity and cardiorespiratory fitness. This study aimed to analyze the effects of HIIT alone or combined with a hypocaloric diet on metabolic and cardiorespiratory parameters in individuals with prediabetes. Methods: A controlled, longitudinal, single-blind intervention study enrolled 68 adults with prediabetes (mean age 42.22–46.60 years; 73.5% women) and randomized them to HIIT plus hypocaloric diet (n = 23), HIIT only (n = 23), or hypocaloric diet only (n = 22) for 13 weeks, with pre/post assessments of glucose, VO₂max, blood pressure, FINDRISC. Results: Significant post-intervention differences were observed among groups in body mass index (p = 0.049), VO₂max (p < 0.001), fasting glucose (p < 0.001), systolic blood pressure (p < 0.001), and diabetes risk (p = 0.038), with the greatest improvements consistently observed in Group A. In Group A, fasting glucose decreased from 111.94 to 91.28 mg/dL (−20.66 mg/dL; −18.5%), VO₂max increased from 21.27 to 24.02 mL·kg⁻¹·min⁻¹ (+2.75; +12.9%), and systolic blood pressure decreased from 163.56 to 150.13 mmHg (−13.43 mmHg; −8.2%). No significant between-group differences were found for body weight (p = 0.271) or waist circumference (p = 0.174). Conclusions: HIIT combined with a hypocaloric diet is an effective and safe strategy for managing prediabetes, producing superior improvements in cardiorespiratory fitness, glycemic control, and reduction in diabetes risk compared with either intervention alone. Full article

Phishing emails continue to evade conventional detection systems due to their increasingly sophisticated, multi-faceted social engineering tactics. To address the limitations of single-modality or rule-based approaches, we propose SAHF-PD, a novel phishing detection framework that integrates multi-modal feature extraction with semantic-aware hierarchical fusion, based on large language models (LLMs). Our method leverages modality-specialized large models, each guided by domain-specific prompts and constrained to a standardized output schema, to extract structured feature representations from four complementary sources associated with each phishing email: email body text; open-source intelligence (OSINT) derived from the key embedded URL; screenshot of the landing page; and the corresponding HTML/JavaScript source code. This design mitigates the unstructured and stochastic nature of raw generative outputs, yielding consistent, interpretable, and machine-readable features. These features are then integrated through our Semantic-Aware Hierarchical Fusion (SAHF) mechanism, which organizes them into core, auxiliary, and weakly associated layers according to their semantic relevance to phishing intent. This layered architecture enables dynamic weighting and redundancy reduction based on semantic relevance, which in turn highlights the most discriminative signals across modalities and enhances model interpretability. We also introduce PhishMMF, a publicly released multimodal feature dataset for phishing detection, comprising 11,672 human-verified samples with meticulously extracted structured features from all four modalities. Experiments with eight diverse classifiers demonstrate that the SAHF-PD framework enables exceptional performance. For instance, XGBoost equipped with SAHF attains an AUC of 0.99927 and an F1-score of 0.98728, outperforming the same model using the original feature representation. Moreover, SAHF compresses the original 228-dimensional feature space into a compact 56-dimensional representation (a 75.4% reduction), reducing the average training time across all eight classifiers by 43.7% while maintaining comparable detection accuracy. Ablation studies confirm the unique contribution of each modality. Our work establishes a transparent, efficient, and high-performance foundation for next-generation anti-phishing systems. Full article

