Search Results (5,619)

Background: Post-stroke spasticity is a frequent and disabling consequence of stroke, including when affecting the lower limbs, where it may impair stance, gait, balance, postural control, functional independence and quality of life. Botulinum toxin type A (BoNT-A) is widely used as a focal neuromodulatory treatment for post-stroke spasticity. However, the relationship between BoNT-A-induced reduction in muscle hypertonia, objective changes in spastic muscle’s biomechanical properties, and functional outcomes such as mobility and balance remains insufficiently clarified. This systematic review aimed to synthesize recent evidence regarding the non-invasive assessment of spastic muscle properties following BoNT-A administration in post-stroke patients, with emphasis on mobility and balance outcomes. Methods: A systematic literature review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The search was performed in international electronic databases and included studies published between 1 January 2023 and 31 December 2025. The search strategy used specific keywords and keyword combinations/syntaxes, contextually, related to the topic of interest. Results: A total of 32 studies met the eligibility criteria and were included in the final data analysis and synthesis, comprising 13 primary clinical studies—6 randomized or controlled interventional studies and 7 observational studies—together with 12 reviews or evidence syntheses, 3 technical or clinical framework papers, and 4 survey, epidemiological, health-services or health-economic studies. Overall, the included articles addressed BoNT-A treatment in post-stroke spasticity, with partial focus on muscle properties, gait, mobility, and functional outcomes. However, only a limited number of studies investigated objective non-invasive assessment methods, and few directly related muscle-property changes in balance and mobility outcomes. Formal risk-of-bias assessment and quantitative synthesis were not performed because of the substantial heterogeneity of the included evidence, with only two studies being potentially suitable for pooling and these addressing different muscle groups, interventions, and outcome domains. Discussion and Conclusions: The reviewed literature confirms the clinical relevance of BoNT-A in the management of post-stroke spasticity. However, most studies assess treatment effects mainly through clinical scales, while objective evaluation of muscle stiffness, elasticity, viscoelastic properties, and their relationship with mobility and balance remains limited. Although some studies address gait, functional recovery, or muscle-related changes, the combined use of BoNT-A treatment, myotonometric assessment, and proprioceptive–stabilometric evaluation is largely absent. Therefore, current evidence highlights an important research gap and supports the need for future longitudinal studies integrating non-invasive biomechanical and balance assessment tools to better monitor treatment response and guide individualized neurorehabilitation in post-stroke patients. Full article

Responding to residents’ differentiated health-promoting needs has become important for improving the adaptability of street renewal in old urban neighborhoods. Based on 1404 valid questionnaires from residents in old urban neighborhoods of Jinan, China, this study develops an analytical framework linking group classification, environmental responses, and renewal strategies from the perspective of health literacy–activity behavior mismatch. Health literacy and activity behavior indices were constructed, and K-means clustering was used to identify mismatch groups. Estimated marginal means, average marginal effects, and multiple-response analysis were then employed to compare group-specific response trajectories and improvement preferences across four street environmental dimensions: slow-mobility space, service function, natural aesthetics, and activity facilities. Further interpretation of the obtained analytical results demonstrates that the investigated resident samples are partitioned into four typical subgroups: behavior-driven, high-literacy/high-behavior, literacy-driven, and low-literacy/low-behavior groups. Slow-mobility space was mainly associated with participation willingness and mismatch adjustment; natural aesthetics was primarily related to environmental cognition and perceived attractiveness; activity facilities were more relevant to mismatch changes among low-literacy/low-behavior residents; and service function mainly provided everyday convenience support. Improvement preferences were generally concentrated on basic environmental conditions, especially traffic safety, natural environment, and public activity spaces. These findings provide empirical evidence for group-based health-promoting street renewal and highlight its relevance to socially inclusive and sustainable urban regeneration. Full article

