Search Results (3,775)

Background: Plant-based protein supplementation in supporting muscle recovery following resistance exercise remains an area of growing interest, particularly among vegan athletes, as a potential alternative to animal-based proteins. This systematic review aimed to evaluate the effectiveness of plant-based proteins on recovery from resistance exercise-induced muscle damage in healthy young adults. Methods: A systematic and comprehensive search was administered in eight databases up to 1 May 2025, identifying 1407 articles. Following deduplication and screening, 24 studies met the eligibility criteria, including 22 randomized controlled trials and 2 non-randomized studies, with the majority from high income western countries. Results: Interventions primarily involved soy, pea, rice, hemp, potato, and blended plant protein sources, with doses ranging from 15 to 50 g, typically administered post resistance exercise. Outcomes assessed included muscle protein synthesis (MPS), delayed-onset muscle soreness (DOMS), inflammatory biomarkers, muscle function, and fatigue. The review findings reaffirm that single-source plant proteins generally offer limited benefits compared to animal proteins such as whey, particularly in acute recovery settings, a limitation well-documented consistently in the literature. However, our synthesis highlights that well-formulated plant protein blends (e.g., combinations of pea, rice, and canola) can stimulate MPS at levels comparable to whey when consumed at adequate doses (≥30 g with ~2.5 g leucine). Some studies also reported improvements in subjective recovery outcomes and reductions in muscle damage biomarkers with soy or pea protein. However, overall evidence remains limited by small sample sizes, moderate to high risk of bias, and heterogeneity in intervention protocols, protein formulations, and outcome measures. Risk of bias assessments revealed concerns related to detection and reporting bias in nearly half the studies. Due to clinical and methodological variability, a meta-analysis was not conducted. Conclusion: plant-based proteins particularly in the form of protein blends and when dosed appropriately, may support muscle recovery in resistance-trained individuals and offer a viable alternative to animal-based proteins. However, further high-quality, long-term trials in vegan populations are needed to establish definitive recommendations for plant protein use in sports nutrition. Full article

Smart walking aids represent a growing trend in assistive technologies designed to support individuals with mobility impairments in their daily lives and rehabilitation. Previous research has introduced sensor-integrated systems that provide user feedback to enhance safety and functional mobility. However, a comprehensive overview of their technological and functional characteristics is lacking. To address this gap, this scoping review systematically mapped the current state of research in sensor-based walking aids, focusing on device types, sensor technologies, application contexts, target populations, and reported outcomes. In addition, integrated artificial intelligence (AI)-based approaches for functional support and health monitoring were examined. Following PRISMA-ScR guidelines, 35 peer-reviewed articles were identified from three databases: ACM Digital Library, IEEE Xplore, and Web of Science. Extracted data were thematically analyzed and synthesized across device types (e.g., walking canes, crutches, walkers, rollators) and use cases, including gait training, fall prevention, and daily support. Findings show that, while many prototypes show promising features, few have been evaluated in clinical settings or over extended periods. A lack of standardized methods for sensor location assessment, often the superficial implementation of feedback modalities, and limited integration with other assistive technologies were identified. In addition, system validation and user testing lack consensus, with few long-term studies and often incomplete demographic data. Diversity in data communication approaches and the heterogeneous use of AI algorithms were also notable. The review highlights key challenges and research opportunities to guide the future development of intelligent, user-centered mobility systems. Full article

Schizophrenia (SCZ) is a complex psychiatric disorder with heterogeneous molecular underpinnings that remain poorly resolved by conventional single-omics approaches, limiting biomarker discovery and mechanistic insights. To address this gap, we applied an artificial intelligence (AI)-driven multi-omics framework to an open access dataset comprising plasma proteomics, post-translational modifications (PTMs), and metabolomics to systematically dissect SCZ pathophysiology. In a cohort of 104 individuals, comparative analysis of 17 machine learning models revealed that multi-omics integration significantly enhanced classification performance, reaching a maximum AUC of 0.9727 (95% CI: 0.8889–1.000) using LightGBMXT, compared to 0.9636 (95% CI: 0.8636–1.0000) with CNNBiLSTM for proteomics alone. Interpretable feature prioritization identified carbamylation at immunoglobulin-constant region sites IGKC_K20 and IGHG1_K8, alongside oxidation of coagulation factor F10 at residue M8, as key discriminative molecular events. Functional analyses identified significantly enriched pathways including complement activation, platelet signaling, and gut microbiota-associated metabolism. Protein interaction networks further implicated coagulation factors F2, F10, and PLG, as well as complement regulators CFI and C9, as central molecular hubs. The clustering of these molecules highlights a potential axis linking immune activation, blood coagulation, and tissue homeostasis, biological domains increasingly recognized in psychiatric disorders. These results implicate immune–thrombotic dysregulation as a critical component of SCZ pathology, with PTMs of immune proteins serving as quantifiable disease indicators. Our work delineates a robust computational strategy for multi-omics integration into psychiatric research, offering biomarker candidates that warrant further validation for diagnostic and therapeutic applications. Full article