Background: Several studies have investigated the importance of physical exercise (PE) in overweight and obese populations; however, to date, no bibliometric study has analyzed research trends in high-intensity interval training (HIIT) in overweight and obese populations across the entire life course. Objective: To analyze the scientific output of HIIT trends in overweight and obese populations. Method: Theoretical study using bibliometrics as a research technique. A total of 282 studies were identified in the Web of Science and PubMed databases for analysis with VOSViewer software 1.6.20. The equation used was (“High-intensity interval training” OR HIIT) AND (overweight OR obesity OR “risk factors” OR “obesity risk”). Results: The year 2022 was the most productive year (n = 46). Most of the documents are research articles (81%), followed by review articles (15%). Most studies do not specify the characteristics of the sample, only mentioning the application of a HIIT program in overweight or obese individuals in (65.6%) of the total articles found. There is low scientific output in research focused on women (23.4%). The most frequently occurring words were “exercise” (n = 145), “obesity” (n = 131), “high-intensity interval training” (n = 81), “overweight” (n = 78), “physical activity” (n = 73), “body composition” (n = 46), “weight loss” (n = 45), “health” (n = 42), and “cardiorespiratory fitness” (n = 40). Conclusions: Scientific research has advanced the understanding of the impact of HIIT in relation to excess weight, with total fat reduction being one of the most frequently reported variables and no differences observed between sexes. HIIT has shown benefits in populations with overweight and obesity when compared with low-intensity training programs. Full article

Background: Bariatric surgery effectively treats severe obesity, but postoperative weight loss includes reductions in both fat mass (FM) and fat-free mass (FFM). Excessive FFM loss may increase the risk of sarcopenia, frailty, and long-term weight regain, yet its magnitude and determinants are not fully established. Methods: We conducted a retrospective analysis of a prospectively collected cohort of 179 patients who underwent laparoscopic or robotic Roux-en-Y gastric bypass between January 2020 and December 2022. Anthropometric parameters and body composition (bioelectrical impedance analysis) were measured preoperatively and at 6 and 12 months. The proportion of FFM loss relative to total weight loss (%FFML/WL) was calculated, and excessive FFM loss was defined using published cut-offs (≥25%, ≥30%, and ≥35%). Predictors of FFM preservation were assessed through stepwise regression. Results: Baseline BMI was 44.1 ± 4.6 kg/m², FM 54.6 ± 10.7 kg, and FFM 61.1 ± 11.9 kg. At 6 and 12 months, BMI decreased to 31.0 ± 4.2 and 28.8 ± 4.4 kg/m², respectively; FM decreased to 35.6 ± 11.0 and 22.0 ± 10.0 kg; and FFM to 54.7 ± 9.5 and 50.1 ± 7.0 kg (all p < 0.001). Most FFM loss occurred within the first 6 months (mean − 6.4 kg). Median %FFML/WL was 26.4% at 6 months and 28.7% at 12 months. Excessive FFM loss affected 41–46% of patients (≥25%), 27–31% (≥30%), and 14% (≥35%). In multivariable analysis, FFM at 6 months was the only independent predictor of FFM at 12 months (p < 0.001). Conclusions: Bariatric surgery leads to substantial FM and FFM reductions, with nearly half of patients exceeding established %FFML/WL alert thresholds. Early postoperative body composition monitoring may help identify individuals at higher risk of FFM depletion and guide preventive strategies such as adequate protein intake and resistance training. Full article

The study evaluates the effects of different types of popular exercises on muscle mass reduction during diet-induced body mass loss in overweight and obese women. Participants were randomly allocated to three exercises (Whole-Body Electromyostimulation (WB-EMS), Pilates, Yoga) combined with nutritional guidance and one nutritional guidance-only group (control). All exercise protocols specified a 2 × 50 min (Pilates, Yoga) or 2 × 20 min (WB-EMS) training, respectively. Weekly applied nutritional guidance focused on −500 kcal/d of energy restriction but increased protein intake. A total 221 overweight/obese women 19–65 years old and largely compliant with the exercise and nutritional guidance protocol were included. We observed significant decreases in body mass in all groups (−3.9 to 6.0 kg, all p < 0.001), with the most pronounced reduction in the nutritional guidance-only group. Apart from WB-EMS (−166 ± 799 g, p = 0.14), all the other groups significantly lost muscle mass (Pilates −343 ± 774 g, p = 0.003; Yoga: −507 ± 801 g, p < 0.001), however, compared to control (−1113 ± 881 g, p < 0.001), all the groups showed significantly more favorable results. WB-EMS, Pilates, and Yoga were associated with a reduced loss of muscle mass during diet-induced weight loss, indicating their potential role as adjunctive interventions in overweight and obese individuals. Full article

