Search Results (4,992)

Dengue is the most concerning mosquito-borne neglected tropical disease globally. The disease is caused by the dengue virus (DENV) and transmitted by the vector mosquito species belonging to the genus Aedes Meigen, 1818, particularly Aedes aegypti (Linnaeus, 1762) and Aedes albopictus (Skuse, 1895). In 2024, global cases of dengue exceeded 7.6 million, with India reporting 233,519 cases. These statistics underscore the ongoing challenge of managing dengue outbreaks worldwide. For generations, tribal communities across India have employed medicinal plant-based extracts as mosquito and other insect repellents. Plant-based phytochemicals are largely preferred over synthetic insecticides due to their perceived safety, non-toxicity to non-target organisms, and environmental sustainability. This review provides a comprehensive overview of various phytochemicals extracted from Indian medicinal plants for their larvicidal activity against Aedes mosquitoes. Furthermore, the article also reviews the mode of action of these phytochemicals, including neurotoxicity, mitochondrial dysfunction, sterol carrier protein-2 inhibition, midgut cytotoxicity, insect growth regulation disruption, and antifeedant activity, which aids in formulating dengue vector control strategies. Based on this review, Ecbolin B from Ecbolium viride, Alizarin from Rubia cordifolia, and Azadirachtin from Azadirachta indica exhibited better larval mortality rates against Ae. aegypti, with LC50 values recorded at 0.70, 1.31, and 1.7 ppm, respectively. Full article

This study systematically analyzed the pollution levels, distribution characteristics, and associated health risks of 17 organochlorine pesticides (OCPs) and 9 polychlorinated biphenyls (PCBs) in Oviductus Ranae (Rana dybowskii) from major production areas in Heilongjiang Province, China. OCPs and PCBs were detected in all samples. The total concentration of OCPs ranged from 11.7 to 67.9 ng/g (dry weight), while that of total PCBs ranged from 4.43 to 8.06 ng/g. Endosulfans constituted the predominant OCP group, accounting for 54.5% of ∑OCPs, with an α/β-endosulfan ratio (~2:1) indicative of recent agricultural input. Among DDTs, the dominance of p,p′-DDE and the absence of parent DDT suggested aerobic degradation of historical residues. For HCHs, the isomer profile (β-HCH predominance, α/γ-HCH = 0.27) pointed to weathered lindane sources. The PCB profile was uniquely dominated by lower-chlorinated congeners (PCB1 and PCB29), implying influences from atmospheric transport and/or in situ microbial dechlorination of legacy PCBs. The persistent organic pollutants (POPs) contamination profile in Oviductus Ranae reflects a combined influence of recent pesticide application, weathered historical residues, and long-range transport. Although the concentrations are below current regulatory limits, the cumulative and persistent nature of these POPs, coupled with the product’s medicinal use, justifies a precautionary stance regarding long-term consumption. The distinct congener patterns underscore the necessity for future research to prioritize the environmental behavior and toxicology of dominant transformation products within such specific agro-ecosystems. Full article

