Search Results (302,221)

Background/Objectives: The World Health Organization (WHO) recommends the use of attenuated Sabin strains for the production of inactivated poliovirus vaccine (IPV), offering improved biosafety while retaining immunogenicity. To better characterize the antigenic composition of Sabin strain-based IPV (sIPV), including both the protective D-antigen and the non-protective H-antigen forms, we developed a method for purifying D- and H-antigens forms. Methods: D- and H-antigens of poliovirus Sabin strains types 1, 2, and 3 were purified using gradient ultracentrifugation and used to generate antigen-specific polyclonal antibodies. Results: The generated polyclonal antibodies demonstrated high specificity with neutralizing titers of antibodies against Sabin type 1 poliovirus—1:2048, against Sabin type 2 poliovirus—more than 1:2048, against Sabin type 3 poloivirus —1:2048. Conclusions: This antigen-specific antibody approach provides a valuable tool for routine quality control in sIPV manufacturing, enabling accurate quantification of immunogenic components and detection of potentially immunogenic degradation products during vaccine storage and distribution. Antibodies to the D-antigen allow assessment of immunogenic, neutralizing epitopes, while antibodies to the H-antigen provide a tool for detecting non-neutralizing components. This antigen-specific antibody approach offers a valuable tool for studying the antigenic structure of sIPV and for improving the accuracy of ELISA-based antigen quantification. Full article

Many transportation structures collapse or sustain severe damage as a result of natural disasters such as earthquakes, floods, wars, and similar attacks. These collapsed or severely damaged structures must be rebuilt and returned to service as quickly as possible. Water is used in the mix for cement-bound concrete roads. It is known that drought problems are emerging due to climate change and that water resources are rapidly depleting. Significant amounts of water are used in concrete production, further depleting water resources. In order to contribute to the elimination of these two problems, the usability of polyurethane resin binder in road pavement construction was investigated. Polyurethane resin binder road pavement is a new type of pavement that does not contain cement or bitumen as binders and does not contain water in its mixture. This new type of road pavement can be opened to traffic within 5–15 min. After determining the aggregate and binder mixture ratios, four different curing methods were applied to the created samples. After the curing, the samples were subjected to compression test, flexural test, Bohme abrasion test, freeze–thaw test, bond strength by pull-off test, ultrasonic pulse velocity (UPV) test, SEM-EDX analysis, XRD analysis, and FT-IR analysis. The new type of road pavement created within the scope of this study exhibited a compression strength of 41.22 MPa, a flexural strength of 25.32 MPa, a Bohme abrasion value of 0.99 cm³/50 cm², a freeze–thaw test mass loss per unit area of 0.77 kg/m², and an average bond strength by pull-off value of 4.63 MPa. It was observed that these values ensured the road pavement specification limits. Full article

Background: Bisphenols (BPs) are present in medical instruments, plastic containers, and personal care products (PCPs). Bisphenol A has been replaced by its alternatives, bisphenol S, F, AF, and B. Due to the awareness of their toxicity, mixed exposure to these alternatives at the regional level has been given less attention; there is a need to study this area of research. This meta-analysis examined the exposure of urinary bisphenol A and its metabolites to blood Hypothalamic–Pituitary–Thyroid axis hormones (HPT axis hormones) in pregnant women and adult males and females. We searched Embase, PubMed, Web of Science, Cochrane Library, and CINAHL until 8 January 2025, yielding 4588 articles using the PECO framework. Quality assessment was done using AHRQ: Agency for Healthcare Research and Quality for cross-sectional and NOS: Newcastle Ottawa Scale for cohort studies, with combined exposure evaluated using random and fixed-effect models. The I² test assessed heterogeneity. We included eighteen studies for the final analysis. Fixed-effect model estimates revealed that BPA is negatively associated with thyroid-stimulating hormone (TSH) in female and male adults (β = −0.02; 95% CI = −0.04 to −0.01); (β = −0.08; 95% CI = −0.14 to −0.02). In Females, BPA was positively associated with free thyroxine, FT4 (β = 0.001, 95% CI, 0.001 to 0.001). In the male group, BPA was negatively associated with FT4 (β = −0.001, 95% CI, −0.001 to −0.001). As per pregnant women, there was no association found between exposure to bisphenols and total Thyroxine (TT4), FT4, and TSH in both trimesters (β = 0.010, 95% CI = −0.030 to 0.050); (β = 0.001, 95% CI = −0.010 to 0.010); (β = −0.001, 95% CI = −0.010 to 0.001), respectively, for early pregnancy. Bisphenols can significantly influence HPT axis hormones in adult males, females, and pregnant women. Gender-based studies were observed, concluding that adult females are more affected by bisphenol exposures than adult males. The subgroup analysis based on the regions did not reveal any associations. Full article

