Search Results (6,655)

Deep wounds often lead to severe complications such as persistent infection, biofilm formation, and high patient morbidity. While skin injuries can usually be managed with functional dressings, wounds in deep layers without sufficient treatment may serve as primary entry points for bacterial infection, thereby posing a significant life-threatening risk to patients. With the rising prevalence of chronic diseases and an aging population, effective strategies for enhanced wound healing are still in high demand. In this study, an injectable and thermoresponsive hexamethylene diisocyanate–Pluronic F127 copolymer–hyaluronic acid composite hydrogel loaded with polyhexamethylene biguanide (PHMB) and epidermal growth factor (EGF), named PEHHPG, was developed for joint therapy of deep wounds. PEHHPG self-gels at 37 °C and stabilizes both agents in the gel matrix. Based on the results of microbial colony assay and analysis of fibroblast growth kinetics, PEHHPG with ≥200 ppm of PHMB and ≥0.15 μg/mL of EGF can eradicate bacteria and enhance cell proliferation in vitro, illustrating the functionalities of PEHHPG. Given the aforementioned effects, together with the recognized advantages of injectable hydrogels such as wound shape/depth adaptation, low adhesiveness, exudate absorptiveness, and moisture maintenance, the developed PEHHPG is anticipated to be a feasible dressing material for deep wound treatment after further in vivo examinations. Full article

The absence of a culturally adapted instrument to assess menopause-specific quality of life in Vietnamese women limits both clinical practice and research in this population. This study aimed to translate, culturally adapt, and psychometrically validate the Vietnamese version of the Utian Quality of Life (VN-UQOL) Scale. A cross-sectional design was employed with 384 community-dwelling postmenopausal women aged 46–65 years. The UQOL was translated and adapted following established guidelines, including forward-back translation, expert review, and pilot testing. Internal consistency was evaluated using Cronbach’s alpha, construct validity through confirmatory factor analysis (CFA), and concurrent validity via Pearson correlations with the Vietnamese Menopause Rating Scale (VN-MRS). The VN-UQOL demonstrated excellent internal consistency, with a total scale Cronbach’s alpha of 0.87 and sub-scale alphas ranging from 0.81 to 0.93. Content validity indices (I-CVI, S-CVI) were 1.0. CFA confirmed the original four-factor structure, with all factor loadings exceeding 0.50 and good model fit indices (CFI = 0.921, RMSEA = 0.072). Concurrent validity was supported by significant negative correlations between the VN-UQOL sub-scales and corresponding VN-MRS domains (p < 0.01). The VN-UQOL is a reliable and valid instrument for assessing menopause-specific quality of life in Vietnamese women, providing a valuable tool for clinical practice and research in this underserved population. Full article

Background and Objectives: Artificial intelligence (AI) is increasingly integrated into healthcare management and pharmaceutical marketing workflows, yet determinants of AI adoption intention among non-clinical professionals remain under-studied in Central and Eastern Europe. This cross-sectional study quantified AI adoption intention (AAI) across three professional groups and examined its organizational, cognitive, attitudinal, and regulatory correlates. Methods: We surveyed 127 Romanian professionals (43 hospital administrators, 42 pharmaceutical marketing professionals, 42 community pharmacy managers) using a 46-item structured instrument. The instrument combined items adapted from UTAUT/TAM and organizational-readiness measures with study-specific AI-marketing, AI-literacy, and regulatory-literacy items; Analyses included ANOVA with Tukey HSD, Spearman correlations, age-adjusted OLS regression with HC3 robust standard errors, bootstrap indirect-effect analysis, moderation, exploratory k-means clustering, and exploratory logistic/ROC analysis. Results: AAI differed across groups: pharmaceutical marketing 4.33 ± 0.50, hospital administrators 3.39 ± 0.47, and pharmacy managers 2.88 ± 0.54; all pairwise Tukey contrasts p < 0.001. In the multivariable model (R² = 0.833)—interpreted cautiously because conceptually related adoption constructs may overlap despite acceptable collinearity diagnostics—perceived usefulness, organizational readiness, and perceived ease of use were the strongest associated factors, while data governance concern was the main negative correlate. Perceived usefulness statistically accounted for 61.7% of the AI literacy–AAI indirect association, and regulatory literacy moderated the AI literacy–AAI association. An exploratory age-adjusted logistic model showed high within-sample discrimination for top-tertile AAI but should be interpreted as convergent validity among survey constructs rather than as a validated screening tool. Conclusions: AI adoption intention in Romanian medical management and pharmaceutical marketing is associated mainly with perceived usefulness and organizational readiness, tempered by data governance concern and regulatory knowledge. Longitudinal, multi-site, real-world implementation studies with external validation are needed. Full article

