Search Results (7,834)

Recent progress in microfluidic technologies has led to the development of compact and highly efficient electrochemical platforms, including lab-on-a-chip (LoC) systems, that integrate multiple testing functions into a single, portable device. Combined with smartphone-based electrochemical devices, these systems enable rapid and accurate on-site detection of food contaminants, including pesticides, heavy metals, pathogens, and chemical additives at farms, markets, and processing facilities, significantly reducing the need for traditional laboratories. Smartphones improve the performance of these platforms by providing computational power, wireless connectivity, and high-resolution imaging, making them ideal for in-field food safety testing with minimal sample and reagent requirements. At the core of these systems are electrochemical biosensors, which convert specific biochemical reactions into electrical signals, ensuring highly sensitive and selective detection. Advanced nanomaterials and integration with Internet of Things (IoT) technologies have further improved performance, delivering cost-effective, user-friendly food monitoring solutions that meet regulatory safety and quality standards. Analytical techniques such as voltammetry, amperometry, and impedance spectroscopy increase accuracy even in complex food samples. Moreover, low-cost engineering, artificial intelligence (AI), and nanotechnology enhance the sensitivity, affordability, and data analysis capabilities of smartphone-integrated electrochemical devices, facilitating their deployment for on-site monitoring of food and agricultural contaminants. This review explains how these technologies address global food safety challenges through rapid, reliable, and portable detection, supporting food quality, sustainability, and public health. Full article

Background: As means of addressing ongoing challenges in accessing publicly funded specialist care, new models of care have been trialled. One such approach is using physiotherapists in advance practice roles, who in collaboration with other health professionals, act as an initial orthopedic point of contact and coordinate care. This research investigated the impact of a model of care, the Spinal Virtual Clinic Model, implemented for the first time in South Australia, using advanced practice physiotherapists in a large metropolitan hospital in South Australia. Although formally named the “Spinal Virtual Clinic” by the health service, this model does not involve direct patient contact and differs from traditional virtual or telehealth clinics. Instead, it is best understood as a physiotherapy-led referral triage and management service. Methods: This research was conducted in two stages. Stage 1 was a retrospective clinical audit of sequential patients triaged to the Spinal Virtual Clinic, as well as a follow up audit to capture any subsequent engagement with the Orthopaedic Spinal Service following the initial Spinal Virtual Clinic correspondence. Data were descriptively analysed. In Stage 2, semi-structured interviews were conducted with patients from the Spinal Virtual Clinic to explore their perspectives on this model of care. The interviews were transcribed verbatim and independently analysed using thematic analysis. The sequential use of quantitative and qualitative approaches enabled us to both describe engagement with this model of care and better understand the underlying perspectives. Results: Three hundred and nine referrals were triaged to the physiotherapy-led spinal virtual clinic over a six-month period from 1 January 2021 to 30 June 2021. Majority of referrals were triaged as low acuity did not need formal spinal specialist review and could be managed safely in primary care. Therapist-led active management strategies (80.8%), trial of neuropathic medication (35.6%) closely followed by advice regarding targeted spinal injections (foraminal and epidural), were the most common conservative management strategies recommended. Only a small proportion needed surgical review. Interviews with eleven patients revealed that while many valued the convenience, timely advice, and reassurance offered by the service, others expressed confusion about the referral process and disappointment at not seeing a specialist. A key recommendation identified was improved communication, including providing patients with direct feedback alongside general practitioner correspondence. Conclusions: This research, underpinned by quantitative and qualitative research, has showcased the potential of this model of care, the spinal virtual clinic, to have a positive impact on improving access and reducing the burden on the health system for low acuity patients. As historical models of care become unsustainable and obsolete, alternative models of care can be implemented in health care settings where outpatient demand significantly exceeds capacity. Full article

Peripartum depression (PPD) represents a significant public health concern, affecting 10–17% of women globally. Traditional monoaminergic treatments demonstrate limited efficacy and delayed onset of action. The glutamate–GABA imbalance hypothesis provides a novel theoretical framework for understanding depression pathophysiology and developing targeted therapeutic interventions. This review examines emerging pharmacotherapeutic approaches targeting glutamatergic and GABAergic neurotransmitter systems for PPD treatment. Search criteria targeted randomized clinical trials investigating GABA-A-positive allosteric modulators (brexanolone, zuranolone, and ganaxolone) and NMDA receptor antagonists (ketamine and esketamine) in PPD patients. Brexanolone was the first neurosteroid to receive FDA approval for PPD, while zuranolone also shows promise. Ketamine and esketamine are also associated with reduced PPD risk, particularly with perioperative administration during cesarean delivery, though benefits are predominantly short-term. These glutamate–GABA pathway modulators represent novel therapeutic alternatives with rapid onset profiles. Further investigation and research are needed to optimize dosing protocols and patient selection criteria and to establish long-term efficacy before PPD treatment guidelines can be drafted. Full article