Background: In adult patients, rocuronium shows interindividual variability related to weight, sex, and age, but paediatric data are limited. This study aimed to evaluate clinical factors influencing the duration of action of rocuronium in children. Methods: Patients aged between 0 and 18 years undergoing planned general anaesthesia were eligible. The primary objective was to compare the duration of clinical action of rocuronium after a single dose, measured until the return of TOF (Train of Four) 1, across three-group age categories. Secondary objectives explored the relationship between TOF recovery and sex, weight, height, initial body temperature, as well as the occurrence of postoperative complications related to general anaesthesia. Results: Among 96 analysed patients, no clinically relevant association was found between the duration of rocuronium action and the studied clinical factors. TOF 1 occurred at 18.1 ± 9.5 min in those aged 1 to 5 years (n = 26), 16.8 ± 14.5 min in those aged 6 to 10 years (n = 33), and 18.2 ± 13.8 min in those aged 10 to 17 years (n = 37), p = 0.626. A post hoc analysis revealed high variability in recovery times across TOF levels, both in the per-protocol population (e.g., TOF 1: 17.7 ± 12.9 min) and in patients who did not receive sugammadex. Conclusions: In paediatric patients, the duration of rocuronium action after a single dose demonstrated substantial interindividual variability, which was not explained by age, sex, weight, height, or body temperature. Full article

Background/Objectives: In all types of diabetes, elevated blood glucose levels cause pathological changes in skeletal muscle, primarily due to oxidative stress, mitochondrial dysfunction, and excessive production of reactive oxygen species (ROS). Regular exercise can help mitigate these effects; however, the underlying mechanisms, particularly those involving the mitochondrial permeability transition pore (mPTP), remain incompletely understood. This study aimed to explore the effects of aerobic exercise training (AET) on oxidative stress and the expression of mPTP components in the skeletal muscle of streptozotocin-induced diabetic rats. Methods: Male Wistar rats were randomly divided into three groups: Healthy Sedentary (H-SED), Diabetic Sedentary (D-SED), and Diabetic Exercise-trained (D-EXER); n = 6 per group. The D-EXER group performed AET (0° slope) 5 days/week for 8 weeks. After the intervention period, body weight and fasting blood glucose (FBG) levels were measured, and soleus muscles were collected and analyzed for oxidative stress biomarkers, Western blotting, and gene expression using qRT-PCR. Results: Following an 8-week intervention, AET reduced FBG concentrations. Accordingly, in the soleus muscles of the D-EXER group, ROS levels decreased, and redox balance was improved compared to the D-SED group. Exercise training reduced CypD and Casp9 mRNA expression and increased Bcl-2 mRNA expression, whereas Ant1 mRNA expression was only slightly altered. CypD protein expression was decreased in exercised diabetic rats, while VDAC1 protein and mRNA levels remained unchanged. In the D-EXER group, there were significant inverse correlations between CypD and Casp9 mRNA expression levels and glutathione redox state. Conclusions: The current study suggests that 8 weeks of AET, in addition to reducing hyperglycemia, may favorably influence oxidative balance and the expression of mPTP-related molecular components in diabetic skeletal muscle. Full article

