Search Results (27,099)

In recent years, innovative edible vegetal products, obtained by harvesting in the early stages of plant development, have emerged for their potential as sources of nutraceuticals. Phytosterols, which play important structural and regulatory roles in plant growth and membrane remodeling, are included among vegetable-related nutraceuticals due to their beneficial effects on human health. For this reason, the present study was focused on the use of RPLC-APCI-HRMS to assess, for the first time, the free sterol (FS) profiles of two edible Brassicaceae plants, namely kale (Brassica oleracea var. acephala) and broccoli raab (Brassica rapa subsp. sylvestris var. esculenta), harvested at the stages of microgreens, microleaves and baby leaves. A comparison with the respective adult forms, conventionally used as edible products upon cooking, was also performed. β-sitosterol was the prevailing FS in all products (>75%), followed by campesterol (8–15%) and isofucosterol (<3%). Total FS concentrations ranged between 13 and 23 mg/100 g fresh weight (FW) for juvenile products of the two plants under study, with the respective highest values being comparable with those found in raw or cooked mature forms (24–26 mg/100 g FW). Interestingly, a more diversified FS profile was observed for juvenile products and an increase in major FS content was observed for microleaves of the two plants cultivated during the winter cycle (January–March), compared to those cultivated in the spring cycle (March–May). These results support the hypothesis that vegetables harvested at early developmental stages may represent promising ready-to-eat alternatives to Brassica plant adult forms, as well as sources of beneficial phytosterols. Full article

Unprovoked shark bites are one of the most recognised human–wildlife conflicts and present a significant concern for beach safety. Lethal methods of shark mitigation have previously been implemented to reduce the risk of such incidents; however, due to their destructive impacts on vulnerable marine wildlife, non-lethal approaches are increasingly preferred. In recent years, drones have emerged as an effective, minimally invasive tool for real-time shark surveillance in surf zones. Drones are also used to collect valuable data on shark ecology and behaviour in nearshore environments, which can inform evidence-based policies. This review examines the utility of drones for shark surveillance programs by identifying key operational parameters and associated challenges of drone-based methods. We investigate emerging technologies, including long-range drones, remotely operated or autonomous flight missions, and the use of artificial intelligence for shark detection and species identification. We also outline current drone licensing, laws, and regulations, noting that these vary across administrative regions (i.e., countries and states). Overall, this review provides insight into the expansion of drone-based shark surveillance in nearshore areas and its potential to enhance beach safety, support management decisions, and advance scientific knowledge without negatively impacting shark populations. Full article

Fire plays a central role in shaping regeneration dynamics in Pinus canariensis C. Sm. & DC. forests, yet the relative importance of different fire-related cues and post-fire environmental filters remains poorly understood. We experimentally evaluated the effects of drought, heat, smoke, ash and soil microbial extracts on the germination of seven co-occurring species representing the main functional groups of these forests. Germination responses varied markedly among species, revealing that no single cue dominates early recruitment. Drought emerged as the strongest and most consistent filter, sharply reducing germination success and slowing emergence in P. canariensis and Fabaceae, while Poaceae remained largely insensitive under the imposed water potentials. Ash enhanced germination in P. canariensis and Cynosurus echinatus L., indicating that nutrient-rich post-fire substrates can facilitate emergence when moisture is available. Soil and microbial extracts accelerated germination in fast-emerging grasses, providing the first experimental evidence that post-fire soil legacies influence recruitment in Macaronesian pine forests. In contrast, heat acted as a species-specific cue, with only limited stimulation at moderate temperatures and widespread declines under extreme heat, while the smoke treatment used in this study produced negligible effects across all species. Across treatments, germination timing emerged as a key functional axis, structuring regeneration niches, with rapid-germinating Poaceae favoured under increasing aridity. Our findings highlight the dominant role of hydric stress, the selective relevance of ash and soil legacies, and the functional divergence among species, offering new mechanistic insights into post-fire regeneration under current and future climate scenarios. Full article