The purpose of this study was to identify the potential inhibitory effects of extracts of garlic, ginger, and onion on Escherichia coli and Staphylococcus aureus, which had been previously isolated from milk of dairy cows with mastitis. Garlic, ginger, and onions were crudely pressed, and the extracts were filtered and tested for their ability to inhibit bacterial growth at a wide range of concentrations, from undiluted to 1:512 (2⁻⁹). Their inhibitory properties were compared to positive controls containing ampicillin and ceftiofur, and negative controls containing only the nutrient medium and bacteria. Each plate contained quality control organisms E. coli ATCC 25922 and S. aureus ATCC 25923. The colorimetric microdilution method with resazurin as an indicator of bacterial growth was used to determine the minimum inhibitory concentrations. In addition, the minimum bactericidal concentrations of the extracts were assessed. The minimum inhibitory concentrations of garlic extracts were 1.56 µL/mL and 3.12 µL/mL for E. coli and S. aureus, respectively. The minimum bactericidal concentrations of garlic extract against E. coli and S. aureus were 12.5 and 25 µL/mL, respectively. For both ginger and onion, no inhibition was detected at the full concentration of the extracts, but garlic extract demonstrated in vitro inhibition against both E. coli and S. aureus. Future studies should evaluate the ability of garlic extracts to achieve an inhibitory concentration in milk and explore its potential activity in naturally infected mammary glands. Full article

Calcium nitrate tetrahydrate, used in fertilizers, wastewater treatment, and concrete admixtures, has limited toxicity data despite extensive industrial use. This study evaluated its repeated-dose and reproductive/developmental toxicity in Sprague Dawley rats following OECD TG 422, which combines TG 407 and 421 to extend dosing than TG 407 and reduce animal use compared with separate studies. Rats were administered 0, 100, 300, or 1000 mg/kg/day. Males were treated for 49 days and females from 2 weeks pre-mating to postpartum day 13; the recovery group was observed for an additional 2 weeks. Endpoints included clinical signs, body weight, food consumption, hematology, serum biochemistry, organ weights, histopathology, reproductive performance, and F1 development. No systemic toxicity was observed in F0 males. Minimal prostate atrophy occurred in high-dose males but was considered non-adverse due to limited severity. One high-dose female died on PPD 1, and high-dose F1 litters showed decreased litter size, increased post-implantation loss, and a reduced live-born index. Based on these results, NOAELs were cautiously assigned 1000 mg/kg/day for repeated-dose and male reproductive toxicity and 300 mg/kg/day for female reproductive and developmental toxicity. TG 422 efficiently characterized hazards while reducing animal use, though its limited duration and scope indicate the need for complementary studies. Full article