Background/Objectives: Early and accurate discrimination of neurological conditions, dementia, stroke and healthy aging, remains a critical clinical challenge. Electroencephalography (EEG) is a non-invasive measure of brain dynamics and entropy-based features obtained from multichannel EEG have shown strong discriminative ability. However, existing deep learning approaches do not sufficiently address the combined challenges of small clinical cohorts and high-dimensional entropy feature spaces. In this study, a novel architecture is proposed for multi-class neurological EEG classification under extreme small-sample conditions. Methods: A novel dual-branch Channel-wise Transformer and Attention-Branch Network (EEG-ChTABNet) are pr to classify 19-channel EEG entropy features into three classes (dementia, stroke, healthy control; N = 45; 15 per class). The architecture suggests four new designs. First, the Channel Importance Attention (CIA) block, which adaptively learns to re-weight the importance of electrodes via squeeze-excitation. Second, the dual-branch encoder, which combines the global multi-head self-attention with the local depthwise-separable convolution. Third, the gated sigmoid fusion mechanism. Fourth, the bottleneck residual classification head, to solve overfitting. Eight entropy feature sets: Amplitude-Aware Permutation Entropy (AAPE), Attention Entropy (AttEn), Dispersion Entropy (DisEn), Distribution Entropy (DistrEn), Fluctuation-based Dispersion Entropy (FDispEn), Fuzzy Entropy (FuzEn), Linear Gaussian Estimation of the Conditional Entropy (LinEn), and Symbolic Dynamics (SyDy) were evaluated individually with stratified 5-fold cross-validation on within-fold SMOTE augmentation. Results: EEG-ChTABNet consistently outperformed the baseline Transformer on all 8 feature sets. DisEn and SyDy features yielded peak classification accuracy of 73.3% (AUC: 0.823 and 0.857, respectively) compared to the corresponding baseline of 57.8% and 55.6%. SyDy achieved the best overall AUC of 0.857 and the dementia detection sensitivity was up to 86.7% over multiple feature sets. Conclusions: EEG-ChTABNet shows the effectiveness of channel-adaptive, dual-branch Transformer Designs for EEG-based neurological classification from Small-Sample Entropy Feature Data, and Identifying SyDy and DisEn as the Most Discriminative Feature Representations for Three-Class Neurological EEG Classification. Full article

Background: Diabetes-related stigma is an underrecognized psychosocial factor that may contribute to emotional burden among individuals with diabetes. In Saudi Arabia, where the prevalence of diabetes is among the highest globally, limited evidence exists on how stigma across different social contexts influences interpersonal diabetes distress. We aimed to assess the association between diabetes-related stigma and interpersonal diabetes distress and to determine whether these associations differed across family, workplace, and healthcare stigma domains among adults with diabetes in Saudi Arabia. Methods: This cross-sectional study analyzed survey data collected from 438 patients with diabetes. Diabetes-related stigma was measured using an adapted 12-item diabetes stigma scale covering family, workplace, and healthcare domains, while interpersonal diabetes distress was assessed using the Interpersonal Distress subscale of the Diabetes Distress Scale (DDS). The relationships between stigma and distress were estimated using multiple linear regression analysis adjusted for age, gender, education level, years since diagnosis, and presence of complications. Results: Participants reported moderate levels of stigma (mean: 2.50, SD: 1.08) and interpersonal distress (mean: 2.31, SD: 1.23). Higher stigma scores were strongly associated with greater interpersonal distress (β = 0.57, 95% CI: 0.48 to 0.66). Domain-specific analysis showed that workplace (β = 0.26, 95% CI: 0.10 to 0.42) and healthcare stigma (β = 0.23, 95% CI: 0.07 to 0.38) were significantly associated with distress, while family stigma was not. Individuals with diabetes complications had higher distress (β = 0.49, 95% CI: 0.25 to 0.73). No evidence of effect modification by gender or education was observed. Spline models confirmed a positive and strengthening association at higher levels of stigma. Conclusions: Diabetes-related stigma is a strong and consistent factor associated with interpersonal diabetes distress in Saudi Arabia, with workplace and healthcare stigma demonstrating the strongest associations. These findings highlight the importance of addressing stigma within both social and healthcare environments and suggest that stigma reduction strategies may help alleviate the psychosocial burden associated with diabetes. Full article