Microplastics (MPs) are emerging environmental contaminants increasingly detected in foods, beverages, and food-contact materials, making dietary intake a relevant route of human exposure. In sports nutrition, this issue may be particularly important because athletes often have high food and fluid consumption, frequent use of packaged sports nutrition products, dietary supplements, bottled beverages, and sport-specific hydration strategies. This narrative review, supported by a structured literature search, examines dietary MP exposure and its potential relevance to gastrointestinal function, gut microbiota, oxidative stress, inflammation, mitochondrial activity, endocrine regulation, metabolism, recovery, adaptation, and performance-related outcomes in athletes. Current evidence suggests that MPs and nanoplastics may interact with biological systems through mechanisms involving intestinal barrier disruption, microbiota alterations, inflammatory activation, oxidative damage, mitochondrial perturbation, endocrine-disrupting chemicals, and metabolic dysregulation. However, most available data derive from in vitro studies, animal models, food contamination analyses, exposure-estimation studies, and indirect human biomonitoring evidence. Direct studies in athletic populations are currently lacking. Therefore, the possible implications of MP exposure on recovery, adaptation, and exercise performance should be interpreted as biologically plausible but unproven. From a practical perspective, evidence-informed strategies may include reducing avoidable plastic-related exposure while maintaining adequate hydration, energy availability, nutrient timing, supplement quality, and dietary patterns that support antioxidant defenses, inflammatory balance, gut health, and physiological resilience. Future research should prioritize standardized exposure assessment, validated biomarkers, human biomonitoring, and sport-specific studies evaluating MP exposure in relation to physiological and performance-related outcomes. Full article

The rapid adoption of electric vehicles (EVs) has intensified the demand for advanced energy storage technologies capable of delivering high energy density, high power density, enhanced safety, and extended service life. Although lithium-ion batteries remain the dominant energy storage technology for EVs, their limited power capability, thermal degradation, and accelerated aging under high transient loads constrain vehicle performance. Battery–supercapacitor hybrid energy storage systems (HESSs) have emerged as a promising solution by combining the high energy density of batteries with the high-power density and rapid charge–discharge capability of supercapacitors. However, the increasing complexity of HESS architecture requires intelligent energy management strategies to optimize power allocation, battery protection, thermal regulation, and overall system efficiency. Existing review papers primarily address individual aspects of HESS architecture, battery management, or artificial intelligence (AI)-based control, leaving a lack of a unified review integrating these topics. This paper addresses this gap by reviewing 181 publications published between 2020 and 2026, covering HESS architectures, conventional and AI-driven energy management strategies, machine learning, deep learning, reinforcement learning, battery state estimation, diagnostics, prognostics, thermal management, and fault diagnosis. The reviewed studies are critically analyzed to assess the impact of AI on battery lifetime, regenerative braking, charging performance, thermal behavior, and energy efficiency. The review further identifies emerging research directions, including explainable AI, digital twins, federated learning, edge intelligence, vehicle-to-grid integration, and cybersecurity-aware energy management. The findings indicate that AI-based approaches generally demonstrate greater adaptability, predictive capability, and battery protection than conventional methods under dynamic operating conditions, although challenges related to computational complexity, real-time implementation, data availability, explainability, cybersecurity, and standardization remain significant barriers to large-scale deployment. Full article