This preliminary study investigates the optimization of the mechanical properties of the zinc wrought alloy ZEP1510 with the objective of assessing its potential to approach the hardness, strength, and toughness of the brass alloy, CuZn21Si3P. Enhancing both toughness and hardness was targeted to improve the durability of potential replacement components. Heat treatment was the primary method, applying annealing, air cooling, water quenching, and artificial aging to modify material properties. Mechanical characterization was performed through Brinell hardness, as well as tensile and Charpy impact testing, complemented by metallographic analysis. Air cooling from temperatures near the transformation point at 275 °C produced a visually refined and homogeneous microstructure (qualitative assessment by OM/SEM), resulting in simultaneous increases in hardness and toughness. Water quenching from this range yielded a metastable state with high toughness but low hardness, while subsequent natural aging significantly increased strength and reduced toughness. Artificial aging indicated precipitation hardening behavior similar to that of aluminum alloys. Although property improvements were achieved, the targeted combination of high toughness and high strength was not fully realized. The findings suggest that controlled artificial aging, alternative quenching media and grain refinement strategies could further enhance performance, providing a basis for tailoring ZEP1510 for demanding engineering applications. Full article

Traditional training methods for first responders are often limited by time, resources, and safety constraints, which reduces their consistency and effectiveness. This study focused on two main issues: whether exposure to virtual reality training scenarios induces measurable physiological changes in heart rate and heart rate variability, and whether these responses differ between police and firefighter contexts. The aim of this study was to explore the integration of virtual reality technologies into responder training and to evaluate how biomedical monitoring can be used to assess training effectiveness. A pilot measurement was conducted with ten participants who completed systematic crime scene investigation scenarios in both domains. Heart activity was continuously recorded using a wearable sensor and analyzed for heart rate and heart rate variability parameters, while cognitive load and task performance were also assessed. The collected data were statistically evaluated using tests of normality and paired comparisons between baseline and virtual reality phases. The results showed a significant increase in heart rate and a decrease in heart rate variability during virtual reality exposure compared to baseline, with higher cognitive load and success rates in police scenarios compared to firefighter scenarios. These findings indicate that virtual reality scenarios can elicit measurable psychophysiological responses and highlight the potential of combining immersive technologies with biomedical monitoring for the development of adaptive and effective training methods for first responders. Full article

Educational institutions face complex challenges when allocating limited teaching resources to specialized seminars, where budget, capacity, and balanced disciplinary representation must all be satisfied simultaneously. We address this for the first time in the educational domain by formulating the teacher seminar selection problem as a multi-dimensional knapsack variant with category-specific benefit multipliers. To solve it, we design a constraint-aware genetic algorithm that incorporates smart initialization, category-sensitive operators, adaptive penalties, and targeted repair mechanisms. In experiments on a realistic dataset representing multiple academic categories, our method achieved an 11.5% improvement in solution quality compared to the best constraint-aware greedy baseline while maintaining perfect constraint satisfaction (100% feasibility) vs. 0–30% for baseline methods. Statistical tests confirmed significant and practically meaningful advantages. For comprehensive benchmarking, we also implemented binary particle swarm optimization (PSO) and Tabu Search (TS) solvers with standard parameterizations. While PSO consistently produced feasible solutions with high budget utilization, its optimization quality was substantially lower than that of the GA. Notably, Tabu Search achieved the highest performance, with a mean fitness of 1557.3 compared to GA’s 1533.2, demonstrating that memory-based local search can be highly competitive for this problem structure. These findings show that metaheuristic approaches, particularly those integrating constraint-awareness into evolutionary or memory-based search, provide effective, scalable decision-support frameworks for complex, multi-constraint educational resource allocation. Full article