This paper develops an exploratory agent-based model of mediated vulnerability in deafblindness-related social exclusion. The revised model treats exclusion as a relational process shaped by multidimensional mediation, education, income and local interaction. Access to social-health mediation is defined as a composite construct that can be decomposed into communication support, mobility and orientation support, health-care continuity, educational and assistive support, and administrative recognition. The reported NetLogo implementation analyses the aggregate access variable generated in BehaviourSpace, while the revision makes explicit the subdimensional update rules required for future empirical calibration. The simulation begins with 1000 agents and runs for 500 ticks. The analysed export contains 1593 runs across six values of risk threshold, with 300 runs for each threshold from 0.1 to 0.5 and 93 runs for threshold 0.6. The results distinguish mediated vulnerability, continuous exclusion, binary exclusion, episodic exclusion and consolidated exclusion. Peak exclusion remains substantial across threshold conditions, whereas final binary exclusion is almost absent under the implemented averaging rules. One-way and Welch ANOVA show that risk-threshold does not significantly affect peak exclusion, mean exclusion or final exclusion, but it has a very strong effect on education and derived social power. Regression models indicate that mean access and mean income are the strongest predictors of exclusion severity, while risk-threshold has no significant direct effect after these variables are included. External validation is treated as a pattern-oriented comparison rather than a prevalence prediction: the model is consistent with the empirical claim that exclusion among persons with deafblindness is mediated by communication, mobility, education, health-care and economic barriers, but it should not be read as an estimate of real-world prevalence. Full article

Visible solid waste pollution in water bodies has intensified, threatening ecosystems and public health. This study proposes a low-complexity approach based on Convolutional Neural Networks (CNNs) for the automatic detection of visible litter in rivers using images. The methodology involves a curated dataset from multiple sources and the application of Transfer Learning with the MobileNetV2 architecture, chosen for its computational efficiency. The model achieved stable performance across 20 independent runs, with an average test accuracy of 89.7%, an F1-score of 90.9%, and an AUC of 0.996. Notably, the representative model selected for qualitative illustration produced zero false negatives on the test set; this result reflects the behavior of a specific model instance and should be interpreted as an illustrative outcome rather than the guaranteed operational performance of the method. The results indicate that the proposed approach is a viable, scalable, and accessible technological alternative for automated river monitoring. Future integration with web applications and geospatial platforms could enhance its utility for environmental agencies and public managers. Full article

The gut microbiome of rainbow trout (Oncorhynchus mykiss) and Atlantic salmon (Salmo salar) is increasingly recognized as a functional interface linking dietary inputs, epithelial barrier integrity, mucosal immunity, environmental stress, disease susceptibility, and antimicrobial-resistance risk in intensive aquaculture. Based on available salmonid studies and relevant evidence from broader fish and aquaculture systems, this review synthesizes current knowledge on salmonid gut microbial composition, nutritional modulation, microbiome–mucosal immune interactions, aquaculture stressors, antibiotic exposure, antibiotic resistance genes (ARGs), mobile genetic elements (MGEs), metagenomics, multi-omics, and emerging microbiome-informed decision-support tools. Current evidence does not support a universally stable single-core microbiota in these species. Instead, community structure is shaped by developmental stage, freshwater–seawater transition, intestinal segment, digesta versus mucosa sampling, diet, temperature, stress, health status, and methodological workflow. Feed substitution and functional additives can remodel the gut microbiota, but these shifts should be interpreted alongside histology, barrier function, metabolic profiles, immune indicators, and disease-resistance phenotypes. Antibiotic exposure may reduce acute bacterial disease pressure while disturbing community structure and potentially enriching ARGs or ARG–MGE associations. Risk assessment should therefore move beyond ARG abundance toward host–ARG–MGE linkage using shotgun metagenomics, metagenome-assembled genomes, long-read sequencing, Hi-C, and externally validated multi-omics models. Machine learning and artificial intelligence approaches may support feature screening, risk stratification, and decision support, but their application in salmonid gut-health management remains at an early stage and requires external validation across sites, production stages, diets, and seasons. Full article