NASA’s Fire Information for Resource Management System (FIRMS) provides near-real-time thermal anomaly detections from VIIRS, but not all detections correspond to wildfire incidents: industrial heat, agricultural burning, and sensor artifacts produce false alarms that contribute to alert fatigue for emergency-management analysts. We study whether contextual machine learning (ML) features improve wildfire-incident classification from FIRMS detections, and—more importantly—whether reported gains survive leakage-controlled evaluation. We construct a labeled dataset by matching 521,395 VIIRS SNPP detections across CONUS in 2024 to 3766 NIFC 2024 wildfire perimeters, yielding 131,771 (25.3%) wildfire-matched and 389,624 candidate non-wildfire detections spanning 1067 distinct wildfire incidents. We benchmark five operational baselines and six classifiers under four validation regimes (random, event-aware, 5° spatial-block, and temporal holdout) with and without raw geographic coordinates. A naive random split inflates LightGBM to F1 $=0.985$, but a leakage-controlled event-aware split reduces it to F1 $=0.767$, and a spatial-block holdout to F1 $=0.627$. Feature attribution shows geographic coordinates account for 88.9% of model gain—the summed share of LightGBM’s total split-gain attributed to the three coordinate features within the full-feature model; removing coordinates improves spatial-block generalization from F1 $=0.627$ to $0.818$, demonstrating that raw coordinates drive memorization of where 2024 fires occurred rather than transferable discrimination. We further show that spatiotemporal clustering must be causal: a model using full-partition clustering appears strong (F1 $=0.908$) but leaks future detections, whereas a properly causal trailing-window version ties plain LightGBM in-distribution (F1 $=0.762$). Combining causal clustering with no raw coordinates is the most robust configuration under spatial transfer (spatial-block F1 $=0.868$ vs. $0.627$ for the coordinate model). Bootstrap 95% confidence intervals show these gaps far exceed statistical uncertainty, and sensitivity analyses show the conclusions are robust to the spatial-block size and to the clustering-window choice. Under natural class prevalence (14%), precision falls to 0.69, and results are sensitive to the labeling buffer. All ML models nonetheless far exceed FIRMS high-confidence thresholding (F1 $=0.128$). We argue that spatial leakage—not raw accuracy—is the central methodological issue for FIRMS wildfire-incident classification, and recommend coordinate-free, causal spatiotemporal-clustering features evaluated under spatial holdout. The system is intended as an analyst-prioritization decision-support layer, not autonomous incident confirmation. Full article

Gait symmetry analysis has emerged as an important tool in rehabilitation engineering and neurological disorder assessment, as it provides clinically relevant indicators of mobility impairment and gait abnormalities. The proposed framework integrates gait symmetry variability, statistical gait features and Dynamic Time Warping (DTW)-based temporal alignment to enhance robustness against gait variations and irregular walking patterns. A hybrid feature vector comprising DTW similarity scores, the hybrid gait symmetry index (GSI), and statistical gait descriptors was employed to classify gait patterns into five categories: normal, slow, medium, fast, and abnormal. The system was implemented as a wearable edge-computing platform using an NI myRIO device equipped with a tri-axial Inertial Measurement Unit (IMU) mounted on the subject’s body. The onboard FPGA performs real-time signal preprocessing, GSI computation, feature extraction, constrained DTW matching, and gait classification using fixed-point streaming architectures and BRAM-based buffering. Meanwhile, the embedded ARM processor manages TCP/IP communication and transmits real-time gait information to a remote monitoring workstation via a WiFi interface for visualization and analysis. Operating at a clock frequency of 100 MHz, the complete architecture achieves an end-to-end processing latency of approximately 4 ms. The proposed FPGA-based implementation provides low-latency, energy-efficient, and real-time gait analysis, making it well suited for wearable rehabilitation systems, assistive healthcare devices, and continuous mobility monitoring applications. Full article

Liquid biopsy has emerged as a transformative approach in modern oncology, offering minimally invasive access to tumor-derived biomarkers through the analysis of circulating tumor DNA, cell-free DNA, and extracellular vesicles such as exosomes. Unlike conventional tissue biopsies, liquid biopsy enables real-time monitoring of tumor dynamics, molecular heterogeneity, treatment response, and the development of therapeutic resistance. Recent advances in ultra-sensitive molecular technologies, including digital droplet polymerase chain reaction, next-generation sequencing, methylation profiling, and fragmentomic analysis, have substantially improved the sensitivity and specificity of circulating nucleic acid detection, facilitating their integration into precision cancer medicine. ctDNA analysis has demonstrated significant clinical utility across multiple malignancies, including lung, breast, colorectal, pancreatic, and prostate cancers, particularly in the identification of actionable genomic alterations, minimal residual disease, and mechanisms of acquired resistance. In parallel, cell-free DNA provides broader insights into tumor biology and systemic genomic alterations, while exosomes contribute additional layers of molecular information through the transport of nucleic acids, proteins, and signaling molecules involved in intercellular communication and tumor microenvironment modulation. The integration of artificial intelligence and machine learning approaches further enhances the interpretative power of liquid biopsy-derived datasets and supports the development of personalized therapeutic strategies. Despite these advances, important challenges remain, including low tumor fraction in early-stage disease, biological and technical variability, clonal hematopoiesis-associated false positives, assay standardization, and cost-effectiveness considerations. Nevertheless, the expanding clinical applicability of liquid biopsy technologies positions them as essential components of contemporary precision oncology. This review summarizes the biological foundations, analytical methodologies, current clinical applications, technological innovations, and future perspectives of circulating tumor DNA, cell-free DNA, and exosome-based liquid biopsies in cancer diagnosis, monitoring, and personalized treatment strategies. Full article