Background: Inappropriate antibiotic prescribing by dental practitioners is a significant problem in low- and middle-income settings, such as India, where there are no guidelines for dental prescribing. This study aims to report, in a step-by-step process, the co-development of a computer-based stewardship educational intervention with Indian stakeholders to reduce inappropriate antibiotic prescribing by primary care dental practitioners in India. Methods: The development process of our intervention was guided by the Medical Research Council framework for developing and evaluating complex interventions. In alignment with the framework’s core elements, a co-production research approach was employed. Engagement with local stakeholders, including primary care dental practitioners, academic dentists, and those from the Indian Dental Association, facilitated the development of a contextually appropriate intervention that was informed by a prior needs assessment (a systematic review and a policy document analysis conducted in India) and evidence from global literature. The intervention was refined through iterative feedback from stakeholders and pre-testing. Results: An educational antibiotic stewardship intervention was co-developed in collaboration with stakeholders from Chennai, a major city in southern India. The final intervention comprised three components: 1. A one-page chairside guide summarising common areas of dental antibiotic use for easy reference in clinical settings; 2. A training module based on the chairside guide; and 3. A patient information sheet to facilitate dentists’ communication with patients. The intervention components were designed to be clear, practical, and contextually relevant, with the potential to enhance clinical decision-making and promote evidence-based antibiotic prescribing practices. Conclusions: This research paper describes, in a structured manner, how an educational antibiotic stewardship intervention for dental practitioners in India was co-developed by researchers and local stakeholders. Further feasibility testing is required to address uncertainties identified at the conclusion of the development process, including those related to dentists’ perceptions of the intervention, the utility of the intervention tools, and prescription recording. Full article

Background/Objectives: Diabetic neuropathy (DN) is a prevalent complication of diabetes mellitus, affecting up to 50% of long-term patients and causing significant pain, reduced quality of life, and healthcare burden. Conventional treatments, including anticonvulsants, antidepressants, and opioids, offer limited efficacy and are associated with adverse effects. Emerging evidence suggests that cannabis, acting via the endocannabinoid system, may provide analgesic and neuroprotective benefits. This study evaluates the long-term effects of inhaled cannabis as adjunctive therapy for refractory painful DN. Inhaled cannabis exhibits rapid onset pharmacokinetics (within minutes, lasting 2–4 h) due to pulmonary absorption, targeting CB1 and CB2 receptors to modulate pain and inflammation. Methods: In this prospective, observational study, 52 patients with confirmed painful DN, unresponsive to at least three prior analgesics plus non-pharmacological interventions, were recruited from a single clinic. Following a 1-month washout, patients initiated inhaled medical-grade cannabis (20% THC, <1% CBD), titrated individually. Assessments occurred at baseline and annually for 5 years, including the Brief Pain Inventory (BPI) for pain severity and interference; the degree of pain relief; Leeds Assessment of Neuropathic Symptoms and Signs (LANSS) score; HbA1c; and medication usage. Statistical analyses used repeated-measures ANOVA, Kruskal–Wallis tests, Welch’s t-tests, and Pearson’s correlations via Analyze-it for Excel. Results: Of 52 patients (mean age 45.3 ± 17.8 years; 71.2% male; diabetes duration 23.3 ± 17.8 years), 50 completed follow-up visits. Significant reductions occurred in BPI pain severity (9.0 ± 0.8 to 2.0 ± 0.7, p < 0.001), interference (7.5 ± 1.7 to 2.2 ± 0.9, p < 0.001), LANSS score (19.4 ± 3.8 to 10.2 ± 6.4, p < 0.001), and HbA1c (9.77% ± 1.50 to 7.79% ± 1.51, p < 0.001). Analgesic use decreased markedly (e.g., morphine equivalents: 66.8 ± 49.2 mg to 4.5 ± 9.6 mg). Cannabis dose correlated positively with pain relief (r = 0.74, p < 0.001) and negatively with narcotic use (r = −0.43, p < 0.001) and pain interference (r = −0.43, p < 0.001). No serious adverse events were reported; mild side effects (e.g., dry mouth or euphoria) occurred in 15.4% of patients. Conclusions: Inhaled cannabis showed sustained pain relief, improved glycemic control, and opioid-sparing effects in refractory DN over 5 years, with a favorable safety profile. These findings are associative due to the observational design, and randomized controlled trials (RCTs) are needed to confirm efficacy and determine optimal usage, addressing limitations such as single-center bias and small sample size (n = 52). Future studies incorporating biomarker analysis (e.g., endocannabinoid levels) could elucidate mechanisms and enhance precision in cannabis therapy. Full article