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza virus are major respiratory pathogens associated with substantial morbidity and a risk of severe disease. However, the effectiveness of current vaccines and antiviral drugs is limited by viral mutations. Umeboshi, a traditional Japanese food prepared from pickled Prunus mume, is known for its health benefits; certain components of P. mume have exhibited antimicrobial properties. However, the efficacy of P. mume against SARS-CoV-2 and influenza virus remains unknown. We aimed to examine the antiviral activity of P. mume extracts against SARS-CoV-2 and influenza virus. Cytopathic effect (CPE) assays and reverse transcription–quantitative polymerase chain reaction (RT-qPCR) analyses with full-time treatment demonstrated that four extracts (PM2, PM3, PM4, and PM6) among eight tested inhibited the replication of both viruses. Subsequent time-of-addition assays, plaque assays, and transmission electron microscopy (TEM) confirmed that PM2 directly inactivated viral particles of both viruses by disrupting their structural integrity. Additional evaluations of virion integrity and infectivity suggested that the antiviral activity of PM2 may also involve mechanisms other than direct virion disruption. These findings suggest that P. mume-derived components exhibit direct antiviral activities against SARS-CoV-2 and influenza virus, supporting their potential development as antiviral agents or infection-preventive dietary products. Full article

As aquaculture expands globally, understanding immune responses in non-traditional farmed species like Octopus vulgaris under varying environmental conditions is increasingly important. This study investigated lysozyme activity, a key innate immune marker, in cell-free hemolymph of O. vulgaris following experimental challenge with four Gram-negative fish pathogens (Photobacterium damselae subsp. piscicida, P. damselae subsp. damselae, Vibrio alginolyticus, and V. anguillarum O1) at two temperatures (21 ± 0.5 °C and 24 ± 0.5 °C). These pathogens were selected because octopus farming frequently occurs near fish aquaculture facilities, raising the potential for pathogen crossover. A total of 216 wild octopuses were injected intramuscularly or intravenously and sampled on days 0, 3, and 7 post-challenge. Lysozyme activity varied by pathogen, injection route, sampling time, and temperature. A significant time- and temperature-dependent increase was observed, especially in IM-challenged groups exposed to Photobacterium species. Elevated temperatures supported a more prolonged immune response. These results highlight lysozyme as a responsive biomarker of innate immunity in O. vulgaris and emphasize the role of environmental factors in immune modulation. This work provides a foundation for disease monitoring and health management in cephalopod aquaculture. Future research should examine long-term lysozyme dynamics, broader pathogen exposure, molecular mechanisms, and additional environmental stressors such as salinity and pollution. Full article

As the core component of aircraft systems, aeroengines require accurate Remaining Useful Life (RUL) prediction to ensure flight safety, which serves as a key part of Prognostics and Health Management (PHM). Traditional RUL prediction methods primarily fall into two main categories: physics-based and data-driven approaches. Physics-based methods mainly rely on extensive prior knowledge, limiting their scalability, while data-driven methods (including statistical analysis and machine learning) struggle with handling high-dimensional data and suboptimal modeling of multi-scale temporal dependencies. To address these challenges and enhance prediction accuracy and robustness, we propose a novel hybrid deep learning framework (CLSTM-TCN) integrating 2D Convolutional Neural Network (2D-CNN), Long Short-Term Memory (LSTM) network, and Temporal Convolutional Network (TCN) modules. The CLSTM-TCN framework follows a progressive feature refinement logic: 2D-CNN first extracts short-term local features and inter-feature interactions from input data; the LSTM network then models long-term temporal dependencies in time series to strengthen global temporal dynamics representation; and TCN ultimately captures multi-scale temporal features via dilated convolutions, overcoming the limitations of the LSTM network in long-range dependency modeling while enabling parallel computing. Validated on the NASA C-MAPSS data set (focusing on FD001), the CLSTM-TCN model achieves a root mean square error (RMSE) of 13.35 and a score function (score) of 219. Compared to the CNN-LSTM, CNN-TCN, and LSTM-TCN models, it reduces the RMSE by 27.94%, 30.79%, and 30.88%, respectively, and significantly outperforms the traditional single-model methods (e.g., standalone CNN or LSTM network). Notably, the model maintains stability across diverse operational conditions, with RMSE fluctuations capped within 15% for all test cases. Ablation studies confirm the synergistic effect of each module: removing 2D-CNN, LSTM, or TCN leads to an increase in the RMSE and score. This framework effectively handles high-dimensional data and multi-scale temporal dependencies, providing an accurate and robust solution for aeroengine RUL prediction. While current performance is validated under single operating conditions, ongoing efforts to optimize hyperparameter tuning, enhance adaptability to complex operating scenarios, and integrate uncertainty analysis will further strengthen its practical value in aircraft health management. Full article