Background: Neuropathic pain (NP), resulting from damage to the somatosensory nervous system, affects 7–10% of the global population and remains poorly managed despite available therapies. Smoking has been associated with increased pain severity and disease burden, yet its role in neuropathy/NP has not been systematically reviewed. This systematic review synthesizes the existing literature on smoking status and its relationship with neuropathy/NP incidence, prevalence, and severity. Methods: The review was conducted in accordance with PRISMA guidelines and included studies that assessed smoking consumption, dependency, quantity, and cessation in individuals with neuropathy/NP. Summary estimates were stratified by exposure type, and pooled odds ratios and relative risks were calculated. Results: Across 62 studies comprising cohort, case–control, and cross-sectional designs, smoking was consistently associated with greater NP prevalence and pain severity. Smoking dependency was linked to increased incidence, while cessation was associated with reduced risk of NP. Despite considerable heterogeneity and risk of bias, particularly from subjective exposure measurement and inconsistent classification, this relationship remained statistically significant. Conclusions: Findings support the role of smoking as a modifiable risk factor in various etiologies of neuropathy/NP. Cessation may represent a low-cost, low-risk, low-tech adjunctive therapy; however, further robust cessation interventional trials are needed, particularly for less common infectious causes of chronic NP such as leprosy. Full article

Focal chondral defects of the knee are a common cause of pain and functional limitation in active individuals and may predispose to early degenerative joint changes. Given the limited regenerative capacity of hyaline cartilage, biologically based surgical strategies have emerged to promote tissue repair and restore joint function. This narrative review critically examines current treatment approaches that rely on autologous cell sources and scaffold-supported regeneration. Particular emphasis is placed on techniques that stimulate endogenous repair or support chondrocyte-based tissue restoration through the use of autologous biomaterial constructs. The influence of lesion morphology, joint biomechanics, and patient-specific variables on treatment selection is discussed in detail, focusing on the differences between tibiofemoral and patellofemoral involvement. Biologically driven approaches have shown promising mid- to long-term outcomes in selected patients, and are increasingly favoured over traditional methods in specific clinical scenarios. However, the literature remains limited by heterogeneity in study design, follow-up duration, and outcome measures. This review aims to provide an evidence-based, morphology-informed framework to support the clinical decision-making process in the management of knee cartilage defects. Full article

Calcific aortic stenosis (CAS) is a newly emerging pandemic in elderly individuals due to the aging of the population in the world. Surgical Aortic Valve Replacement (SAVR) and Transcatheter Aortic Valve Replacement (TAVR) are the cornerstone of the management of severe aortic stenosis accompanied by one or more symptoms. Moreover, an appropriate interventional treatment of CAS, in elderly patients, is a very complex decision for heart teams, to avoid bad outcomes such as operative mortality, cardiovascular and all-cause death, hospitalization for heart failure, worsening of quality of life. In fact, CAS in the elderly is not only a focal valve disease, but a very complex clinical picture with different risk factors and etiologies, differing underlying pathophysiology, large phenotypic heterogeneity in a context of subjective biological, phenotypic and functional aging until frailty and disability. In this review, we analyzed separately and in a more integrated manner, the natural and prognostic histories of the progression of aortic stenosis, the phenotypes of myocardial damage and heart failure, within the metrics and aging trajectory. The aim is to suggest, during the clinical timing of valve disease, the best interval time for an appropriate and effective interventional treatment in each older patient, beyond subjective symptoms by integration of clinical, geriatric, chemical, and advanced imaging biomarkers. Full article