Within the food industry, research on mobile gastronomy has increased from the consumer perspective. Food trucks play an important role as economic units worldwide, serving as a culinary alternative to traditional restaurants. They have emerged as an innovative initiative and business model that offers a disruptive alternative to home cooked meals. One of the aspects most appreciated by consumers is the charcoal-grilled food offered by food trucks. Globally, charcoal is widely used as an energy source and cooking fuel, with an annual production of approximately 53.2 million tons. Its characteristics and low cost make charcoal a dominant energy resource, and it plays a fundamental role in cooking in both low- and high-income countries due to the distinctive flavor and texture it imparts to food. Research has focused on air pollution and health risks, supplemented with information on the types of charcoal, characteristics and properties, production techniques, and added value. Charcoal ash residue production has not been fully analyzed, providing an opportunity for research to obtain data and evaluate various criteria, such as kilograms of charcoal purchased and food trucks’ residual charcoal ash. To address this gap, the authors propose a horizontal collaboration perspective through the application of the COHRV model to (1) collect data and create a database from food-truck business owners in Ciudad Juarez, Chihuahua; (2) develop a circular economy model for charcoal ash as a sustainable strategy within the food industry; and (3) estimate charcoal consumption during the grilling process and the generation of charcoal ash residue in the food truck sector. Full article

Cross-border mobility (CBM) is highly sensitive to policy shocks during public health crises, yet its behavioral and demographic dynamics remain poorly understood. CBM disruptions can be conceptualized as differentiated responses to non-pharmaceutical interventions (NPIs) across demographic groups in integrated cross-border systems. Focusing on the Shenzhen–Hong Kong cross-border mobility corridor, causal evidence shows that NPIs generate both immediate and uneven mobility contractions. These responses are structured along gender and age lines: younger individuals and males exhibit more elastic and rapid behavioral adjustments, whereas females demonstrate greater stability and faster recovery. In contrast, older adults show limited initial responsiveness but prolonged recovery, indicating persistent structural constraints. These findings identify vulnerable populations and provide empirical evidence for designing targeted, equitable border management and transportation policies in highly integrated regions during future public health crises. Full article

Background. Orthotic and prosthetic devices for general-use and activity-specific function can provide critical preventive health benefits for individuals with limb loss, limb difference, and mobility impairments, and yet coverage remains inconsistent across U.S. states. Objective. To evaluate the fiscal impact of clarifying insurance coverage for orthotic and prosthetic devices across 23 states lacking comprehensive coverage. Methods. A cost consequence analysis was conducted using data from the U.S. Census Bureau, Kaiser Family Foundation, Government Accountability Office, and a recent actuarial analysis informing baseline cost, coverage, and prevalence assumptions. Per-member-per-month (PMPM) cost increases were compared against device enabled preventive health savings to estimate net fiscal impact. Sensitivity analyses modeled three scenarios based upon a combination of uptake (% eligible individuals accessing device) and physical activity equivalent annual cost saving, respectively: conservative (25% uptake, $1000), moderate (50% uptake, $2500), and high-impact (75% uptake, $5000). Return on investment (ROI) was calculated for the moderate scenario as the ratio of annual savings to implementation cost. Results. Under the assumptions of the moderate scenario, projected ROI remained positive across all states, ranging from approximately 1.5× in Florida to over 114× in Vermont, with 78% of states (18 of 23 states) demonstrating returns greater than 4×. Moderate scenario annual net savings ranged from approximately $10.8 million in Vermont to $437.0 million in California, with substantial projected savings also observed in Florida ($235.5 million), New York ($225.2 million), and Virginia ($143.8 million). PMPM cost increases for 70% of states range between $0.03 and $0.43, with all modeled states remaining below $1.46. Discussion. In our healthcare system dominated by high-cost and reactive care, the ROI obtained by this cost-consequence analysis (CCA) using evidence-based assumptions supports orthotic and prosthetic coverage clarification as preventive interventions to restore function. Full article