Compared to non-smart communities, smart communities expand the boundaries of community management and provide a platform for the deep integration of fitness and health. However, a single-entity governance model reduces the management efficiency of smart communities and hinders the realization of fitness-health integration within them. A collaborative governance model involving governments, businesses, social organizations, and residents replaces the traditional linear governance model that relies on a single entity through resource integration. This study, based on collaborative governance theory, employs three scenario-based experimental designs and quantitative analysis, with Xiamen’s smart city community and non-smart urban village community as research subjects. It explores the multistakeholder collaborative governance model for the deep integration of fitness and health, compares the differences in fitness-health integration between smart communities and non-smart communities, and measures the effectiveness differences between multistakeholder collaborative governance and single-entity governance models. The findings indicate: (1) Residents in smart communities have higher satisfaction with comprehensive fitness-health services; (2) Residents in smart communities perceive shorter psychological distances when engaging in fitness-health activities compared to non-smart environments; (3) The governance model moderates the impact of psychological distance on service satisfaction. Compared to the single-actor model, multiactor collaborative governance more effectively enhances perceived psychological proximity and improves satisfaction. The research findings contribute theoretically to advancing understanding of collaborative governance theory while expanding the application of the technology acceptance model (TAM) and the construal level theory in the context of community governance. Practically, they offer insights for public policymakers to optimize resource allocation and for community managers to strengthen digital governance. Full article

This study aimed to characterize the morphometric traits and production systems of Criollo sheep in the highlands of Caylloma, Arequipa, Peru. A total of 455 sheep were evaluated using a stratified proportional sampling method across the districts of Tisco, San Antonio de Chuca, and Yanque. Morphometric data were collected under standardized conditions, and nine zoometric indices were calculated to assess functional conformation and productive aptitude. Additionally, 52 sheep producers were surveyed to contextualize herd management practices. Results revealed low levels of formal education and limited technical assistance among producers. Sheep farming was primarily sustained by family tradition, with declining flock sizes attributed to pasture scarcity and climatic challenges. Campaign-based sales strategies and rudimentary reproductive management were prevalent. Health practices showed widespread deworming but limited preventive care. Multivariate analysis indicated significant morphometric variation linked to sex, biotype, and dental stage. This integrative approach highlights both the adaptive potential and production constraints of Criollo sheep in high-altitude environments, providing a basis for developing breeding strategies based on morphometric indices. Full article

Introduction: Mental health problems in children and adolescents are a growing public health concern. Aerobic physical activity has been identified as a promising, accessible, and low-cost intervention to promote psychological well-being. Methods: This systematic review and meta-analysis was conducted following PRISMA 2020 guidelines and a pre-registered PROSPERO protocol. We searched PubMed, Scopus, Web of Science, and CINAHL for randomized controlled trials published until December 2024, with no language restrictions. Eligibility criteria included interventions based on aerobic physical activity among children and adolescents (5–18 years) reporting outcomes on mental health (e.g., depression, anxiety, self-esteem, mood, resilience). Methodological quality was assessed with the PEDro scale. Results: From 828 initial records, 21 studies met the inclusion criteria and 19 were included in the meta-analysis. The trials, conducted in diverse countries and settings, applied structured aerobic interventions (e.g., running, dancing, cycling, active games) with durations of 6–30 weeks. The pooled results showed significant improvements in depression, anxiety, self-esteem, and stress, with the largest effects observed in stress reduction and self-esteem enhancement. Conclusions: Aerobic physical activity appears to be an effective and feasible strategy to improve mental health in children and adolescents. Its integration into school and community programs is recommended as a preventive and complementary approach to traditional treatments. Full article