Background: Bovine mastitis caused by Prototheca spp. is the most significant animal disease of algal origin, with an increasing number of cases reported worldwide. Currently, there is no effective treatment, so control requires the culling of infected animals. In Chile, information is limited, and a discrepancy remains in the literature regarding the Prototheca species involved in bovine mastitis. Methods: This study aimed to molecularly type and phenotypically characterize Prototheca isolates associated with bovine mastitis in Chile. Sixty-six Prototheca isolates obtained from individual bovine mastitis milk samples and bulk tank milk samples were analyzed through cytochrome b gene (cytb) sequencing, Random Amplified Polymorphic DNA–Polymerase Chain Reaction (RAPD-PCR) analysis, and phenotypic evaluation (morphology, antimicrobial susceptibility, and biofilm formation). Results: Sixty-five isolates were identified as P. bovis and one as P. ciferrii, marking the first report of the latter in bovine mastitis in Chile. RAPD analysis revealed a high genetic diversity in P. bovis. All strains exhibited resistance to the antibiotics tested from the Fluoroquinolone, β-lactam, and sulfonamide groups; however, 100% of the strains showed susceptibility to aminoglycosides, with gentamicin standing out as a potential therapeutic option. Most P. bovis strains formed weak (81.5%, 53/65) or moderate (15.4%, 10/65) biofilms, which could favor the persistence of infection. Conclusions: These findings provide novel insights into the molecular and phenotypic characteristics of Prototheca spp. in Chile, highlighting the predominance of P. bovis, the emergence of P. ciferri, and the implications for antimicrobial management and disease control. Full article

Accurate recognition of estrus behavior in sows is of great importance for achieving scientific breeding management, improving reproductive efficiency, and reducing labor costs in modern pig farms. However, due to the evident spatiotemporal continuity, stage-specific changes, and ambiguous category boundaries of estrus behaviors, traditional methods based on static images or manual observation suffer from low efficiency and high misjudgment rates in practical applications. To address these issues, this study follows a video-based behavior recognition approach and designs three deep learning model structures: (Convolutional Neural Network combined with Long Short-Term Memory) CNN + LSTM, (Three-Dimensional Convolutional Neural Network) 3D-CNN, and (Convolutional Neural Network combined with Temporal Convolutional Network) CNN + TCN, aiming to achieve high-precision recognition and classification of four key behaviors (SOB, SOC, SOS, SOW) during the estrus process in sows. In terms of data processing, a sliding window strategy was adopted to slice the annotated video sequences, constructing image sequence samples with uniform length. The training, validation, and test sets were divided in a 6:2:2 ratio, ensuring balanced distribution of behavior categories. During model training and evaluation, a systematic comparative analysis was conducted from multiple aspects, including loss function variation (Loss), accuracy, precision, recall, F1-score, confusion matrix, and ROC-AUC curves. Experimental results show that the CNN + TCN model performed best overall, with validation accuracy exceeding 0.98, F1-score approaching 1.0, and an average AUC value of 0.9988, demonstrating excellent recognition accuracy and generalization ability. The 3D-CNN model performed well in recognizing short-term dynamic behaviors (such as SOC), achieving a validation F1-score of 0.91 and an AUC of 0.770, making it suitable for high-frequency, short-duration behavior recognition. The CNN + LSTM model exhibited good robustness in handling long-duration static behaviors (such as SOB and SOS), with a validation accuracy of 0.99 and an AUC of 0.9965. In addition, this study further developed an intelligent recognition system with front-end visualization, result feedback, and user interaction functions, enabling local deployment and real-time application of the model in farming environments, thus providing practical technical support for the digitalization and intelligentization of reproductive management in large-scale pig farms. Full article