Young Black women face barriers to exercise and elevated cardiometabolic risk, yet resistance exercise (RE) remains underutilized despite its benefits. We evaluated the feasibility and acceptability of a 24-week culturally adapted RE intervention + text messages in young Black women. Participants were randomized to the motivational exercise group (MEG; n = 14) or the standard exercise group (SEG; n = 13). Both groups received 10 and 11 weeks of supervised (by a Black woman) and unsupervised RE. MEG received additional cultural adaptations and weekly discussions to build competence, autonomy, and self-regulation strategies + mobile support. Feasibility and acceptability were assessed via recruitment, consent, and retention rates, adherence, and thematic analysis of semi-structured interviews. Recruitment and consent rates were 97.2% and 100.0%, respectively. Retention rates were 93.3% (MEG) and 86.7% (SEG) at 12 weeks, and 93.3% and 80.0% at 24 weeks, respectively. Supervised adherence was 93.9% and 88.8% in MEG and SEG, and 14.3% and 15.4%, respectively, during unsupervised RE. Participants desired continued support and a more tailored mobile experience during unsupervised RE. Supervised RE with ethnically matched trainers was feasible and acceptable. Future interventions should incorporate mobile tools with tailored feedback and accountability strategies to sustain long-term RE to improve health outcomes in this population. Full article

Background/Objectives: Oral diseases affect around 3.5 billion people worldwide and remain a major public health burden. Adolescence represents a critical stage for establishing lifelong oral health behaviours, particularly given the widespread use of smartphones in this age group. This review aimed to synthesise available evidence on the use of mobile health (mHealth) applications to promote oral health among adolescents, identify app features, evaluate their efficacy in improving oral health outcomes and behaviours, and explore barriers and challenges to their use. Methods: A comprehensive review was conducted across PubMed, Scopus, the Cochrane Library, and Web of Science. Studies published between 2010 and 2025 in English, Portuguese, or Spanish that evaluated oral health apps targeting adolescents were included. Data were extracted regarding study design, sample characteristics, app features, clinical and behavioural outcomes, and barriers to app use. Methodological quality was assessed using RoB 2, ROBINS-I, and the JBI checklist, as appropriate. Results: Twenty-five studies met the inclusion criteria, comprising 19 randomised controlled trials, 3 qualitative studies, and 3 non-randomised trials. Common app features included educational content, brushing timers, reminders, gamification, and communication with professionals. Most studies demonstrated improvements in plaque and gingival indices, brushing frequency, and oral health knowledge, particularly when apps incorporated behaviour change techniques. However, long-term adherence, usability issues, and lack of regulation remain major limitations. Conclusions: mHealth applications show promise as complementary tools for promoting oral health in adolescents. Their success depends on sustained engagement, evidence-based content, user-centred design, and integration with traditional preventive approaches. Full article

Public lighting can account for nearly 40% of municipal energy consumption in some European cities and plays a vital role in road safety, mobility, and the quality of public spaces. Despite notable efficiency gains from the widespread adoption of light-emitting diode (LED) technologies, the technical outputs of standards-based and installation-level assessment methods are not usually simple and communicable energy-performance labels for municipal decision-making. This study addresses this issue by introducing an algorithm-based framework for classifying energy performance in public lighting at the road-segment level. This approach translates existing lighting standards and efficiency indicators into a straightforward and understandable energy label, adapting the energy labelling concept, commonly used for buildings and appliances, to public space infrastructure. This framework is implemented through a national digital platform for public lighting classification, which has already attracted formal interest from more than 100 municipalities, indicating strong institutional uptake. The results indicate that road-segment-level energy classification is feasible and scalable as a voluntary tool to enhance municipal accountability and support informed decision-making. This study concludes that algorithmic energy labels for public lighting can support sustainable urban governance transparency, comparability and decision-making capacity, with future research aimed at building capacity for large-scale implementation and incorporating environmental, human health, and ecological impact considerations into the classification system. Full article