For centuries, Scaptotrigona mexicana honey has been treasured in Mexico, where pre-Columbian cultures harvested it not only for its sweet flavor but also for its medicinal and ceremonial purposes. Today, it remains a high-value product in local markets, prized above Apis mellifera honey for its unique sensory qualities and traditional health benefits. Yet its scientific characterization and functional potential remain underexplored. In this study, twenty-four samples from diverse regions were analyzed to quantify bioactive compounds and determine physicochemical composition, α-amylase inhibition, and antioxidant activity. Non-parametric statistical tests revealed distinct compositional clusters, with samples from Cruz Blanca showing exceptional phenolic content and stronger α-amylase inhibition (5.6–49.2%). Antioxidant capacity correlated positively with phenols and flavonoids, showing moderate effect sizes for ABTS (η² = 0.49) and DPPH (η² = 0.37). Compared with Apis mellifera honey, Scaptotrigona mexicana contained more moisture, free acidity, phenols, and antioxidants, but less diastase, hydroxymethylfurfural, and reducing sugars. Importantly, natural α-amylase inhibitors can help modulate postprandial glucose, offering dietary support for type 2 diabetes management. Kinetic analyses (EC50, Vmax, and Km) suggested mixed inhibition. These findings highlight Scaptotrigona mexicana as both a heritage product and a promising functional ingredient for developing foods that merge tradition with metabolic health innovation. Full article

Background and Objectives: Musculoskeletal pain is a global public health issue. Eight Constitution Medicine (ECM), a type of East Asian Traditional Medicine, offers personalized, minimally invasive treatment through Eight Constitution Acupuncture (ECA) and Eight Constitution Lifestyle Intervention (ECLI). Despite its clinical use, scientific evidence supporting ECM’s effectiveness remains limited. This study aimed to evaluate the effectiveness in treating musculoskeletal pain in primary care settings. Materials and Methods: This retrospective study analyzed medical records from three ECM clinics (Gangnam-Shingwang, Yeson, and Yebon) between January 2018 and August 2023. A total of 163 patients were included, with 44 providing follow-up data. Pain intensity, quality of life, and functional outcomes were assessed using validated instruments including the PainDETECT questionnaire, Korean Cancer Pain Assessment Tool (KCPAT) somatic pain scores, EuroQol 5-Dimension 5-Level (EQ-5D-5L), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), Oswestry Disability Index (ODI), Neck Disability Index (NDI), and Shoulder Pain and Disability Index (SPADI). Pre- and post-treatment scores were statistically analyzed. Results: Significant decreases were observed in KCPAT somatic pain scores (11.77 ± 4.77 to 9.77 ± 5.32) and significant improvements in EQ-5D-5L scores (0.74 ± 0.12 to 0.80 ± 0.07). WOMAC and ODI scores also showed significant improvements. However, the changes in the NDI, SPADI, and PainDETECT scores were not statistically significant. No adverse events were reported. Conclusions: ECM, through ECA and ECLI, may offer effective personalized treatment for musculoskeletal pain, improving both pain intensity and quality of life. Despite its small sample size and retrospective design, this study offers valuable preliminary evidence for ECM. Further large-scale prospective studies are needed to confirm these findings. Full article

Background: Geographic information systems (GIS) are a promising tool for mapping vaccination coverage and identifying missed communities, yet their use in low- and middle-income countries (LMICs) remains limited. In settings without standardized addresses such as schools or outreach sites, innovative methods are needed to collect and analyse spatial data. Schools offer a unique platform for identifying under-vaccinated children missed by routine or campaign efforts. Methods: During a pilot school vaccination screening program in Zambia, GIS reference maps of health facility catchment areas were developed from hand-drawn sketch maps, catchment area shapefiles, and coordinates of prominent landmarks. These maps were iteratively refined with input from local health staff. In caregiver interviews, data collectors used the maps to identify the child’s zone of residence within the health facility catchment area. Vaccination status was extracted from paper registries used during screening. Geographic heat maps were generated in ArcGIS to visualize under-vaccination by zone. Results: Of 535 children screened across 25 zones, 29% were under-vaccinated. Under-vaccination varied by zone, with clusters of missed children identified, for example, 50% of children in Kabushi Zone 6 were under-vaccinated, compared with much lower rates elsewhere. Conclusions: Pairing school-based vaccination checks with GIS mapping offers a scalable approach to identifying missed communities in LMICs. This method enables spatial analysis without household visits, supporting targeted immunization planning where traditional data systems fall short. However, because the study was limited to children enrolled in five purposively selected schools, out-of-school children and those in other schools were not represented. This selection bias may underestimate the true extent of under-vaccination, and future evaluations should incorporate broader and more representative populations. Full article