Seasonal design floods and operational water levels are critical for high-efficient water resource utilization. In this study, statistical and rational analyses methods were applied to divide the flood season based on seasonal rainfall patterns. The Mann–Kendall test and Theil–Sen analysis were used to detect trend changes in the observed flow series. Both stationary and nonstationary flood frequency analysis methods were conducted to estimate seasonal design floods. The Three Gorges Reservoir (TGR) in the Yangtze River, China, was selected as the case study. Results show that the TGR flood season could be divided into four periods: the reservoir drawdown period (1 May–20 June), the Meiyu flood period (21 June–31 July), the transition period (1 August–10 September), and the Autumn Rain refill period (11 September–31 October). Trend analyses indicate that the flow series at the TGR dam site exhibited a decreasing trend in recent decades. Upstream reservoir regulation has significantly reduced inflow discharges of TGR, and the nonstationary seasonal 1000-year design floods in the transition period are decreased by about 20%, and the flood control water level could rise from 145 m to 157 m, which can generate 2.288 billion kW h more hydropower (16.57% increase) while maintaining unchanged flood prevention standards. This study provides valuable insights into the TGR operational water level in the flood season and highlights the necessity of considering the regulation impact of upstream reservoirs for design floods and reservoir operational water levels. Full article

Cardiopulmonary Exercise Testing (CPET) is the gold standard for the functional assessment in patients with heart failure (HF), providing objective parameters that reflect the integrated response of the cardiovascular, respiratory, and muscular systems, in addition several CPET-derived variables have shown independent prognostic value in patients with both reduced (HFrEF) and preserved ejection fraction (HFpEF) HF. This review aims to critically analyze the main CPET prognostic variables in heart failure, highlighting their underlying pathophysiological mechanisms, their predictive capacity for mortality and hospitalizations, and their integration into clinical decision-making models. Parameters such as peak oxygen uptake (VO₂), minute ventilation/carbon dioxide production (VE/VCO₂) slope, periodic breathing (or exercise oscillatory ventilation—EOV), anaerobic threshold (AT), oxygen pulse, and VO₂/work slope provide complementary insights into clinical risk; moreover, the combination of multiple CPET variables allows for more accurate risk stratification compared to the isolated use of each parameter. Multiparametric prognostic models such as the Metabolic Exercise Cardiac Kidney Index (MECKI) score, the Seattle Heart Failure Model, and the Heart Failure Survival Score (HFSS) incorporate these variables alongside clinical and laboratory data to guide advanced management and therapeutic decisions, including heart transplantation or left ventricular assistant device (LVAD) implantation. For these reasons, CPET-derived variables are essential prognostic tools in heart failure. Beyond improving risk stratification, their integration into multiparametric models supports a more personalized therapeutic approach, including tailored pharmacological management. Full article

AI chatbots have the potential to facilitate students’ academic progress and enhance knowledge accessibility in higher education, yet learners’ attitudes toward these technologies vary amid AI-driven disruptions, with factors influencing acceptance remaining debated. The current study constructs an integrated model based on Technology Acceptance Model 3 (TAM3), an extension of the original TAM, incorporating factors including Self-Efficacy, Perceived Enjoyment, Anxiety, Perceived Ease of Use, Perceived Usefulness, Output Quality, Social Influence, and Behavioral Intention, to explore determinants and mechanisms influencing learners’ acceptance of AI chatbots. This addresses key challenges in AI-augmented learning, such as personalization benefits versus risks like information inaccuracy and ethical concerns. Results from the questionnaire survey analysis with 265 valid responses reveal significant relationships: (1) self-efficacy significantly predicts perceived ease of use; (2) both perceived enjoyment and perceived ease of use positively influence perceived usefulness; and (3) self-efficacy, perceived usefulness, and social influence collectively exert significant effects on behavioral intention. Measurement invariance tests further indicate significant differences in acceptance between undergraduate and graduate students, suggesting academic level moderates behavioral intentions. Findings offer principled guidance for designing inclusive AI tools that mitigate accessibility barriers and promote equitable adoption in educational environments. Full article