This study presents a comprehensive analysis of the chemical composition of bottom ash samples generated during municipal waste incineration. A total of 52 samples were collected and subjected to statistical analysis for 17 elements and 2 element sums using techniques such as correlation analysis and one-way ANOVA. The results confirm a high degree of heterogeneity in the elemental content, reflecting the variability of waste streams and combustion processes. Strong correlations were identified between certain elements, including Cu-Zn, Co-Ni, and HREE-LREE, indicating common sources and similar geochemical properties. The analysis also revealed significant seasonal variability in the content of Ba and Sr, with lower average values observed during the spring season and greater variability noted during summer and winter. Although Al and HREE did not reach classical significance levels, their distributions suggest possible seasonal differentiation. These findings underscore the need for long-term monitoring and seasonal analysis of incineration bottom ash composition to optimize resource recovery processes and assess environmental risk. The integration of chemical data with operational data on waste composition and combustion parameters may contribute to a better understanding of the variability of individual elements, ultimately supporting the development of effective strategies for ash management and element recovery. Full article

Organoids allow to model healthy and diseased human tissues. and have applications in developmental biology, drug discovery, and cell therapy. Traditionally cultured in immersion/suspension, organoids face issues like lack of standardization, fusion, hypoxia-induced necrosis, continuous agitation, and high media volume requirements. To address these issues, we developed an air–liquid interface (ALi) technology for culturing organoids, termed AirLiwell. It uses non-adhesive microwells for generating and maintaining individualized organoids on an air–liquid interface. This method ensures high standardization, prevents organoid fusion, eliminates the need for agitation, simplifies media changes, reduces media volume, and is compatible with Good Manufacturing Practices. We compared the ALi method to standard immersion culture for midbrain organoids, detailing the process from human pluripotent stem cell (hPSC) culture to organoid maturation and analysis. Air–liquid interface organoids (3D-ALi) showed optimized size and shape standardization. RNA sequencing and immunostaining confirmed neural/dopaminergic specification. Single-cell RNA sequencing revealed that immersion organoids (3D-i) contained 16% fibroblast-like, 23% myeloid-like, and 61% neural cells (49% neurons), whereas 3D-ALi organoids comprised 99% neural cells (86% neurons). Functionally, 3D-ALi organoids showed a striking electrophysiological synchronization, unlike the heterogeneous activity of 3D-i organoids. This standardized organoid platform improves reproducibility and scalability, demonstrated here with midbrain organoids. The use of midbrain organoids is particularly relevant for neuroscience and neurodegenerative diseases, such as Parkinson’s disease, due to their high incidence, opening new perspectives in disease modeling and cell therapy. In addition to hPSC-derived organoids, the method’s versatility extends to cancer organoids and 3D cultures from primary human cells. Full article

The IoE forms the foundation of the modern digital ecosystem by enabling seamless connectivity and data exchange among smart devices, sensors, and systems. However, the inherent nature of this structure, characterized by high heterogeneity, distribution, and resource constraints, renders traditional security approaches insufficient in areas such as data privacy, authentication, access control, and scalable protection. Moreover, centralized security systems face increasing fragility due to single points of failure, various AI-based attacks, including adversarial learning, model poisoning, and deepfakes, and the rising threat of quantum computers to encryption protocols. This study systematically examines the individual and integrated solution potentials of technologies such as Blockchain, Edge Computing, Artificial Intelligence, and Quantum-Resilient Cryptography within the scope of IoE security. Comparative analyses are provided based on metrics such as energy consumption, latency, computational load, and security level, while centralized and decentralized models are evaluated through a multi-layered security lens. In addition to the proposed multi-layered architecture, the study also structures solution methods and technology integrations specific to IoE environments. Classifications, architectural proposals, and the balance between performance and security are addressed from both theoretical and practical perspectives. Furthermore, a future vision is presented regarding federated learning-based privacy-preserving AI solutions, post-quantum digital signatures, and lightweight consensus algorithms. In this context, the study reveals existing vulnerabilities through an interdisciplinary approach and proposes a holistic framework for sustainable, scalable, and quantum-compatible IoE security. Full article