Millions of chicks are hatched daily in commercial hatcheries and due to ease of access and the large availability of chicks produced daily, such chicks have been accepted as a reference and control. Unfortunately, this is not a correct assumption. Chickens evolved to be hatched in nests and to remain in close contact with adult hens, which is important for the transfer of chicken-adapted microbiota from hens to offspring. In the absence of adult hens, chicks from hatcheries are colonised by microbiota of environmental origin. Forgetting this fact has led to many confounding conclusions, including a dogma on the age-dependent development of gut microbiota. In this sense, chicks from hatcheries represent a threat. However, if correctly perceived, the same chicks represent a unique opportunity for host–microbiota studies since there is no alternative animal model in which offspring free of any paternal influence are that readily available. Full article

Real-time precise point positioning (PPP) is increasingly supported by open satellite-broadcast state-space representation (SSR) services, yet standalone operation with a single service remains vulnerable to limited constellation support, correction outages, latency variations, and service-dependent modeling inconsistencies. In the Asia-Pacific region, MADOCA-PPP and PPP-B2b provide two publicly accessible and complementary SSR sources, but their consistent fusion before user-level PPP estimation remains insufficiently investigated. This paper proposes a correction-domain fusion framework that combines MADOCA-PPP and PPP-B2b orbit and clock corrections before PPP estimation, rather than merging final positioning solutions. Inter-service discrepancies and unknown cross-correlations are handled by a bias-state-aware structured covariance intersection strategy, in which the relative weighting is derived from the respective correction information (inverse variance), preserving statistical consistency and avoiding overconfident fusion. A unified multi-GNSS PPP scheme further supports signal-priority harmonization, broadcast-ephemeris adaptation, correction-age control, and GLONASS inter-frequency and differential code bias handling. Static-station per-epoch (pseudo-kinematic) and offshore kinematic experiments validate the framework. In the static-station test, fusion raised the mean number of valid satellites from 21.98 and 14.98 to 26.56 and improved the horizontal RMS to 0.033 m—better than either standalone service (0.037 m, 0.079 m)—confirming a genuine combination rather than source selection, while the 3D RMS (0.068 m) matched the best standalone service (0.066 m). In the offshore test, fusion achieved the best overall accuracy (0.232 m horizontal, 0.290 m 3D, versus 0.332 m and 0.313 m for the standalone services) and the most satellites (25.4). It also degraded most slowly with increasing elevation cut-off, outperforming both services about threefold at 40°. A normalized-innovation-squared check confirmed the fused covariance is consistent and not overconfident (median ≈ 1.1; within the 99% bound in 100% of epochs). Under single-service outages from 30 s to 600 s, fusion maintained 100.0% availability, confirming its advantage in redundancy, continuity, and resilience. Full article

