Search Results (857)

The global Black Lives Matter movement and COVID-19 pandemic drew attention to the urgency of addressing entrenched structural dynamics such as racialization, gender, and colonization shaping health inequities for diverse racialized people. Canadian community-based research with racialized immigrant women recognized the need to enhance service provider capacity using a strengths-based activism approach to support client health and wellbeing. In this study, we aimed to understand the impacts of this mental health promotion practice on service providers and strategies to support them. Through purposeful convenience sampling, three focus groups were completed with 19 service providers working in settlement and mental health services in Toronto, Canada. Participants represented varied ethnicities and work experiences; most self-identified as female and racialized, with experiences living as immigrant women in Canada. Postcolonial feminist and critical mental health promotion analysis illuminated organizational and structural dynamics contributing to burnout and vicarious trauma that necessitate a focus on trauma- and violence-informed care. Transformative narratives reflected service provider resilience and activism, which aligned with and challenged mainstream biomedical approaches to mental health promotion. Implications include employing a postcolonial feminist lens to identify meaningful and comprehensive anti-oppression strategies that take colonialism, racialization, gender, and ableism and their intersections into account to decolonize nursing practices. Promoting health equity for diverse racialized women necessitates focused attention and multilevel anti-oppression strategies aligned with critical mental health promotion practices. Full article

Honey bees are essential pollinators for the ecosystem and food crops. However, their health and survival face threats from both biotic and abiotic stresses. Fungi, microsporidia, and bacteria might significantly contribute to colony losses. Therefore, rapid and sensitive diagnostic tools are crucial for effective disease management. In this study, molecular assays were developed to quickly and efficiently detect the main honey bee pathogens: Nosema ceranae, Aspergillus flavus, Paenibacillus larvae, and Black queen cell virus. In this context, new primer pairs were designed for use in quantitative Real-time PCR (qPCR) reactions. Various protocols for extracting total nucleic acids from bee tissues were tested, indicating a CTAB-based protocol as the most efficient and cost-effective. Furthermore, excluding the head of the bee from the extraction, better results were obtained in terms of quantity and purity of extracted nucleic acids. These assays showed high specificity and sensitivity, detecting up to 250 fg of N. ceranae, 25 fg of P. larvae, and 2.5 pg of A. flavus DNA, and 5 pg of BQCV cDNA, without interference from bee DNA. These qPCR assays allowed pathogen detection within 3 h and at early stages of infection, supporting timely and efficient management interventions. Full article

This study presents the scientific and methodological foundation of Spain’s first national framework for the ethical management of community cat populations: the Action Plan for the Management of Community Cat Colonies (PACF), launched in 2025 under the mandate of Law 7/2023. This pioneering legislation introduces a standardized, nationwide obligation for trap–neuter–return (TNR)-based management of free-roaming cats, defined as animals living freely, territorially attached, and with limited socialization toward humans. The PACF aims to support municipalities in implementing this mandate through evidence-based strategies that integrate animal welfare, biodiversity protection, and public health objectives. Using standardized data submitted by 1128 municipalities (13.9% of Spain’s total), we estimated a baseline population of 1.81 million community cats distributed across 125,000 colonies. These data were stratified by municipal population size and applied to national census figures to generate a model-ready demographic structure. We then implemented a stochastic simulation using Vortex software to project long-term population dynamics over a 25-year horizon. The model integrated eight demographic–environmental scenarios defined by a combination of urban–rural classification and ecological reproductive potential based on photoperiod and winter temperature. Parameters included reproductive output, mortality, sterilization coverage, abandonment and adoption rates, stochastic catastrophic events, and territorial carrying capacity. Under current sterilization rates (~20%), our projections indicate that Spain’s community cat population could surpass 5 million individuals by 2050, saturating ecological and social thresholds within a decade. In contrast, a differentiated sterilization strategy aligned with territorial reproductive intensity (50% in most areas, 60–70% in high-pressure zones) achieves population stabilization by 2030 at approximately 1.5 million cats, followed by a gradual long-term decline. This scenario prioritizes feasibility while substantially reducing reproductive output, particularly in rural and high-intensity contexts. The PACF combines stratified demographic modeling with spatial sensitivity, offering a flexible framework adaptable to local conditions. It incorporates One Health principles and introduces tools for adaptive management, including digital monitoring platforms and standardized welfare protocols. While ecological impacts were not directly assessed, the proposed demographic stabilization is designed to mitigate population-driven risks to biodiversity and public health without relying on lethal control. By integrating legal mandates, stratified modeling, and realistic intervention goals, this study outlines a replicable and scalable framework for coordinated action across administrative levels. It exemplifies how national policy can be operationalized through data-driven, territorially sensitive planning tools. The findings support the strategic deployment of TNR-based programs across diverse municipal contexts, providing a model for other countries seeking to align animal welfare policy with ecological planning under a multi-level governance perspective. Full article