Laser shock peening (LSP) is an advanced surface modification technique that significantly enhances the fatigue resistance of metallic components through the synergistic implantation of deep compressive residual stresses (CRSs) and gradient microstructural refinement. Existing investigations have shown that LSP can generate strengthening layers extending from several hundred micrometers to approximately 1 mm in depth, with affected zones reaching 5–6 times the depth typically achieved by conventional shot peening in representative titanium alloys. In specific cases, LSP has increased the fatigue limit from 483.2 MPa to 593.6 MPa, corresponding to an improvement of approximately 22.8%, while optimized treatment of Ti-17 compressor blades has extended fatigue life by more than two orders of magnitude. This review systematically elucidates the anti-fatigue strengthening mechanisms of LSP across a range of metallic systems, with emphasis on three key aspects: (i) the mechanistic retardation of fatigue crack initiation and propagation, mediated by CRS-induced reductions in the stress intensity factor and enhanced crack closure effects; (ii) the parametric sensitivity of surface integrity and stress field homogeneity to laser energy density, spot overlap ratio, and multiple-impact sequencing; and (iii) the process-specific characteristics of emerging LSP variants, including laser peening without coating, warm laser shock peening, and cryogenic laser shock peening. Furthermore, we critically evaluate the role of multiscale numerical simulations—encompassing macroscopic finite element analysis, mesoscopic crystal plasticity modeling, and molecular dynamics—in optimizing process parameters and predicting fatigue life. By integrating experimental, computational, and theoretical perspectives, this review establishes a coherent process–structure–property framework to guide the rational design of LSP protocols for targeted fatigue performance enhancement. Full article

School gymnasiums in Taiwan often serve as emergency shelters, demanding vital seismic evaluation. Conventional collapse ground acceleration (Ac) assessment via finite element software requires exhaustive computational time and detailed reinforcement data unavailable during early-stage planning. To bridge this operational gap, this study develops a data-driven framework for preliminary seismic evaluation. This framework offers structural designers or architects a rapid planning tool for prospective facilities and enables regional screening to identify vulnerable existing gymnasiums, complementing high-fidelity modeling. An evolutionary support vector machine inference system (ESIS) is proposed to efficiently predict Ac utilizing basic geometric and layout parameters. Concurrently, gene expression programming derives explicit equations to enhance engineering interpretability, while multivariate statistical analyses, including principal component analysis and cluster analysis, together with correlation analysis, are incorporated to investigate seismic characteristics statistically and identify dominant seismic factors. Based on an empirical inventory of 479 standalone gymnasiums, results reveal that dominant seismic factors vary distinctly among structural clusters. Compared with several baseline AI models, the ESIS achieves superior generalization performance, yielding RMSE values of 0.067–0.086 and R² values of 0.794–0.918 on testing datasets. Ultimately, this integrated framework provides an efficient and highly accurate decision-support tool for macro-scale screening and preliminary seismic performance assessment. Full article