Zanthoxylum bungeanum alkaloids have attracted considerable attention for their potential health benefits, yet systematic investigations into their extraction, purification, and comprehensive bioactivity remain scarce. In this study, an efficient extraction protocol was developed and scaled up, followed by purification using macroporous resin NKA-9 with 70% ethanol as the optimal eluent. Ultra-performance liquid chromatography coupled with ion mobility quadrupole time-of-flight mass spectrometry (UPLC-IM-QTOF/MS) identified 11 major alkaloids in the 70% ethanol eluate fraction. The antioxidant capacity of the 70% ethanol eluate fraction was evaluated through DPPH, ABTS⁺·, and Fe³⁺ reducing power assays, revealing a clear dose-dependent effect, albeit weaker than ascorbic acid. Antibacterial screening against four pathogenic bacteria (Escherichia coli, Bacillus subtilis, Staphylococcus aureus, and Pseudomonas aeruginosa) via the Oxford cup method, macrobroth dilution, and minimum bactericidal concentration (MBC) determination demonstrated strain-selective activity. The strongest effect was observed against E. coli [minimum inhibitory concentration (MIC) = 2 mg/mL, MBC = 8 mg/mL, MBC/MIC = 4, bactericidal], followed by moderate activity against B. subtilis (MIC = 4 mg/mL, MBC = 16 mg/mL), while only bacteriostatic effects were noted against S. aureus and P. aeruginosa within the tested range. These findings provide a robust foundation for further development of Zanthoxylum bungeanum alkaloids as natural functional ingredients or food-compatible bio preservatives. Full article

Background/Objectives: Physical activity (PA) and body mass index (BMI) are two central modifiable determinants of cardiometabolic health and functional performance across the adult lifespan. Excess adiposity and physical inactivity frequently coexist and may interact in determining functional aging trajectories. However, evidence from real-world primary care populations examining whether PA–cardiometabolic associations are consistent across BMI categories—including individuals with obesity—remains limited. This study evaluated the associations between self-reported PA categories and LDL-C concentrations and timed up and go (TUG) functional performance across three WHO-defined BMI categories and formally tested whether BMI category modified these associations. Methods: This cross-sectional observational study included 863 adult primary care patients stratified into normal weight (BMI < 25 kg/m², n = 241), overweight (BMI 25–29.9 kg/m², n = 348), and obese (BMI ≥ 30.0 kg/m², n = 274) groups. PA was categorized as low, moderate, or high based on World Health Organization recommendations. LDL-C and TUG were the primary outcomes. BMI-category-stratified analyses included one-way ANOVA with Bonferroni post hoc correction and multivariable linear regression adjusted for age, sex, arterial hypertension (AH), and diabetes mellitus (DM). An interaction term (PA × BMI category) formally tested BMI modification. Results: Age, LDL-C, TUG, sex, AH, DM, and PA distribution did not differ significantly across BMI categories (all p > 0.05). Higher PA categories were associated with significantly lower LDL-C in all three BMI categories (normal: F = 8.93, p < 0.001; overweight: F = 10.53, p < 0.001; obese: F = 9.35, p < 0.001) and with significantly better TUG performance (normal: F = 18.17, p < 0.001; overweight: F = 41.62, p < 0.001; obese: F = 21.14, p < 0.001). PA was the only consistently significant independent predictor of both LDL-C (all p < 0.001) and TUG (all p < 0.001) in all three BMI categories after multivariable adjustment. The interaction term (PA × BMI category) was not statistically significant for LDL-C (p = 0.972) or TUG (p = 0.475). The proportion of patients with TUG ≥12 s among low-PA patients increased across BMI categories: 33.7% in patients with normal weight, 37.5% in patients with overweight, and 42.3% in patients with obesity. Conclusions: PA–cardiometabolic and PA–functional performance associations were consistent across all three BMI categories, with no statistically significant BMI modification detected. These findings support the potential clinical utility of routine PA assessment as a BMI-independent indicator of cardiometabolic risk and functional health in primary care, including in individuals with obesity, and are relevant to healthy aging and maintaining mobility and functional independence across the adult lifespan. Full article

