Search Results (20,858)

The necrotrophic pathogen Sclerotinia sclerotiorum compromises the physiological and anatomical integrity of cotton, leading to substantial economic losses due to rapid tissue necrosis, stem blight, boll rot, and leaf wilting. In this context, the use of endophytic microorganisms emerges as a promising strategy for the biocontrol of white mold. This study tested the hypothesis that endophytic fungal strains isolated from the roots of Butia purpurascens, a palm tree endemic to the Cerrado biome, could mitigate disease symptoms in Gossypium hirsutum L. To evaluate this, cotton plants were subjected to biotic stress imposed by S. sclerotiorum to assess the effectiveness of seven fungal strains in attenuating disease. The impact of the pathogen was monitored through growth variables, gas exchange, leaf temperature, chlorophyll a fluorescence, antioxidant enzyme activity, proline and malondialdehyde (MDA) levels, and the incidence of rot in petioles, leaves, and flower buds. Overall, inoculation with endophytic fungi significantly alleviated the effects of the phytopathogen, promoting vegetative growth and optimizing physiological performance. Treated plants exhibited alleviated stress in primary photochemistry, reduced non-photochemical energy dissipation, and stable carbon fixation. Additionally, efficient modulation of the antioxidant system and preservation of anatomical structures were observed, minimizing the severe symptoms of white mold. Notably, the non-pathogenic strains BP10EF (Gibberella moniliformis), BP16EF (Penicillium purpurogenum), and BP33EF (Hamigera insecticola) acted as potent physiological modulators, yielding responses similar to those of healthy plants. These results highlight the biotechnological potential of these endophytic strains, which can be explored as both growth promoters and resistance inducers in cotton against white mold. Full article

Soil contamination in Sub-Saharan Africa (SSA) is increasingly driven by rapid industrialization, intensive agriculture, mining activities, and urban expansion, posing significant risks to food safety, ecosystem services, and human livelihoods. Despite the growing scale of the problem, low-cost, locally adaptable remediation technologies are widely available and technically feasible within the region. Organic waste and waste-derived products—such as compost, manure, biochar, vermicompost, digestate, and agro-industrial residues—have emerged as sustainable and cost-effective amendments for the remediation of contaminated soils. These materials can immobilize heavy metals, enhance the microbial degradation of organic pollutants, and improve soil health, making them especially suitable for resource-constrained settings. This review synthesizes the current knowledge on the use of organic waste-based remediation approaches in SSA, highlighting technologies already applied at the laboratory, pilot, and field scales, as well as their effectiveness across different contaminant types. However, despite their demonstrated potential, their widespread adoption remains limited. The primary challenge is not the absence of affordable solutions, but rather the systemic constraints characteristic of many SSA countries, including limited technical capacity, weak policy and regulatory frameworks, low stakeholder awareness, and insufficient financial and institutional support for large-scale implementation. To enable broader uptake, there is a need to strengthen waste segregation and treatment systems, standardize composting and pyrolysis processes, and develop robust regulatory guidelines and certification schemes. Investments in monitoring infrastructure, practitioner training, and knowledge transfer mechanisms will also be critical to translating scientific advances into scalable, field-ready solutions for sustainable soil remediation in SSA. Full article