Background/Objective: This study aimed to develop and validate an automated deep learning-based model for 3D segmentation and quantification of the psoas major and gluteus muscles at 3T MRI in a large cohort study and to analyze the distribution of findings as well as gender-, age-, and BMI-related differences. Methods: The study population consisted of 27,805 participants from the MR imaging subgroup of the population-based, longitudinal German National Cohort study. A deep learning segmentation model was trained, tested, and implemented to automatically quantify psoas major maximum cross-sectional area (CSA_psoas) and gluteus volume (V_gluteus) on T1-weighted 3D VIBE DIXON sequences. Associations with gender, age, and BMI were assessed by linear regression. Results: The segmentation model demonstrated a high performance, with mean Dice coefficients of 0.92 for the psoas and 0.95 for the gluteus. Males showed higher total CSA_psoas (males: 37.92 ± 5.80 cm²; females: 24.47 ± 3.65 cm²) and higher total V_gluteus (males: 3.384 ± 0.528 L; females: 2.386 ± 0.408 L) compared to females. Younger participants aged <30 years showed the highest CSA_psoas, whereas participants aged 30–59 years showed the highest V_gluteus. Participants with higher BMI > 25 kg/m² showed higher muscle CSA and volumes compared to subjects with lower BMI < 25 kg/m². V_gluteus showed a strong correlation to body weight in both females and males. Conclusions: Deep learning-based models provide accurate 3D segmentation and quantification of skeletal muscle compartments from MR images in large cohort studies, thus offering a feasible method for skeletal muscle evaluation. The morphometric size characteristics of the psoas and gluteus muscles are dependent on gender and BMI. Deep learning enables accurate 3D segmentation and quantification of skeletal muscle in large MR imaging cohorts, providing a feasible tool for muscle evaluation. The morphometric characteristics of psoas and gluteus muscles are dependent on gender and BMI. Full article

Purpose: This single-athlete, longitudinal observational study describes training intensity distribution (TID) across two Olympic preparation cycles (Rio 2016 vs. Tokyo 2021) and explores whether differences in high-intensity exposure coincided with performance outcomes. Methods: An elite male 50 m freestyle specialist (personal best 21.27 s; height: 187 cm, weight: 80 kg, body mass index: 22.9 kg·m⁻², fat-free mass: 75.2 kg, and fat mass: 4.8 kg) was monitored across four mesocycle periods. TID is expressed as % of total swim volume in three zones: Z1 (low intensity), Z2 (threshold), Z3 [high intensity/race-pace, including High Intensity Interval Training (HIIT) and Sprint Interval Training (SIT)]. Both the coach and swimmer signed a written informed consent for the use of their data. Results: For Rio 2016, TID (Z1/Z2/Z3) was as follows: General 80/0/20, Specific 60/0/40, Pre-competition 40/30/30, and Taper 50/20/30, indicating a polarized approach. For Tokyo 2021, TID shifted to: General 85/0/15, Specific 60/0/40, Pre-competition 30/30/40, and Taper 40/20/40. Discussion: In this single athlete, a greater proportion of work in Z3 during the Tokyo cycle, particularly in the Pre-competition and Taper phases, probably coincided with improved performance (21.57 vs. 21.79 s). Conclusions: Although clear causal inference is not possible, these observations depict the probability that sprint-swim preparation for 50 m events needs a training volume oriented to Z3 and relatively less in Z1. However, the study’s design, the methods by which the TID was recorded, etc., limit any generalization about the interpretation of the findings. Therefore, future studies should address these limitations, providing more insights into improving the training on that kind of events. Full article

Background/Objectives: Incretin-based medications have transformed obesity management by enabling substantial body weight reduction. However, the rapid and pronounced loss of body mass necessitates a comprehensive, multidisciplinary approach incorporating nutritional and physical activity strategies to preserve lean mass, optimize functional outcomes, and prevent long-term complications. This narrative review provides a critical overview of this emerging clinical concern, which is expected to gain increasing relevance in the coming years. Methods: A literature review was conducted up to 31 October 2025, focusing on studies addressing nutritional, physical activity, and adjunctive interventions in adults with obesity treated with incretin-based medications. Results: Incretin-based agents induce significant weight loss, comparable to bariatric surgery, predominantly targeting adipose tissue. Nevertheless, these medications also cause rapid reductions in muscle and bone mass, often accompanied by nutrient deficiencies, which may compromise metabolic health and physical function. Tailored nutritional strategies—including hypocaloric diets enriched in protein and fiber, as well as amino acid, vitamin, and mineral supplementation—are critical to preserve lean mass and support sustained weight maintenance. Concurrently, structured, supervised physical activity, encompassing aerobics, resistance, and strength training, mitigates muscle loss and enhances functional capacity. Emerging pharmacological agents designed to promote adipose tissue reduction while preserving lean mass, as well as interventions targeting gut microbiota modulation, may represent promising adjunctive strategies to optimize long-term outcomes further. Conclusions: While incretin-based medications produce substantial weight loss, their impact on lean mass underscores the necessity of integrating personalized nutrition, supplementation, and structured exercise to preserve muscle, prevent malnutrition, and optimize long-term health and obesity outcomes. Full article