The growing aging population is a primary driver of chronic, long-term health conditions. The rising prevalence of cognitive decline in older populations is a pressing public health issue due to its impact on health and social care and its emotional toll on family members. A lesser-known condition is sarcopenia—the age-related debilitating loss of skeletal muscle mass and function which leads to weakness and loss of mobility, quality of life and social independence. Neither health condition has a clear pharmacological treatment pathway. Diet and nutrition have therefore received the most attention for disease prevention. This review evaluates the research on the association between sarcopenia and cognitive decline and how both conditions may be linked to protein intake. While findings can be inconclusive or contradictory, a higher consumption of protein may protect against declines in physical and cognitive health, either acting separately or synergistically with exercise. The evidence supports the recommendation for a daily intake of protein higher than the current guideline of 0.8 g/kg/d for older people. Evidence suggests that healthy dietary patterns such as the Mediterranean diet appear to positively influence cognitive health in older people. Furthermore, the impact of specific high-protein foods, including egg, soy and dairy foods, on cognitive health has been reviewed, again with a suggestion that their consumption may mitigate against cognitive decline. Functional foods aimed at the aging population who wish to increase their protein intake and avert or delay the onset of these health conditions could play an important role in preventive nutrition, especially if they are formulated around the protein-rich foods which appear to positively impact cognitive health. Full article

Background: With the vast and fast-growing number of mHealth applications supporting health, disease management and self-care for older people, the usability of these applications has become a critical factor determining their acceptance and usage. In order to develop mHealth applications suitable for the aging population, it is important to investigate the relationship between older people’s experience with mobile technology in the past, their perception of the usability of mHealth applications and their subsequent use of these applications. Objective: This study investigated the impact of the length of mobile usage on the perceived mHealth application usability of older adults, and the impact of mHealth application usability on the mHealth application user satisfaction and frequency of use of older adults. Methods: This study is based on a cross-sectional survey among older individuals in Al-Ahsa, Saudi Arabia. The measurement model consisted of five distinct constructs with fifteen corresponding indicators including efficiency, learnability, memorability, error handling, and user satisfaction. In terms of analysis, this study included reliability and descriptive statistics as well as correlation and regression analysis, as well as simple and bootstrapped mediation analysis, and, finally, confirmatory factor analysis (CFA) and structural equation modeling (SEM). Based on discriminant validity, the findings suggest that four first-order dimensions, efficiency, learnability, memorability, and error handling, constitute second-order usability dimensions. Results: A total of 271 older adults were included in the final analysis. All constructs demonstrated satisfactory reliability and convergent validity, with Cronbach’s alpha values ranging from 0.797 to 0.862, Composite Reliability values ranging from 0.798 to 0.860, and Average Variance Extracted values ranging from 0.568 to 0.673. Structural equation modeling revealed that mobile usage duration significantly influenced usability (β = 0.616, p < 0.001), usability significantly influenced user satisfaction (β = 0.953, p < 0.001), and user satisfaction significantly influenced use frequency (β = 0.193, p = 0.002). The second-order structural model demonstrated excellent fit to the data (χ²/df = 1.824, CFI = 0.972, TLI = 0.966, GFI = 0.940, AGFI = 0.928, RMSEA = 0.055). Conclusions: Usability plays a central role in explaining the satisfaction of older people with mHealth services and their continuous use of applications. Older people’s experience with their smartphones is associated with their perceptions of the usability of mHealth applications. Higher perceived usability of mHealth applications is positively associated with greater user satisfaction and more frequent use of these applications among older adults. The findings are in line with a usability-centered technology acceptance model. Design of mHealth services should be based on user-centered design principles. In addition to other design principles, efficiency, learnability, memorability, error handling and other usability principles should be particularly addressed in order to increase acceptance of mHealth services by older people. Full article