The rapid growth of the elderly population worldwide demands reliable activity recognition technologies to support independent living and continuous health supervision. However, conventional wearable sensor-based human activity recognition (HAR) techniques often fail to capture the complex temporal behaviour and subtle motion patterns characteristic of the elderly. To address these limitations, this study introduces a hybrid deep residual architecture—CNN-CBAM-BiGRU—that integrates convolutional neural networks (CNNs), the convolutional block attention module (CBAM), and bidirectional gated recurrent units (BiGRUs) to improve activity recognition using inertial measurement unit (IMU) data. In the proposed CNN-CBAM-BiGRU framework, CNN layers automatically derive representative features from raw sensor signals, CBAM applies adaptive channel and spatial attention to highlight informative patterns, and BiGRU captures long-range temporal relationships within activity sequences. The approach was evaluated on three benchmark datasets designed for elderly populations—HAR70+, HARTH, and SisFall—covering daily activities and fall events. The proposed model consistently outperforms existing methods across all datasets, achieving accuracies exceeding 96%, F1-scores above 93%, and a fall detection recall of 93.74%, confirming its robustness and suitability for safety-critical monitoring applications. Class-level evaluation indicates excellent recognition of static postures and consistent performance for dynamic actions. Convergence analysis further confirms efficient learning with limited overfitting across datasets. The proposed framework thus provides a robust and accurate solution for wearable-based elderly activity recognition, with strong potential for deployment in fall detection, health monitoring, and ambient assisted living systems. Full article

Radon is a significant indoor air pollutant and a leading cause of lung cancer in non-smokers. While geogenic radon potential is well-documented, the specific contribution of building materials—particularly historic stones and those containing industrial by-products—requires precise in situ characterization to ensure public safety. This study investigates radon activity concentrations and surface exhalation rates across three distinct case studies in Slovakia: a mid-20th-century structure with cinder blocks, a UNESCO-protected Gothic building featuring volcanic andesite, and a historic stone plinth. Continuous radon monitoring and accumulation chamber measurements were employed, integrated with the tracking of meteorological parameters. The results revealed the highest surface exhalation rate in cinder block masonry (8.98 Bq m⁻² h⁻¹), followed by andesite ashlars (7.9 Bq m⁻² h⁻¹) and stone (1.87 Bq m⁻² h⁻¹). A clear correlation was observed between indoor radon levels and barometric pressure, whereas the influence of outdoor temperature appeared negligible. An estimated Activity Concentration Index of 0.30 suggests that the volcanic rock is likely radiologically safe for use as a bulk building material. The study concludes that while specific materials contribute to exhalation, indoor radon stability is primarily governed by barometric variations and the effectiveness of floor barriers against geogenic ingress rather than the masonry itself. Full article

Concurrent with the rising consumption of ultra-processed, high-calorie diets and the decline in physical activity, obesity and related cardiovascular conditions among young adults have continued to increase, becoming an important global public health concern. This study integrates non-invasive Internet of Things (IoT) sensing devices, including the TERUMO ES-P2000 blood pressure monitor (Terumo Corp., Tokyo, Japan) and the PhysioFlow PF07 Enduro cardiac hemodynamic analyzer (Manatec Biomedical, Poissy, France), with an artificial neural network (ANN) for cardiac index (CI) prediction. Through appropriate data preprocessing and model training strategies, the generalization ability and stability of the proposed CI prediction model were significantly enhanced. Experimental results demonstrate that, when using three physiological parameters as input, the ANN achieved a classification accuracy of 97.78%, substantially outperforming traditional approaches. Even under two-parameter input conditions, the model maintained strong predictive performance. These findings confirm the effectiveness and practical potential of the proposed framework for real-time, non-invasive CI assessment. Moreover, this research has received rigorous assessment and approval from the Institutional Review Board (IRB) under application number 202501987B0. Full article

Autism Spectrum Disorder (ASD) is a lifelong condition marked by challenges in social communication and repetitive behaviors. Current treatments, primarily behavioral therapies, often fail to address the core symptoms. Recent research has explored the potential of psychedelics, such as LSD, psilocybin, and MDMA, as a new therapeutic approach. While these substances primarily modulate the serotonin 5-HT_2A receptor, their therapeutic effects also involve interactions with other serotonergic, dopaminergic, and glutamatergic pathways, collectively promoting neuroplasticity—the brain’s ability to change and adapt. The specific receptors’ activation leads to structural and functional changes in the brain that can enhance social behavior and emotional regulation. Studies show that psychedelics may reduce symptoms of conditions like treatment-resistant depression and PTSD, highlighting their therapeutic potential. For ASD specifically, psychedelics may improve psychological flexibility, reduce distress, and enhance social interaction. While promising, the use of these substances requires careful consideration. Psychedelics can induce intense experiences and altered states of consciousness, necessitating strict monitoring and support during therapy. Ethical guidelines, including informed consent, are crucial, especially for vulnerable populations. In conclusion, psychedelics hold significant promise for treating ASD and other psychiatric disorders by promoting neuroplasticity and modulating complex signaling pathways. Continued research and clinical trials, conducted with strong ethical oversight, are essential to realizing their full therapeutic potential. Full article