Background and Objective: Streetlifting is a developing strength sport derived from calisthenics and based on maximal external load performance in weighted pull-ups, dips, muscle-ups, and squat variations. Its rapid global expansion has raised interest in identifying sport-specific nutritional and recovery strategies that can support performance and health. However, scientific evidence directly focused on streetlifting remains limited. This narrative review aims to summarize current knowledge regarding body composition, nutrition, supplementation, and sleep in streetlifting athletes by integrating findings from related strength sports. Methods: A narrative review design was adopted due to the scarcity of empirical studies on streetlifting. Searches were performed using the terms “streetlifting AND nutrition,” “streetlifting AND body composition,” and “streetlifting AND sleep quality.” Peer-reviewed studies involving comparable strength disciplines were included when directly applicable to performance or recovery determinants. Results: Performance in streetlifting appears strongly driven by strength-to-bodyweight ratio, supported by low-to-moderate fat mass and adequate lean mass. Evidence from resistance training literature suggests that meeting energy requirements, consuming 1.2–1.5 g/kg/day of protein, and using nutrient timing around training may enhance muscle protein synthesis and glycogen replenishment. Creatine supplementation shows consistent benefits for maximal strength and ATP turnover, whereas other supplements lack robust evidence. Sleep duration and quality contribute to neuromuscular recovery, endocrine balance, and cognitive readiness, though sport-specific findings are insufficient. Conclusions: Streetlifting athletes may benefit from integrated nutritional planning, evidence-based supplementation, and sleep optimization. Further sport-specific interventional and longitudinal studies are required to develop validated performance and health guidelines. Full article

Background/Objectives: Metabolic dysfunction-associated steatotic liver disease (MASLD) often requires caloric restriction (CR) to reduce hepatic fat, but CR can compromise muscle mass and function. Resistance training and whey protein are anabolic stimuli, yet their independent and combined effects under substantial CR are unclear. Methods: In a 4-week randomized, double-blind trial, adults with MASLD (n = 45) under ~30% CR were allocated to four groups: resistance training with whey protein supplementation (E-PRO), resistance training with placebo (E-PLA), whey protein supplementation only (PRO), or placebo only (PLA). PRO groups consumed 1.5 g·kg⁻¹·day⁻¹ protein, while PLA groups consumed 0.8 g·kg⁻¹·day⁻¹. Exercise groups performed supervised exercise 5 days/week. Outcomes included body composition and isokinetic muscle function. Results: Across ~30% CR, all groups reduced body weight and fat mass without skeletal muscle mass loss; no between-group differences in body composition changes were observed. For peak torque, E-PRO improved across all regions except trunk, E-PLA improved except non-dominant shoulder flexors and trunk flexors, PRO improved non-dominant knee flexors and shoulder extensors, and PLA showed no change. For total work, E-PRO and E-PLA increased across all regions PRO improved dominant knee extensors/flexors and shoulder extensors; PLA increased only non-dominant knee extensors. E-PRO and E-PLA exceeded PLA for multiple knee/shoulder/trunk outcomes. Conclusions: In individuals with MASLD undergoing severe CR, ≥0.8 g·kg⁻¹·day⁻¹ of protein preserves skeletal muscle mass. However, the anabolic synergy of resistance training and protein for functional adaptation appears to be blunted by the substantial energy deficit. Full article