Research on the post-deployment reintegration needs of women veterans is limited. Non-traditional support may enhance mental health. Relationships with animals and volunteering may aid those with post-traumatic stress disorder (PTSD). Using the biopsychosocial model, we examined whether participation in an 8-week service dog training program (SDTP) affected telomere length (TL), heart rate variability (HRV), PTSD symptom severity, perceived stress, and anxiety in female veterans with PTSD, as well as whether combat exposure influenced these relationships. Female veterans (ages 32–72, M = 45.9, SD = 11.8) with PTSD were randomized to either the SDTP group (n = 13) or a comparison group (n = 15) that received dog training video content. The interventions lasted one hour weekly for 8 weeks. Outcomes were assessed pre-, mid-, and post-intervention. Linear mixed models with random intercepts examined changes from pre- to post-intervention and compared changes by group and combat exposure. TL changes differed [F(1,11.65) = 3.543, p = 0.085] by intervention. In the SDTP group, TL increased, indicating reduced cellular senescence (i.e., slower biological aging), whereas TL decreased in the CI group. Combat exposure moderated these changes [F(1,12.36) = 5.41, p = 0.038]. HRV changed by intervention group [F(1,389.08) = 10.623, p = 0.001]. HRV decreased (stress increased) in the SDTP group but not in the CI group. Combat exposure did not moderate HRV changes. PTSD symptom severity [F(1,48.04) = 19.22, p < 0.001], perceived stress [F(1,48.48) = 14.65, p < 0.001], and anxiety [F(1,47.30) = 6.624, p = 0.013] decreased significantly from pre- to post-interventions; the decreases did not differ by intervention or combat exposure. Full article

With the global aging population, skeletal muscle aging has threatened to elderly health, making dietary interventions for age-related muscle decline a research priority. Lycium barbarum, a traditional food and medicinal herb, was used in the study to prepare Lycium barbarum water (LBW). This experiment was conducted in animals and included four groups: young control (C-Young), aged control (C-Aged), young LBW-drinking (G-Young), and aged LBW-drinking (G-Aged). Assessments covered skeletal muscle mass, cross-sectional area, and exercise ability to compare health status. The study measured mRNA expression of Atrogin-1 and MuRF-1 from the Forkhead Box O (FOXO) pathway, advanced glycation end products (AGEs) and senescence-associated β-galactosidase (SA-β-gal), oxidative stress levels via superoxide dismutase (SOD), malondialdehyde (MDA) and glutathione (GSH), inflammatory levels through interleukin-10 (IL-10) and tumor necrosis factor-alpha (TNF-α), and applied untargeted metabolomics to profile metabolic alterations. Optimal LBW was achieved at 80 °C with a 1:10 (w/v) solid-liquid ratio. In aged mice, long-term LBW administration improved exercise capacity, reduced muscle atrophy, and increased muscle mass, alongside decreased aging-related markers, alleviated oxidative stress, and modulated inflammatory levels. Additionally, metabolomics confirmed age-related oxidative stress and inflammation. Long-term LBW consumption alleviates age-related skeletal muscle dysfunction via multi-target regulation, holding promise as a natural nutritional intervention for mitigating skeletal muscle aging. Full article

Leptospirosis is a worldwide zoonosis caused by pathogenic Leptospira spp. with small rodents serving as the main reservoir. In Croatia, the serogroup Pomona has been detected most frequently, but its genomic diversity remains insufficiently characterized. This study presents the first whole genome sequencing analysis of 48 Croatian Leptospira spp. isolates collected from small rodents over a 14-year period. Serological typing confirmed that all the isolates belonged to the serogroup Pomona. Genomic analysis assigned them to L. kirschneri based on high genomic similarity using average nucleotide identity (ANI). The isolates were assigned to ST-98 using traditional multilocus sequence typing (MLST), while cgMLST identified seven genotype clusters, many of which showed geographic structuring. Phylogenetic analyses based on single nucleotide polymorphisms (SNPs) supported this structure and revealed a monophyletic clade of Croatian isolates distinct from other global L. kirschneri strains. Serological typing, MLST, and phylogenetic clustering support classification of the isolates as L. kirschneri, serogroup Pomona, most likely serovar Mozdok, although serovar Tsaratsovo cannot be excluded. These results indicate the existence of a geographically restricted and potentially host-adapted lineage of L. kirschneri in Croatia. The integration of ecological, serological, and genomic data in this study emphasizes the value of whole genome sequencing for understanding the population biology of Leptospira spp. serogroup Pomona. Moreover, it supports targeted, country-specific surveillance and control strategies for leptospirosis through the identification of circulating serovars and species in reservoir hosts, in line with a One Health approach. Full article