Background: The relationship between physical exercise and human longevity constitutes one of the most consequential intersections in contemporary preventive medicine. Although international guidelines recommend 150 min of moderate-intensity exercise weekly, growing evidence suggests that the architecture of optimal exercise is far more complex, encompassing dose, modality, timing across the lifespan, and the paradox risks imposed by extreme endurance. Methods: We included in this narrative review landmark cohort studies, randomized controlled trials, meta-analyses, and expert physiological frameworks published in high-impact cardiovascular, sports medicine, and longevity journals from 1966 to 2024. Results: Cardiorespiratory fitness (CRF), indexed by maximal oxygen uptake (VO₂ max), demonstrates the strongest and most linear dose–response relationship with all-cause mortality identified in preventive medicine, with every 1 metabolic equivalent of task (MET) increment associated with a 12–15% reduction in mortality risk. The optimal dose of vigorous-intensity exercise follows a J-shaped dose–response curve: 3–5 sessions per week generating 1–2.4 h of vigorous activity is associated with the lowest all-cause mortality risk in large prospective cohorts, whereas chronic extreme endurance exercise incurs measurable atrial remodeling, patchy myocardial fibrosis, and a 5.3-fold increase in the risk of atrial fibrillation. The importance of exercise types shifts profoundly across the lifespan, transitioning from aerobic capacity effort in the third decade to resistance training in the seventh decade and neuromuscular stability in the eighth. Based on our interpretation of the available evidence, we propose a structured, personalized four-step exercise pathway integrating CRF assessment, lifespan-adapted prescription, lifestyle co-interventions, and periodic reassessment. Conclusions: Among currently available lifestyle interventions, regular exercise is consistently associated with some of the largest and most reproducible reductions in all-cause and cardiovascular mortality observed in prospective cohort data, while remaining accessible and cost-effective. Full article

Background/Objectives: Age-related functional decline is increasingly linked to chronic low-grade inflammation (inflammaging) and sarcopenia, two interconnected processes contributing to frailty, metabolic dysregulation, and impaired physical function. These conditions share several underlying mechanisms, including immune dysregulation, mitochondrial dysfunction, oxidative stress, and impaired anabolic signaling. This narrative review critically evaluated the mechanistic and translational interactions between natural bioactive compounds and lifestyle interventions in modulating inflammaging and sarcopenia. Methods: Evidence from molecular, experimental, epidemiological, and clinical studies was synthesized to examine the effects of bioactive compounds—including polyphenols, flavonoids, carotenoids, and omega-3 fatty acids—as well as physical activity and dietary patterns. Particular emphasis was placed on inflammatory regulation, redox homeostasis, mitochondrial adaptation, and muscle metabolism, including NF-κB, AMPK–mTOR, and Nrf2 signaling pathways. Results: Observational studies and randomized controlled trials generally indicate that anti-inflammatory dietary patterns and regular physical activity are associated with improved muscle strength, physical performance, and inflammatory status in older adults. Mechanistically, nutritional bioactives and exercise appear to converge on several pathways involved in mitochondrial function, oxidative stress, anabolic signaling, and immune activation. Emerging evidence suggests potential convergence and interaction of biological pathways affected by nutritional and lifestyle interventions; however, formal evidence demonstrating true synergistic effects in humans remains limited. Nevertheless, substantial heterogeneity persists regarding intervention protocols, dosage strategies, bioavailability, and long-term clinical outcomes. Conclusions: Natural bioactive compounds and lifestyle-based interventions represent promising approaches for targeting biological processes implicated in inflammaging and sarcopenia. By integrating current evidence within a hormesis-oriented geroscience framework, this review highlights the importance of adaptive redox regulation, metabolic resilience, and evidence-based lifestyle strategies in healthy aging. Future well-designed longitudinal and intervention studies are needed to clarify the clinical relevance of these interactions and optimize translational implementation. Full article

Background and Objectives: Seizures and epilepsy are common in children with life-limiting illnesses, particularly in the context of severe neurological impairment. However, data on the clinical profile of these patients in paediatric palliative care are limited, and the lack of standardised protocols adapted to this context represents a clinical challenge. To assess the prevalence of epilepsy and associated clinical characteristics in children receiving paediatric palliative care and to develop a clinical protocol for the management of seizures based on expert consensus. Materials and Methods: A retrospective observational study was conducted, based on the analysis of clinical data from children registered in a paediatric palliative care service (Lumina Association, Romania). Demographic, diagnostic, neurological status and anticonvulsant treatment data were collected. Based on the results obtained and the existing literature, a clinical protocol was developed using a modified Delphi method approach, involving a multidisciplinary panel of experts and two rounds of evaluation of clinical statements. Results: A total of 101 patients (54.5% boys and 45.5% girls) were included, with a mean age of 7.2 ± 4.7 years. Epilepsy was documented in 32.7% of patients and was significantly associated with a neurological diagnosis (p = 0.008), severe neurodevelopmental delay (p = 0.032) and severe motor impairment (p = 0.036). The Delphi process led to the validation of 13 clinical recommendations, the majority of which achieved a strong level of consensus (>85%). Conclusions: Epilepsy is common and closely associated with severe neurological impairment in paediatric palliative care. The integration of systematic neurological assessment and the implementation of a consensus-based clinical protocol can support a more structured approach to seizure management in paediatric palliative care. Full article