Exercise training reduces metabolic dysfunction and improves neural function; however, its cortical molecular effects in diabetic–obese conditions remain unclear. Here, we aimed to identify transcriptional pathways by integrating physiological evaluation with an in silico analysis of cortical RNA-seq data from Zucker Fatty Diabetes Mellitus rats following a 12-week swimming training program. Exercise training reduced body weight and improved glucose control and blood pressure. RNA-seq analysis revealed 814 differentially expressed genes, with pathway enrichment highlighting glutamatergic synapse, retrograde endocannabinoid signaling, and oxytocin signaling pathways. These coordinated transcriptional shifts involved genes related to excitatory neurotransmission, neuromodulatory feedback, and calcium-dependent regulation. As hypothesis-generating models, these pathway-level patterns suggest that exercise training may modulate cortical signaling properties in diabetic–obese states and provide a conceptual framework for future mechanistic investigation. Full article

Background/Objectives: Overweight and obesity is a continuing health concern for preadolescent youth. We assessed associations between sleep timing and sleep duration and body mass index/body composition in Latine youth. Methods: Participants were 119 Latine youth (mean age 11.53 year; 58.8% girls) and their mothers living in the rural Midwestern U.S. Youth reported their average bedtime and waking time. Heights and weights for children and mothers were measured by trained research assistants and were used to calculate BMI scores (in mothers), as well as BMI percentiles and overweight status (in youth). Mothers completed surveys for demographic variables. Results: Youth who went to bed before 9:30 PM (mean bedtime) obtained more sleep than those with later bedtimes (9.73 h vs. 8.63 h, respectively, t(117) = 7.88, p < 0.001). Each extra hour of sleep duration was associated with a decreased risk of being overweight (OR = 0.53 for weeknight sleep, OR = 0.67 for weekend night sleep), and each hour later to bed was related to increased risk for being overweight (OR = 2.35 on weeknights, and OR = 1.66 on weekend nights). To replicate previous work, we broke the youth up into four sleep timing groups: early-to-bed and early-to-rise (EE), early-to-bed and late-to-rise (EL), late-to-bed and early-to-rise (LE), and late-to-bed and late-to-rise (LL). Youth with LL sleep patterns on weeknights were much more likely to be overweight compared to youth with EE patterns (OR = 4.94). On weekend nights, compared to EE weekend youth, LE and LL weekend youth were more likely to be overweight (OR = 3.45 and OR = 3.32, respectively). Wake times were not significantly related to overweight risk. Conclusions: Sleep timing patterns, especially sleep duration and earlier bedtimes, may be important to address in future research on obesity interventions. Findings suggest that earlier bedtimes may play an important and complimentary role in health, in addition to sleep duration alone, and this study highlights the need for more research in underserved, minoritized populations. Full article

Accurate estimation of live weight is essential for efficient management and precision control in poultry production. This study evaluated the potential of supervised machine learning (ML) algorithms and digital image analysis for non-invasive prediction of live weight in Anadolu-T broilers, a locally developed genotype in Türkiye. A total of 4200 records were collected from 100 broilers (50 males and 50 females) over 42 days, including daily measurements of back length, back width, and live weight. Five ML algorithms—Random Forest (RF), k-Nearest Neighbors (KNN), Support Vector Regression (SVR), Extreme Gradient Boosting (XGB), and Multiple Linear Regression (MLR)—were trained and validated to estimate live weight based on morphometric traits. Among all algorithms, KNN achieved the highest accuracy (R² = 0.982, RMSE = 111.509 g, MAPE = 8.205%), followed by RF and XGB, which also produced stable and reliable predictions. The image-based models using log-transformed regression between body surface pixel area and live weight yielded similar accuracy (R² = 0.989, RMSE = 101.197 g, MAPE = 7.266%), confirming that projected surface area can effectively represent growth progression. The results demonstrate that integrating ML algorithms with digital imaging offers a practical, cost-effective, and non-invasive approach for real-time broiler weight estimation. This approach supports the advancement of precision poultry farming through automated, data-driven growth monitoring. Full article