Background/Objectives: Steady-State Visual Evoked Potential-based Brain–Computer Interfaces face a critical trade-off between system accuracy and user visual fatigue. To address this challenge, the objective of this study was to determine how the spatial manipulation of stimulus size modulates the full spectral dynamics of the Electroencephalogram, encompassing both the periodic oscillatory response and the aperiodic (1/f) background noise. Methods: Twenty-two healthy subjects completed a sustained visual attention task using a competitive stimulus paradigm (20 Hz and 30 Hz) presented in three spatial dimensions (Small, Medium, and Big). Parieto-occipital brain signals were decomposed using the spectral parameterization algorithm (SpecParam) to extract frequency-specific visually evoked response power and the aperiodic slope, while visual fixation was continuously monitored via eyetracking. Results: Increasing stimulus size induced a statistically significant gain in the power of the attended signal (Target) without increasing the response of the peripheral distractor. Simultaneously, larger stimuli produced a significant increase in the aperiodic slope during 20 Hz attention and visual rest, suggesting increased cortical inhibition and a reduction in broadband neural activity. This aperiodic modulation was not observed at 30 Hz. Conclusions: The improvement in Signal-to-Noise Ratio with increasing stimulus size arises from a dual neurophysiological mechanism: enhancement of the periodic evoked response together with a reduction in background neural noise. Full article

Exercise adaptation depends on overload that is resolved by recovery, yet the same biology becomes maladaptive when immune, endocrine, metabolic, and muscle-centered stress signals fail to normalize. Exercise-induced maladaptation represents a systems-level failure of biological resolution, with direct relevance to disease-like dysregulation. Functional overreaching, non-functional overreaching, and overtraining syndrome remain difficult to diagnose because no single biomarker provides adequate specificity, temporal stability, or clinical portability. This narrative review synthesizes human and mechanistic evidence across proteomics, transcriptomics, metabolomics, endocrine profiling, extracellular vesicles, and mitochondrial quality-control biology to define the molecular architecture most relevant to athlete monitoring. Across these layers, the most coherent signatures cluster in immune-acute-phase activation, redox-buffering strain, endocrine drift, altered substrate availability, excitation–contraction dysfunction, integrated stress-response signaling, and defects in autophagy–mitophagy and lysosomal remodeling. Three translational elements emerge from this synthesis: a systems-convergence model of recovery failure, a staged biomarker deployment hierarchy, and a provisional recovery failure index. The practical priority is therefore not a solitary marker, but serial phenotype-anchored multimarker panels that connect circulating signals with muscle-centered biology and support decision-making before prolonged recovery failure becomes entrenched. Full article