Foundation models (FMs) are increasingly proposed as general-purpose solutions for computational pathology, with the potential to simplify clinical artificial intelligence deployment by reducing the need for task-specific architectures. However, their reliability across cancer domains with distinct morphological characteristics remains unclear, limiting confidence in real-world clinical use. We benchmarked seven general-purpose pathology FMs and three domain-specific FMs across eleven patch-level datasets spanning three clinically relevant domains: pediatric hematology, prostate cancer, and breast cancer, using both linear probing and last-layer fine-tuning adaptation strategies. By jointly evaluating pediatric leukemia, male-predominant prostate cancer, and female-predominant breast cancer, this study is, to our knowledge, the first to explicitly examine specialist-versus-generalist FM behavior across age- and sex-stratified cancer populations. Performance differences were strongly domain dependent. In hematology, the specialist FM DINOBloom matched and, in several datasets, marginally exceeded leading generalist models (AUC 0.990–0.999 vs. GigaPath 0.981–1.000), suggesting advantages for highly distinctive cellular morphology. In prostate cancer grading, the generalist FM UNI2-h consistently outperformed the specialist HistoEncoder (AUC 0.956–0.977 vs. 0.908–0.964). In breast cancer, UNI2-h achieved the best overall performance across all tasks. No publicly available breast-cancer-specific FM currently exists for direct comparison; therefore, breast cancer results characterize general FM transferability rather than specialist-versus-generalist differences. Importantly, cross-dataset experiments revealed substantial performance degradation under dataset shift in both prostate and breast cancer, indicating that current FMs are not yet robust enough for heterogeneous multi-site clinical use. These findings support the use of generalist FMs as efficient backbones for well-characterized single-site, patch-level tasks, while challenging the assumption that high benchmark performance necessarily reflects true clinical readiness and demonstrating that pathology FMs are not uniformly superior to specialist models. Full article

Driven by global population aging, long-term in-home and institutional elderly care faces challenges in delivering continuous, privacy-aware, and resource-efficient safety and health monitoring. Existing edge-based solutions struggle to jointly balance detection accuracy, privacy, and resource overhead during continuous operation, and often have limited situational awareness and inflexible management. We propose EdgeElderCare, a resource-aware, scene-adaptive edge-cloud collaborative system for continuous elderly safety and health monitoring. Its contributions are threefold: (1) a scene-adaptive multi-sensor task-sharing architecture that deploys vision-based fall detection in public areas and privacy-aware millimeter-wave radar in private spaces. Combined with edge-side task scheduling, it provides spatially complementary coverage of public and private areas, mitigates the accuracy–privacy conflict, and reduces computing and bandwidth consumption relative to data-level fusion; (2) a lightweight myocardial infarction detection module deployed on an edge platform, enabling local ECG analysis with low resource overhead; (3) a 3D digital-twin edge-cloud management platform that maps multi-source sensing data to a virtual scene in real time and supports hierarchical visual alerting. Experiments in a real nursing home environment show that the system operated stably on resource-constrained edge hardware: UWB positioning achieved centimeter-level RMSE, visual fall detection reached a recall of 0.90, millimeter-wave radar fall detection achieved accuracy, and F1 above 0.90, and myocardial infarction detection exceeded 0.99 accuracy on the public PTB/PTB-XL benchmark. These results indicate an engineering-feasible approach to intelligent elderly care. Larger-scale and longer-term validation remains the focus of future work. Full article