Objective: The emergence and spread of multi-drug-resistant (MDR) bacteria pose a growing threat in veterinary medicine, particularly in equine hospitals. This study investigated the colonization and infection dynamics of horses undergoing emergency laparotomy with two distinct antibiotic protocols (single-shot versus 5-day protocol) during hospitalization. Methods: Nasal swabs and fecal samples were collected from 67 horses undergoing emergency laparotomy at clinic admission as well as on postoperative days 3 and 10. These were screened for multi-drug-resistant indicator pathogens. As multi-drug-resistant indicator pathogens, methicillin-resistant Staphylococcus aureus (MRSA), extended-spectrum β-lactamase (ESBL)-producing Enterobacterales (ESBL-E), and bacteria belonging to the Acinetobacter baumannii complex were defined. Results: Preoperatively, 6.2% of horses tested positive for MRSA and 13% for ESBL-E. An increase in colonization was observed on day 3 postoperatively, with 62.1% of nasal swabs and 86.4% of fecal samples testing positive for MDR organisms. On day 10, 53.4% of nasal swabs and 62.5% of fecal samples tested positive for indicator pathogens. Surgical site infection developed in five horses, two of which tested positive for MRSA in both nasal and wound samples during hospitalization, supporting the potential role of nasal carriage as a source of infection. Furthermore, all horses tested positive for ESBL-E during at least one time-point during hospitalization, and Enterobacterales (MDR in two surgical site infections (SSI)) were involved in all surgical site infections. No significant differences were observed between the two antibiotic treatment groups regarding colonization rates with indicator pathogens during hospitalization. However, the results indicate that hospitalization itself contributes to increased colonization with resistant bacteria. A clear limitation of the study is the restricted number of sampled horses and the lack of environmental contamination data. Non-sampled hospitalized horses with and without antibiotic treatment may have acted as reservoirs for MDR bacteria. Conclusion: The findings emphasize the need for routine environmental monitoring and strict adherence to hygiene protocols in equine clinics to reduce the risk of nosocomial transmission. Ongoing surveillance and infection control strategies are essential to mitigate the spread of MDR pathogens in veterinary settings. Full article

Diagnostic errors have been a critical concern in healthcare, leading to substantial financial burdens and serious threats to patient safety. The Improving Diagnosis in Health Care report by the National Academies of Sciences, Engineering, and Medicine (NASEM) defines diagnostic errors, focusing on accuracy, timeliness, and communication, which are influenced by clinical knowledge and the broader healthcare system. This review aims to integrate existing literature on diagnostic error from a systems-based perspective and examine the factors across various domains to present a comprehensive picture of the topic. A narrative literature review was structured upon the Systems Engineering Initiative for Patient Safety (SEIPS) model that focuses on six domains central to the diagnostic process: Diagnostic Team Members, Tasks, Technologies and Tools, Organization, Physical Environment, and External Environment. Studies on contributing factors for diagnostic error in these domains were identified and integrated. The findings reveal that the effectiveness of diagnostics is influenced by complex, interconnected factors spanning all six SEIPS domains. In particular, socio-behavioral factors, such as team communication, cognitive bias, and workload, and environmental pressures, stand out as significant but difficult-to-capture contributors in traditional and commonly used data resources like electronic health records (EHRs), which limits the scope of many studies on diagnostic errors. Factors associated with diagnostic errors are often interconnected across healthcare system stakeholders and organizations. Future research should address both technical and behavioral elements within the diagnostic ecosystem to reduce errors and enhance patient outcomes. Full article

Understanding how plants respond to water limitation is increasingly important under accelerating climate change. Lycoris aurea, a widely distributed ornamental and medicinal bulbous plant, frequently inhabits environments with fluctuating soil moisture, yet its molecular drought-response mechanisms remain largely unexplored. In this study, we investigated L. aurea growing under field-based, in situ soil moisture regimes, comparing low (~20% soil water content) and high (~40% soil water content) conditions. We combined soil property assessments with high-resolution transcriptomic and untargeted metabolomic profiling to characterize the adaptive responses of bulb tissues under contrasting soil water conditions. Although total nitrogen, phosphorus, and potassium levels were comparable across treatments, soil moisture, representing the primary contrasting field condition, and soil pH, a correlated environmental factor, were significantly associated with variation in gene expression and metabolite accumulation (p < 0.05, n = 3). Transcriptome analyses identified a total of 1034 differentially expressed genes enriched in pathways related to amino acid metabolism, cuticle formation, cell wall modification, and osmotic adjustment. Metabolomic analysis identified a total of 1867 differentially expressed metabolites belonging to carboxylic acids and prenol lipids, showing alterations involved in amino acids, lipids, phenolic acids, and alkaloids associated with osmoprotection, membrane stabilization, and structural reinforcement under low soil moisture. Pathway-based integration analysis highlighted four core pathways, including “alanine, aspartate and glutamate metabolism” (p = 0.00371) and “cutin, suberine and wax biosynthesis” (p = 0.00873), as central hubs linking transcriptional regulation with metabolic reconfiguration. Gene-metabolite-soil correlation networks further demonstrated that drought adaptation arises from tightly coordinated biochemical and structural adjustments rather than shifts in nutrient acquisition. Together, this species-specific study provides a comprehensive multi-omics framework for understanding drought tolerance in L. aurea, reveals key molecular targets associated with plant resilience, and offers potential targets and insights for the conservation of drought-resilient Lycoris cultivars. Full article