Accurate classification of physical activity (PA) intensity is essential for exercise prescription, rehabilitation monitoring, and evaluation of guideline adherence. However, widely used wrist-worn accelerometer cut-points may substantially misclassify physiological intensity. This study evaluated absolute accelerometer thresholds during a maximal 2400 m run in military office workers and examined whether individualized cut-points improve agreement with physiological intensity. Seventy-four military office workers completed the test while wearing a wrist-worn ActiGraph GT9X Link and a chest-worn Zephyr BioHarness. Participants achieved near-maximal physiological effort, with peak heart rate averaging 187 ± 11 bpm (95 ± 4.2% age-predicted HRmax). Despite this high intensity, absolute wrist-worn cut-points classified only 34.5% of participants as performing vigorous activity for most of the test. Individualized cut-points, derived from each participant’s individual reference intensity, calculated as the three highest consecutive one-minute epochs during the 2400 m test, substantially improved agreement between accelerometer-derived classifications and physiological intensity. Agreement with %HRmax increased from fair (κ = 0.31), using absolute thresholds, to good (κ = 0.74), using individualized thresholds, and intraclass correlation increased from 0.52 to 0.81. These findings demonstrate that absolute cut-points markedly underestimate high-intensity activity, potentially leading to inaccurate exercise load monitoring and misinterpretation of training intensity. Individualized calibration during a standardized maximal running test provides a feasible strategy to improve the validity of intensity assessment using wearables. Although the study population consisted of military office workers, the approach may be applicable to other active populations. However, further validation in independent samples is needed. Full article

Lamellar ichthyosis is a rare congenital disorder of keratinization frequently associated with ocular complications, most commonly cicatricial ectropion and exposure keratopathy. We present a case of severe mixed exposure-related and neurotrophic keratopathy with marked corneal thinning in a 61-year-old man with genetically confirmed lamellar ichthyosis. At presentation, the best-corrected visual acuity (BCVA) in the right eye was limited to hand motion (logMAR 2.3). Slit-lamp examination revealed a large central to inferocentral corneal ulcer measuring approximately 3 × 4 mm with severe stromal thinning in the setting of marked lower eyelid ectropion, incomplete eyelid closure, and chronic ocular surface exposure, while anterior segment optical coherence tomography (AS-OCT) demonstrated a minimal corneal thickness of approximately 165 µm. Microbiological swabs obtained from the conjunctival sac were negative, and no purulent discharge, hypopyon, or anterior chamber inflammatory reaction was present, making active infectious keratitis unlikely. Corneal sensitivity measured with Cochet–Bonnet esthesiometry at presentation, centrally and in all four peripheral quadrants of both eyes, was markedly reduced, more severely in the affected right eye, supporting the presence of a severe neurotrophic component contributing to impaired corneal healing. Intensive conservative therapy including preservative-free lubricants, dexpanthenol gel, autologous serum eye drops, topical insulin, prophylactic antibiotics, and systemic doxycycline was initiated. Serial AS-OCT imaging demonstrated progressive structural recovery, with corneal thickness increasing to 438 µm after one month of treatment and complete corneal epithelialization. The BCVA improved to 0.2 Snellen (0.7 logMAR). This case highlights the diagnostic value of multimodal anterior segment imaging in monitoring severe mixed keratopathy with advanced corneal thinning and demonstrates that intensive conservative therapy may stabilize the ocular surface and prevent corneal perforation in patients with lamellar ichthyosis. Full article

Water scarcity and pollution from anthropogenic activities are major challenges, increasing the need for sustainable wastewater treatment solutions. Constructed wetlands mimic natural wetland ecosystems using macrophytes and substrates, representing a possible nature-based solution aligned with circular economy principles and the United Nations Sustainable Development Goals. So, this revision integrates recent literature, providing an overview of natural wetlands and examining the design and operation of constructed wetland systems. Also, incorporates a case study that focuses on a constructed wetland implemented at an eco-friendly dog shelter in Portugal—a unique example globally—demonstrating practical wastewater treatment and small-scale water reuse, and offering insights for sustainable management. Performance assessment based on previous work indicates that the system effectively reduces most water quality parameters to levels compliant with national and European irrigation standards. Removal efficiencies exceeded 97% for chemical oxygen demand, total suspended solids, and turbidity, while maintaining low energy consumption and minimal maintenance. Overall, constructed wetlands emerge as a sustainable alternative to conventional wastewater treatment systems; however, several challenges remain to be addressed. Future research should focus on improved aeration strategies, optimized substrate–macrophyte combinations, and long-term monitoring under climate variability, with floating wetlands offering promising opportunities to further enhance treatment efficiency. Full article