Proton exchange membrane fuel cell–battery hybrid power systems provide an effective solution to overcome the limited endurance of battery-powered multirotor unmanned aerial vehicles. However, the highly transient power demands of quadcopter platforms, combined with balance-of-plant losses and operational constraints, create significant challenges for reliable energy management. This study proposes a degradation-aware stress-mitigation model predictive control-based energy management framework to maximize mission endurance under realistic conditions. A control-oriented, physics-consistent model is developed using manufacturer polarization data from a 500 W Aerostak proton exchange membrane fuel cell. The model captures polarization behavior, balance-of-plant loads, battery dynamics, and direct current-bus power balance. The model predictive control strategy optimally allocates power by maintaining direct current-bus stability, regulating battery state-of-charge within safe limits, and constraining fuel cell power ramp rates to mitigate degradation. High-fidelity simulations are conducted under stochastic wind disturbances and mission-dependent load profiles, including takeoff, climb, cruise, and maneuvering phases. The results show continuous power delivery without unmet load demand. The hybrid system achieves a flight endurance of 220–224 min, consuming a total of 89.99 g of hydrogen at an average rate of 0.398–0.412 g/min, indicating a notable reduction under the considered operating conditions. Additionally, long-term analysis indicates that over 97% of initial endurance is preserved after 100 cycles, demonstrating robustness against fuel cell aging. An analytical real-time feasibility assessment further indicates that the control-oriented formulation is compatible with the computational resources of typical unmanned aerial vehicle-class onboard processors, while the integration of adaptive and robust predictive control techniques is identified as a direction for future work. Full article

Purpose in life is a central component of healthy ageing and psychological well-being, yet its meaning in later life has often been operationalised through standardized measures rather than being grounded in older adults’ lived experience. This qualitative study explores how older adults living in the community in Spain interpret their life purpose during the transitions of old age. Ten adults aged 65 years and older from Aragón and Andalucía participated in semi-structured interviews lasting 60–90 min. Data were analyzed using reflective thematic analysis on ageing supported by MAXQDA, supplemented with questions related to internalized ageism, psychological inflexibility, and quality of life to enrich the interpretive depth. Four themes were identified: (1) purpose as biographical continuity; (2) purpose as a dynamic and adaptive process; (3) legacy as a central axis towards meaning; and (4) the interplay between internal strengths and external conditions. Participants constructed purpose as rooted in identity, values, and life narratives rather than in distal goal attainment. Purpose was maintained through adaptive processes—including resilience, psychological flexibility, and meaning-centered coping—while internalized ageism and personal barriers emerged as life limitations. These findings suggest that purpose in later life is not diminished, but rather is reconfigured through processes of adaptation, value alignment, and social contribution. The study highlights the need for person-centred and process-based approaches that promote psychological flexibility and challenge deficit-based and ageist views of ageing. Full article

Adolescents with LGBTQ+ parents and LGBTQ+ adolescents navigate unique social and identity-related challenges as compared to those without minoritized sexual and/or gender identities. Adolescents with LGBTQ+ parents (regardless of their own sexual or gender identity) and adolescents who personally identify as LGBTQ+ are distinct populations, though they sometimes overlap. Research on adolescents with LGBTQ+ parents has often focused on parent–adolescent relationships and family structures. How do friends help youth cope with identity-based minority stressors, like peer microaggressions, bullying, and exclusion, common for those with minoritized identities? Friendships are developmentally pivotal during adolescence, shaping social competence, identity exploration, and psychological adjustment. Grounded in ecological systems, social learning, and minority stress theories, we sought to understand how friendships relate to mental health and coping in adolescents with LGBTQ+ parents. This cross-sectional quantitative study included 98 adolescents (ages 12–19) with LGBTQ+ parents in the U.S., recruited via community sampling and Prolific. Higher-quality peer attachment, conceptualized by trust, communication, and alienation in close friendships, was associated with lower depression and greater social competence, but not associated with anxiety or adaptive coping (after accounting for avoidant coping). Avoidant coping was most strongly associated with poorer mental health. This study, with implications for practice, emphasizes the importance of peer relationships for adolescents with LGBTQ+ parents—particularly how high-quality friendships offer important possible protection via social competence and against depression—while also highlighting the complex interplay between friendships, coping, and adjustment. Full article