Introduction: Uterine leiomyosarcoma (uLMS) is a rare, highly aggressive malignancy arising from the smooth muscle tissue of the uterine wall. It typically presents with abnormal vaginal bleeding, pelvic pain, or a pelvic mass. In rare instances, symptoms may result from local invasion or metastasis. We report a case of uLMS initially diagnosed following colonic perforation due to direct tumor invasion, accompanied by a comprehensive narrative review of the literature on the incidental identification of uterine sarcomas during emergency general surgery to further emphasize the diagnostic challenges, treatment approaches, and need for individualized care in these complex cases. Case Presentation: A 45-year-old woman presented to the Emergency Department with acute abdominal pain of several hours’ duration, in the absence of other associated symptoms. An emergency exploratory laparotomy was performed, revealing feculent peritonitis secondary to sigmoid colon rupture, resulting from local invasion by a large uterine mass. A total abdominal hysterectomy with bilateral salpingo-oophorectomy was undertaken, followed by en bloc resection of the sigmoid colon, appendectomy and construction of a terminal colostomy. Her postoperative course was uneventful, and she was discharged on postoperative day eight. Histopathological examination of the specimen revealed a high-grade uterine leiomyosarcoma. Following evaluation by a multidisciplinary oncology board, the patient received adjuvant chemotherapy. Methods and Results: A narrative review of the literature was performed to identify cases of uterine sarcomas incidentally diagnosed during emergency surgery performed by general surgeons. Including the present case, six cases were identified. Most patients presented with acute abdomen mimicking gastrointestinal pathology, with diagnosis established intraoperatively or postoperatively. Definitive surgical management was achieved during the initial emergency procedure in all cases. Conclusion: Although exceptionally rare, uterine sarcoma should be considered in the differential diagnosis of acute abdomen in female patients undergoing emergency surgery. Awareness of this atypical presentation, the appropriate diagnostic approach, real-time intraoperative adaptability, and individualized multidisciplinary management are essential for ensuring appropriate surgical management and optimizing patient care. Full article

Sarcopenia is an age-related progressive decline in skeletal muscle mass, strength, and physical performance that increases the risk of falls, disability, and reduced quality of life among older adults. Its pathogenesis is multifactorial and involves chronic low-grade inflammation, hormonal disturbances, insulin resistance, and mitochondrial dysfunction, leading to an imbalance between muscle protein synthesis and degradation. The aim of this study was to summarise current knowledge regarding the mechanisms underlying sarcopenia, contemporary diagnostic methods, and the effectiveness of modern nutritional and exercise-based strategies, with particular emphasis on technologies supporting patient monitoring. This study is a structured narrative review conducted across PubMed, Scopus, and Web of Science databases, with the literature search completed on 1 March 2026. Separate searches were performed for thematic sections, including pathophysiology, diagnosis, physical activity, nutritional interventions, plant-derived compounds, and digital health technologies. While the core search focused on publications from 2023–2025, specific time-bound deviations were applied: the search for plant-derived compounds was extended back to 2020, and combined interventions were searched up to March 2026 to ensure the inclusion of the most recent evidence. The review included 53 peer-reviewed primary studies (RCTs and observational) and secondary literature (reviews and meta-analyses) involving individuals aged ≥60 years. The most robust evidence supports multicomponent interventions, particularly the synergy between resistance training and adequate protein intake (1.2–1.5 g/kg/day), often supplemented with leucine, vitamin D, omega-3 fatty acids, and creatine. Such strategies effectively counteract anabolic resistance by combining mechanical loading with the stimulation of the mTORC1 signalling pathway, leading to significant improvements in muscle mass, strength, and physical function. While isolated protein or micronutrient supplementation shows limited effectiveness in the absence of exercise, their role as supportive elements in multimodal strategies is well-documented. Furthermore, emerging digital health technologies—including wearable sensors and telerehabilitation—are proving essential for clinical practice, enabling precise, continuous monitoring of physical activity and gait parameters under free-living conditions, which enhances both patient adherence and long-term therapeutic outcomes. Full article

Background/Objectives: Transportation insecurity and chronic health conditions can substantially influence healthcare access and alternative in-person healthcare utilization in urban areas. Alternative healthcare delivery models, such as telehealth services and professional homecare visits, may help address mobility-related barriers. This study examines how transportation insecurity, chronic health status, and healthcare access challenges are associated with homecare visits and telehealth utilization, while also assessing differences in health and well-being perceptions among individuals with and without chronic health conditions in Dallas, Texas, and Detroit, Michigan. Methods: A cross-sectional survey design was employed among 1649 respondents using a questionnaire. Binary logistic regression analyses were conducted to examine associations between transportation insecurity, chronic health status, healthcare access challenges, homecare visits, and telehealth utilization. Mann–Whitney U tests were used to compare perceived physical health and mental health between participants with and without chronic health conditions. Results: Transportation insecurity emerged as having a significant relationship with homecare visits, with transportation-insecure respondents being approximately 4.7 times more likely to receive homecare services than transportation-secure respondents. Transportation insecurity and healthcare access challenges were also significantly associated with greater telehealth utilization in Detroit and both cities combined. Participants without chronic health conditions reported significantly more favorable perceptions of physical and mental health than those with chronic conditions. Transportation affordability, lack of available rides from family or friends, and long waiting times were identified as the most common healthcare transportation barriers. Conclusions: Healthcare utilization and well-being outcomes are significantly associated with self-reported chronic health status and transportation insecurity. Expanding transportation assistance programs, strengthening homecare services, and improving telehealth availability may enhance healthcare access and support better health outcomes among transportation-disadvantaged and chronically ill populations. Full article