Ventricular tachycardia (VT) remains a major cause of morbidity and mortality in patients with structural heart disease. While catheter ablation has become a cornerstone in VT management, recurrence rates remain substantial due to limitations in electroanatomic mapping (EAM), particularly in cases of deep or heterogeneous arrhythmogenic substrates. Cardiac imaging, especially when multimodal and integrated with mapping systems, has emerged as a critical adjunct to enhance procedural efficacy, safety, and individualized strategy. This comprehensive review explores the evolving role of various imaging modalities, including echocardiography, cardiac magnetic resonance (CMR), computed tomography (CT), positron emission tomography (PET), and intracardiac echocardiography (ICE), in the preprocedural and intraprocedural phases of VT ablation. We highlight their respective strengths in substrate identification, anatomical delineation, and real-time guidance. While limitations persist, including costs, availability, artifacts in device carriers, and lack of standardization, future advances are likely to redefine procedural workflows. Full article

Background/Objectives: The increasing incidence rates of keratinocyte carcinoma (KC), particularly in fair-skinned populations, call for efforts to intensify health education of the general population in addressing this prevalent skin cancer type. As a preparatory step, this systematic review summarizes the published research on the knowledge and risk perception regarding KC among individuals without medical training. Methods: The review was registered in PROSPERO (CRD42024618851) and adheres to PRISMA guidelines. The databases PubMed, Scopus, Web of Science, PsycArticles, and PsycINFO were searched on 30 July 2024. Studies were eligible if knowledge and/or risk perception was assessed in lay people. Risk of bias (ROB) was assessed with the Joanna Briggs Institute checklist for prevalence studies. Comparable outcomes (e.g., awareness of terms for KC) were meta-analyzed. Results: Included reports (n = 17) were published between 1991 and 2024 with 16,728 individuals assessed. Awareness for the most common type of KC, basal cell carcinoma (BCC), was low (20.75% of respondents (95% confidence interval (CI): 15.24–27.61)), while more respondents were familiar with colloquial terms (60.9–72.8%). Meta-analysis indicated an underestimation of the frequency of KC, with only 7.21% (CI: 4.03–12.58) identifying BCC as the most common type of skin cancer. Furthermore, concern about developing KC as assessed in only two overlapping studies was reported by only 25–30% of respondents, indicating a significant gap in risk awareness and a lack of research on risk perception regarding KC. Conclusions: This review highlights the need for targeted health education interventions to improve knowledge and preventive behaviors regarding KC. Given the limitations of the included studies, characterized by high ROB, heterogeneity of results, and a lack of standardized assessment tools, further research is essential to enhance the understanding and awareness of KC in diverse populations. Full article

Background: Persistent Postural-Perceptual Dizziness (PPPD) is a chronic vestibular disorder characterized by dizziness, instability, and visual hypersensitivity. Vestibular Physical Therapy (VPT) is commonly used, but its efficacy remains uncertain due to limited and heterogeneous evidence. Objective: This systematic review and meta-analysis aimed to evaluate the effectiveness of VPT in reducing dizziness and improving balance in individuals with PPPD. Methods: A systematic search of MEDLINE and PEDro was conducted in January 2025. Studies were selected following PRISMA guidelines and included if they assessed VPT interventions in patients diagnosed with PPPD. Risk of bias was assessed using the PEDro scale and the modified Newcastle–Ottawa Scale. The meta-analysis focused on pre- and post-intervention changes in Dizziness Handicap Inventory (DHI) scores using a random-effects model. Results: Six studies met the inclusion criteria. VPT significantly reduced DHI scores (pooled Hedges’ g = 1.60; 95% CI: 0.75–2.45), indicating a moderate to large improvement. Additional outcomes included improvements in postural control (e.g., mini-BESTest and posturography) and psychological well-being (anxiety and depression questionnaires). However, high heterogeneity (I² = 92%) was present across studies. Conclusions: VPT may improve dizziness and balance in PPPD, though evidence is limited. Further high-quality trials with standardized protocols are needed. Full article