Modern agriculture faces the critical need to develop sustainable, safe, and effective strategies for enhancing productivity, protecting plants and animals, and ensuring food security. Challenges posed by antibiotic resistance and the adverse environmental and consumer health impacts of chemical agents are driving the search for eco-friendly alternatives. In this context, bacteriocins—naturally occurring antimicrobial peptides synthesized by diverse bacteria—represent a promising alternative to traditional chemical compounds. This article reviews the potential and current advances in bacteriocin applications across agricultural sectors, with particular focus on their targeted antagonistic activity, structural diversity, commercial bacteriocin-based products, and their utilization in livestock farming, crop production, poultry farming, and aquaculture. Key findings demonstrate that bacteriocins, particularly nisin and pediocin PA-1, exhibit potent activity against major agricultural pathogens including Listeria monocytogenes, Staphylococcus aureus, Clostridium perfringens, and Escherichia coli, with efficacy rates reaching 90% in mastitis treatment and significantly reducing pathogen loads in poultry and aquaculture systems. Commercial products such as Nisaplin, Wipe Out, and ALTA 2431 have been successfully implemented in veterinary medicine and food production. In aquaculture, bacteriocins effectively control Lactococcus garvieae, Aeromonas spp., Vibrio spp., and Pseudomonas aeruginosa, contributing to sustainable disease management with minimal environmental impact. It can be suggested that bacteriocins may play an essential role in combating pathogens and offer viable alternatives to conventional antibiotics across primary food production systems, though optimization of production methods and regulatory frameworks remains essential for broader commercial adoption. Full article

Dilovasi district of Kocaeli is one of the largest industrial regions, and due to its high production capacity and industrial waste, the soil heavy metal levels in this region are exceptionally high. Consequently, this study focuses on essential elements (B, Ca, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Zn) and non-essential elements that are considered toxic to humans (Al, Cd, Pb), covering a total of thirteen elements. Accordingly, this study aims to highlight the degree of pollution in a Turkish Organized Industrial Zone located in the Dilovasi district of Kocaeli by quantifying the concentrations of the aforementioned elements in Calamintha nepeta subsp. glandulosa plants and soil samples, and by assessing their potential implications for human health. Significant accumulation of heavy metals in both soils and plant parts suggests that metal contamination, especially that of Fe (up to 1009.2 mg kg⁻¹), is a matter of great concern in the Dilovasi district. The results revealed that the concentrations (mg kg⁻¹) of Cr (23.0 ± 0.1), Fe (1292.5 ± 5.6), Pb (36.9 ± 0.1), Zn (151.2 ± 0.8), and Cd (3.6 ± 0.1) were considerably higher. However, the concentrations of Cu, Mn, and Ni were found to be within the permissible limits in accordance with the American Herbal Products Association and the World Health Organization referenced guideline values. Furthermore, heavy metal concentrations in C. nepeta subsp. glandulosa were generally higher in areas characterized by elevated soil metal levels, indicating a clear correspondence between soil contamination and plant metal content. Based on these findings, C. nepeta subsp. glandulosa, a plant with culinary and medicinal value, can be considered a useful bioindicator for assessing local heavy metal contamination. Full article