Background: Lung infections represent a major cause of morbidity and mortality in patients with cystic fibrosis (CF) and are predominantly associated with chronic infection by Pseudomonas aeruginosa. The clinical management of CF lung disease is increasingly compromised by the emergence of multidrug-resistant strains, biofilm formation, and the expression of multiple virulence determinants. Antimicrobial peptides (AMPs), evolutionarily conserved effectors of innate immunity, have emerged as promising therapeutic candidates due to their ability to exert both bactericidal and anti-virulence activities. In this study, we investigated the antimicrobial and mechanistic effects of Ranalexin-1G, an AMP derived from the skin secretion of Rana grylio, against P. aeruginosa, for which its antibacterial activity has not previously been reported in the literature. Methods: Antibacterial activity was determined against the reference strain and three clinical isolates of P. aeruginosa by broth microdilution assays, time-kill kinetics and anti-biofilm assays, while peptide-mediated modulation of virulence was evaluated through transcriptional analysis of key virulence-associated genes by RT-PCR. The impact of Ranalexin-1G on host–pathogen interactions was further assessed using bacterial invasion assays in human bronchial epithelial cells (BEAS-2B). Results: Ranalexin-1G exerted a rapid bactericidal effect within 6 h at non-cytotoxic concentrations and displayed modest anti-biofilm effects, with greater efficacy in inhibiting biofilm formation. Mechanistically, peptide treatment resulted in a reduction in the expression of selected genes involved in biofilm formation and virulence, including those associated with alginate biosynthesis and type III secretion system-mediated cytotoxicity. Consistently, Ranalexin-1G markedly impaired bacterial invasion of epithelial cells, indicating interference with early host–pathogen interaction processes. Notably, the peptide displayed robust antimicrobial activity against multidrug-resistant P. aeruginosa clinical isolates from CF patients. Conclusions: Collectively, these findings suggest that Ranalexin-1G acts through a dual mechanism involving direct bactericidal activity and modulation of selected virulence pathways, supporting further investigation of its potential as an anti-virulence and host-directed approach for the treatment of chronic P. aeruginosa infections in cystic fibrosis. Full article

Background/Objectives: Therapeutic adherence remains a critical challenge in the management of chronic conditions, yet most research has focused on pharmacological adherence from the perspective of physicians and pharmacists. The views of non-physician healthcare professionals—particularly physiotherapists, podiatrists, psychologists, and nurses—remain underrepresented. This study aims to explore how these four healthcare disciplines perceive the factors influencing therapeutic adherence, the strategies they use to support it, and how they address patient resilience in clinical practice. Methods: An exploratory qualitative study was conducted using semi-structured interviews with 32 healthcare professionals (8 per discipline) recruited through purposive sampling across diverse care settings across Spain. Data were analyzed using reflexive thematic analysis following a hybrid deductive–inductive approach. Quality criteria were applied in accordance with the standards proposed by Lincoln and Guba. Results: Three thematic domains emerged. Patient-related factors, especially motivation, health literacy, illness beliefs, and socioeconomic constraints, emerged as central determinants across all disciplines. Health system barriers, particularly limited consultation time and fragmented continuity of care, also constituted significant barriers. Discipline-specific strategies ranged from the teach-back technique and customized visual aids in nursing and podiatry to functional goal-setting and group-based dynamics in physiotherapy and expectation-setting and digital follow-up in psychology. Resilience was consistently described as a key mediating factor enabling patients to sustain adherence despite adversity. Conclusions: Therapeutic adherence is a multifactorial and discipline-sensitive phenomenon. The complementary strategies identified across professions support the value of coordinated interdisciplinary approaches. Resilience-informed interventions and profession-specific adherence training represent promising directions for improving clinical practice and professional education. Full article