Hyperspectral remote sensing plays a crucial role in guiding and supporting various mineral prospecting activities. Combined with artificial intelligence, hyperspectral remote sensing technology becomes a powerful and versatile tool for a wide range of mineral exploration activities. This study investigates the effectiveness of ensemble learning (EL) algorithms for lithological classification and mineral exploration using EnMAP hyperspectral imagery (HSI) in a semi-arid region. The Moroccan Anti-Atlas mountainous region is known for its complex geology, high mineral potential and rugged terrain, making it a challenging for mineral exploration. This research applies core and heterogeneous ensemble learning methods, i.e., boosting, stacking, voting, bagging, blending, and weighting to improve the accuracy and robustness of lithological classification and mapping in the Moroccan Anti-Atlas mountainous region. Several state-of-the-art models, including support vector machines (SVMs), random forests (RFs), k-nearest neighbors (k-NNs), multi-layer perceptrons (MLPs), extra trees (ETs) and extreme gradient boosting (XGBoost), were evaluated and used as individual and ensemble classifiers. The results show that the EL methods clearly outperform (single) base classifiers. The potential of EL methods to improve the accuracy of HSI-based classification is emphasized by an optimal blending model that achieves the highest overall accuracy (96.69%). The heterogeneous EL models exhibit better generalization ability than the baseline (single) ML models in lithological classification. The current study contributes to a more reliable assessment of resources in mountainous and semi-arid regions by providing accurate delineation of lithological units for mineral exploration objectives. Full article

Background: Cognitive behavioral therapy (CBT) has shown consistent efficacy in individuals with psychosis, as supported by many trials. One classical distinction is that between affective and non-affective psychosis. Few studies have specifically examined the possible moderating role of substantial affective elements. In this systematic review and meta-regression analysis, we assess how CBT response differs across the affective spectrum in psychosis. Methods: We included studies assessing various CBT modalities, including third-wave therapies, administered in people with psychosis. The study protocol is published in the Open Science Framework. Meta-regression was conducted to assess whether the proportion of participants with affective psychosis (AP), as proxied by a documented diagnosis of schizoaffective (SZA) disorder, moderated CBT efficacy across positive, negative, and depressive symptom domains. Results: The literature search identified 4457 records, of which 39 studies were included. The median proportion of SZA disorder participants was 17%, with a total of 422 AP participants represented. Meta-regression showed a trend toward lower CBT efficacy for positive symptoms with a higher SZA disorder proportion (β = +0.10 SMD per 10% increase in AP; p = 0.12), though it was not statistically significant. No significant associations were found for negative (β = +0.05; p = 0.73) or depressive symptoms (β = −0.02; p = 0.78). Heterogeneity was substantial across all models (I² ranging from 54% to 80%), and funnel plot asymmetry was observed in negative and depressive symptoms, indicating possible publication bias. Risk of bias assessment showed the anticipated inherent difficulty of psychotherapies in blinding and possibly dropout rates affecting some studies. Conclusions: Affective symptoms may reduce the effectiveness of CBT for positive symptoms in psychotic disorders, although the findings did not reach statistical significance. Other patient-level characteristics in psychosis could indicate which patients can benefit most from CBT modalities. Full article

Objectives: To evaluate the association between antidepressant use and the risk of venous thromboembolism (VTE), including deep vein thrombosis and pulmonary embolism (PE), through a systematic review and meta-analysis of observational studies. Methods: A comprehensive literature search was conducted in Medline, Embase^®, and Web of Science^® up to December 2024. Eighteen studies (cohort, case-control, and nested case-control designs) meeting inclusion criteria were analyzed. Study quality was assessed using the Newcastle–Ottawa Scale. Pooled relative risks (RR) with 95% confidence intervals (CIs) were calculated using a random-effects model. Subgroup analyses were performed based on recency of antidepressant use, VTE onset type (first vs. recurrent), and VTE subtype (PE). Results: Antidepressant use was associated with a significantly increased risk of VTE (RR = 1.22; 95% CI: 1.12–1.32; p < 0.001). Subgroup analyses revealed a stronger association for recent use (within 90 days), first-onset VTE, recurrent VTE, and PE. Heterogeneity was high (I² = 87.92%), but sensitivity analysis confirmed result robustness. No publication bias was detected. Conclusions: This meta-analysis indicates a modest but statistically significant increase in the risk of VTE associated with antidepressant use, particularly among recent users, individuals experiencing either first-time or recurrent VTE, and those with PE-type events. These findings highlight the importance of individualized VTE risk assessment when initiating antidepressant therapy. Full article