Titanium dioxide (TiO₂) nano- and submicrometric particles’ widespread use in different sectors raised concerns about human and environmental exposure. The validation of analytical methods is essential to ensure reliability in risk assessment studies. In this study, a single-particle inductively coupled plasma mass spectrometry (spICP-MS) method was validated for the detection, quantification, and dimensional characterization of TiO₂ particles in biological tissues. Tissue samples collected after exposure to TiO₂ particles underwent mild acidic digestion using a HNO₃/H₂O₂ mixture to achieve complete matrix decomposition while preserving particle integrity. The resulting digests were analyzed by ICP-MS operated in single-particle mode to quantify and size TiO₂ particles. Method validation was conducted according to ISO/IEC 17025:2017 and included linearity, repeatability, recovery, and detection limit assessments. The limit of detection for TiO₂ particles was 0.04 µg/g, and 55.7 nm was the size the detection limit. Repeatability was within 0.5–11.5% for both TiO₂ mass concentrations and particle size determination. The validated method was applied to tissues from inhalation-exposed subjects, showing TiO₂ levels of 80 ± 20 µg TiO₂/g and particle number concentrations of 5.0 × 10⁵ ± 1.2 × 10⁵ part. TiO₂/mg. Detected TiO₂ particles’ mean diameter ranged from 230 to 330 nm. The developed and validated spICP-MS method provides robust and sensitive quantification of TiO₂ particles in biological matrices, supporting its use in human biomonitoring and exposure assessment studies. Full article

Pediatric obesity is an increasingly prevalent, chronic, and multifactorial disease. Achieving successful and sustained weight reduction with current interventions remains challenging due to significant heterogeneity in treatment response. This review summarizes current evidence describing variability in outcomes across lifestyle, pharmacologic, and metabolic/bariatric surgery interventions in children and adolescents, and examines key biological, metabolic, behavioral, environmental, and psychosocial factors that influence response. In adults, recent findings on energy balance obesity phenotypes (characterized by abnormal satiation, abnormal postprandial satiety, abnormal hedonic eating, and reduced energy expenditure) have demonstrated promise in predicting weight loss outcomes and guiding tailored interventions. However, data on obesity phenotyping within children and adolescents remain limited. Addressing this gap is essential for advancing precision medicine approaches in pediatric obesity, with the potential to improve treatment selection, enhance effectiveness, and optimize long-term clinical outcomes. Full article

1,4-Dihydropyridines (1,4-DHPs) are privileged heterocycles with broad relevance in medicinal chemistry and redox-related applications. However, conventional Hantzsch syntheses typically require prolonged thermal heating and often suffer from limited efficiency and regioselectivity. Herein, we report a sustainable and efficient microwave-assisted protocol for the synthesis of 1,4-DHPs, employing phosphotungstic acid (HPW) as a heteropolyacid catalyst in PEG-400 as a green reaction medium. The multicomponent cyclocondensation proceeds rapidly under microwave irradiation, affording the desired 1,4-DHP derivatives in good to excellent yields within short reaction times. Compared with classical acid-catalyzed conditions, the HPW/PEG-400 system markedly enhances regioselectivity toward the 1,4-DHP framework while simultaneously reducing energy input. Moreover, the catalytic system exhibits good recyclability, underscoring its potential as a practical and environmentally responsible platform for the synthesis of bioactive 1,4-dihydropyridine scaffolds. Full article