Bone health in highly trained female athletes is critical for performance and long-term wellbeing, yet systematic evidence regarding seasonal changes remains limited. The main objective of this systematic review (PROSPERO ID: 420251230393) is to determine changes in bone mineral density (BMD) and bone mineral content (BMC) across the sport macrocycle in highly trained female athletes, encompassing both elite and collegiate (NCAA) populations. Six databases were searched for studies published between 2010 and 2025, with inclusion requiring female athletes, BMD/BMC measurements, and longitudinal assessment across a macrocycle. Fourteen studies involving 522 premenopausal athletes were included, with dual-energy X-ray absorptiometry measurements conducted approximately six months apart. Study quality was assessed using the NIH Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies and indicated a predominantly good quality. Five studies reported no significant change in BMD/BMC, five demonstrated improvements, three reported mixed findings across sports or athlete subgroups, and one reported a significant decline. Only two studies attempted to account for all three primary confounders—menstrual cycle status, dietary intake, and physical activity monitoring—while seven reported no confounding variables. While bone health appears largely maintained across the sport macrocycle in highly trained premenopausal female athletes, these findings should be interpreted cautiously given the inadequate confounder reporting, heterogeneous sport exposures, variability in skeletal sites measured, and inconsistent measurement timing. Future research must comprehensively assess these variables alongside sport-specific skeletal measurements to identify athletes at risk of bone health deterioration. Full article

Heart rate variability (HRV) has emerged as a key biomarker for assessing autonomic nervous system activity, stress, fatigue, and emotional states. With the rapid development of wearable sensor technologies, HRV analysis has expanded from clinical environments to real-world, continuous monitoring. This review summarizes current applications of HRV metrics in wearable devices, including fitness tracking, mental stress assessment, sleep quality evaluation, and early detection of physiological or psychological disorders. Recent advances in photoplethysmography (PPG)-based HRV estimation have enabled noninvasive and user-friendly measurement, though challenges remain in accuracy under motion and variable environmental conditions. We also discuss methodological considerations, such as artifact correction, data segmentation, and the integration of HRV with other biosignals for multimodal analysis. Emerging research suggests that combining HRV with metrics such as respiration rate, skin conductance, and accelerometry can enhance robustness and interpretability in dynamic settings. Finally, future directions are proposed toward personalized health analytics, emotion-aware computing, and real-time adaptive feedback systems. This review highlights the growing potential of wearable HRV analysis as a foundation for preventive healthcare and human–machine symbiosis. Full article

Oral cancer remains a major global health problem with high morbidity and mortality rates, and despite advances in therapeutic approaches, challenges persist in early diagnosis and effective disease management. MicroRNAs (miRNAs) are endogenous, small non-coding RNAs that regulate gene expression at the post-transcriptional level and play fundamental roles in maintaining cellular homeostasis, as well as in the initiation and progression of multiple malignancies, including oral cancer. Dysregulation of miRNAs contributes to oral carcinogenesis by modulating key cellular processes such as cell proliferation, apoptosis, invasion, metastasis, and angiogenesis. Altered miRNA expression profiles have been consistently identified in oral cancer tissues and body fluids, including saliva and blood, supporting their potential utility as reliable biomarkers for early detection, prognosis, and disease monitoring. Circulating miRNAs, in particular, represent a promising non-invasive diagnostic tool for assessing disease progression and therapeutic response. Moreover, miRNAs are actively involved in regulating sensitivity and resistance to chemotherapy and radiotherapy, with specific miRNAs either enhancing treatment efficacy or promoting therapeutic resistance. This review aims to highlight the critical role of miRNAs in oral cancer pathogenesis, diagnosis, prognosis, and treatment, exploring their potential as biomarkers and therapeutic targets to improve early detection, patient outcomes, and personalized treatment strategies. Full article