Chronic obstructive pulmonary disease (COPD) is a major health burden worldwide and in Taiwan, ranking as the third leading cause of death globally, and its prevalence in Taiwan continues to rise. Readmission within 14 days is a key indicator of disease instability and care efficiency, driven jointly by patient-level physiological vulnerability (such as reduced lung function and multiple comorbidities) and healthcare system-level deficiencies in transitional care. To mitigate the growing burden and improve quality of care, it is urgently necessary to develop an AI-based prediction model for 14-day readmission. Such a model could enable early identification of high-risk patients and trigger multidisciplinary interventions, such as pulmonary rehabilitation and remote monitoring, to effectively reduce avoidable early readmissions. However, medical data are commonly characterized by severe class imbalance, which limits the ability of conventional machine learning methods to identify minority-class cases. In this study, we used real-world clinical data from multiple hospitals in Kaohsiung City to construct a prediction framework that integrates data generation and ensemble learning to forecast readmission risk among patients with chronic obstructive pulmonary disease (COPD). CTGAN and kernel density estimation (KDE) were employed to augment the minority class, and the impact of these two generation approaches on model performance was compared across different augmentation ratios. We adopted a stacking architecture composed of six base models as the core framework and conducted systematic comparisons against the baseline models XGBoost, AdaBoost, Random Forest, and LightGBM across multiple recall thresholds, different feature configurations, and alternative data generation strategies. Overall, the results show that, under high-recall targets, KDE combined with stacking achieves the most stable and superior overall performance relative to the baseline models. We further performed ablation experiments by sequentially removing each base model to evaluate and analyze its contribution. The results indicate that removing KNN yields the greatest negative impact on the stacking classifier, particularly under high-recall settings where the declines in precision and F1-score are most pronounced, suggesting that KNN is most sensitive to the distributional changes introduced by KDE-generated data. This configuration simultaneously improves precision, F1-score, and specificity, and is therefore adopted as the final recommended model setting in this study. Full article

Background: Despite significant advances in genetics, immunology, and endometrial research, the underlying cause of nearly half of recurrent pregnancy loss (RPL) cases remains unknown. This highlights the limitations of conventional diagnostic approaches and underscores the need for methods that can detect complex, subtle biological patterns. Objectives: To summarize and critically assess how artificial intelligence (AI) is changing our knowledge of, ability to predict, and future therapeutic management of RPL, with a focus on machine learning (ML) approaches that identify latent biological pathways and multifactorial contributors to pregnancy loss. Methods: This narrative review summarizes contemporary research on AI applications in reproductive medicine. Research using imaging, proteomic, genomic, clinical, and multi-omics information to create predictive or mechanistic models associated with RPL provided evidence. Results: AI-based approaches are increasingly demonstrating the ability to detect complex interactions among environmental, immunological, biochemical, and genetic factors associated with RPL. ML and deep learning (DL) models enhance prognostic accuracy, identify novel candidate biomarkers, and provide insights into the systemic and molecular mechanisms underlying pregnancy loss. Integrating heterogeneous data through AI supports the development of personalized reproductive profiles and can improve prediction and counseling. Conclusions: AI has the potential to improve both personalized prediction and mechanistic understanding of RPL. However, clinical translation is currently hampered by a number of important issues, including small and diverse datasets, conflicting diagnostic definitions, limited external validation, and a lack of prospective clinical trials. To responsibly integrate AI tools into reproductive care, these limitations must be addressed. Full article

Background: Chronic urticaria (CU) is characterized by recurrent wheals and/or angioedema persisting for more than six weeks. While disease triggers are often unidentified, seasonal and environmental factors may modulate disease activity; however, evidence regarding their clinical impact remains limited. Objective: This study aimed to evaluate the effects of seasonal, meteorological, and pollutant-specific environmental factors on urticaria control using the Urticaria Control Test (UCT), and to compare these effects between chronic spontaneous urticaria (CSU) and chronic inducible urticaria (CIU) in relation to inflammatory serum biomarkers. Materials and Methods: This prospective observational study was conducted at the Allergy and Clinical Immunology outpatient clinic of Kirikkale University Faculty of Medicine between 1 June 2023 and 1 April 2024. Patients with CU were classified as CSU or CIU according to international guidelines. Each participant was evaluated during summer and winter seasons. Area-level air pollution data and meteorological parameters were obtained from national monitoring systems. Disease control was assessed using the UCT, and inflammatory biomarkers were analyzed. Results: Urticaria control showed significant seasonal variation, with lower UCT scores during summer and higher scores during winter in both CSU and CIU patients. Among environmental factors, ozone (O₃) was the only pollutant consistently associated with poorer urticaria control, whereas particulate matter and traffic-related pollutants, despite being higher in winter, showed no clinically relevant association. Summer months were characterized by increased inflammatory activity, including elevated leukocyte counts, neutrophil-to-lymphocyte ratio (NLR), C-reactive protein (CRP), and D-dimer levels, particularly in CSU patients. D-dimer emerged as an independent marker associated with poor disease control during summer. Conclusions: CU demonstrates marked seasonal variation, with disease worsening during summer months. Pollutant-specific effects, particularly O₃ exposure, rather than overall air pollution burden, appear to be clinically relevant in urticaria control. Inflammatory and coagulation-related biomarkers may provide additional insight into disease activity. These findings support a season-aware and individualized management approach and highlight the need for future studies incorporating individual-level exposure assessment and biomarker-guided strategies. Full article

Cancer cases have been estimated that will increase in the next years with consequent increase of antineoplastic (AD) drug treatments and workers handling these hazardous chemicals. We aimed to evaluate genotoxic/oxidative effects of AD exposure by fpg-comet assay on a large size sample of workers (214 exposed and 164 controls) involved in preparation; administration, including Hyperthermic intraperitoneal chemotherapy (HIPEC) and pressurized intraperitoneal aerosol chemotherapy (PIPAC); and disposal. With the final aim to identify suitable early biomarkers of genotoxic effect useful to health surveillance, we correlated fpg-comet assay (blood) and Buccal Micronucleus Cytome (BMCyt) assay data. Fpg-comet parameters resulted higher in the exposed group vs. controls, demonstrating direct and oxidative DNA damage in workers handling ADs. Fpg-comet direct DNA damage and genotoxic parameters of BMCyt assay demonstrated a weak statistically significant correlation. This cross-sectional study is one of the few available evaluating both direct and oxidative DNA damage due to ADs on a large sample size of workers and correlating fpg-comet and BMCyt assay results. It highlights the need to evaluate genotoxic effects by both the biomarkers and furnishes a contribution to their validation. Moreover, we demonstrate for the first time oxidative DNA damage on workers performing HIPEC and PIPAC administration. Full article

Lentinula edodes (shiitake) is a major edible and medicinal mushroom and a key component of the horticultural mushroom industry in East Asia. During April–June 2024 cropping season, a widespread blue mold outbreak was observed on bag-cultivated shiitake in Xixia County, Henan Province, China. Affected cultivation rooms showed extensive blue-green sporulation on the exposed surfaces of substrate blocks and on developing and mature fruiting bodies, leading to rapid loss of marketability. To clarify the etiology of this disease, we coupled field surveys with morphological, molecular, and pathogenicity analyses. Fifty-five Penicillium isolates were obtained from symptomatic cultivation bags. Three representative isolates (LE06, LE15, and LE26) were characterized in detail. Colonies on PDA produced velutinous to floccose mycelia with blue-green conidial masses and terverticillate penicilli bearing smooth-walled, globose conidia. Sequencing of four loci—the internal transcribed spacer (ITS1-5.8S-ITS2), β-tubulin (benA), calmodulin gene (CaM), and RNA polymerase II second largest subunit (rpb2)—followed by multilocus phylogenetic analysis placed all three isolates in a well-supported clade with the ex-type CBS 227.28 of Penicillium bialowiezense. Inoculation of healthy shiitake cultivation bags with conidial suspensions (1 × 10⁶ conidia mL⁻¹) reproduced typical blue mold symptoms on substrate surfaces and fruiting bodies within 40 days post inoculation, whereas mock-inoculated controls remained symptomless. The pathogen was consistently reisolated from diseased tissues and showed identical ITS and benA sequences to the inoculated strains, thereby fulfilling Koch’s postulates. This is the first confirmed report of P. bialowiezense causing blue mold on shiitake, and it expands the known host range of this species. Our findings highlight the vulnerability of bag cultivation systems to airborne Penicillium contaminants and underscore the need for improved hygiene, environmental management, and targeted diagnostics in commercial shiitake production. Full article