The incidence and mortality of colorectal cancer (CRC) have increased globally. Several therapeutic approaches have been suggested to address this health issue, in addition to classical methods. Propranolol (PRO) is a beta-blocker that was repurposed to treat infantile hemangiomas, and its anti-tumor activity has been reported. This study aimed to investigate the effects of PRO in a panel of CRC cell lines and its potential impact when combined with chemotherapy. The effects of PRO on cell cytotoxicity, cell morphology, colony formation, cell death induction, cell cycle, mitochondrial and intracellular reactive oxygen species (ROS), and migration were measured in all cells. CompuSyn software was utilized to assess the possible synergistic or additive interaction in the combined treatment. The results showed that PRO suppressed cell proliferation, altered cell morphology, inhibited colony formation, induced apoptosis, altered cell cycle and ROS generation, and inhibited the migration of treated cells in a cell-type-specific, time-dependent, and dose-dependent manner compared with the control. HT-29 was the most sensitive cell line to PRO in terms of cytotoxicity, apoptosis, cell cycle arrest, and ROS generation, while SW-480 was the most sensitive in terms of migration inhibition. Moreover, the PRO and capecitabine combination exhibited a synergistic effect and induced mitochondrial apoptosis in metastatic CRC cells. The data suggest that PRO could be a promising adjuvant therapy for primary and advanced CRC. This study identified variations between CRC cell lines in response to PRO, which may be related to their genetic and epigenetic differences. In addition, the findings highlight the potential of combination strategies to improve therapeutic outcomes in metastatic CRC. Full article

Nosocomial infections caused by ESKAPE pathogens represent a significant burden to global health. These pathogens may exhibit multidrug resistance (MDR) mechanisms, of which mechanisms such as efflux pumps and biofilm formation are gaining significant importance. Multidrug resistance mechanisms in ESKAPE pathogens have led to an increase in the effective costs in health care and a higher risk of mortality in hospitalized patients. These pathogens utilize antimicrobial efflux pump mechanisms and bacterial biofilm-forming capabilities to escape the bactericidal action of antimicrobials. ESKAPE bacteria forming colonies demonstrate increased expression of efflux pump-encoding genes. Efflux pumps not only expel antimicrobial agents but also contribute to biofilm formation by bacteria through (1) transport of molecules and transcription factors involved in biofilm quorum sensing, (2) bacterial fimbriae structure transport for biofilm adhesion to surfaces, and (3) regulation of a transmembrane gradient to survive the difficult conditions of biofilm microenvironments. The synergistic role of these mechanisms complicates treatment outcomes. Given the mechanistic link between biofilms and efflux pumps, therapeutic strategies should focus on targeting anti-biofilm mechanisms alongside efflux pump inactivation with efflux pump inhibitors. This review explores the molecular interplay between efflux pumps and biofilm formation, emphasizing potential therapeutic strategies such as efflux pump inhibitors (EPIs) and biofilm-targeting agents. Full article

In chili cultivation, obstacles to continuous cropping significantly compromise crop yield and soil health, whereas crop rotation can enhance the microbial environment of the soil and reduce disease incidence. However, its effects on the diversity of rhizosphere soil microbial communities are not clear. In this study, we analyzed the composition and characteristics of rhizosphere soil microbial communities under chili continuous cropping (CC) and chili–cotton crop rotation (CR) using high-throughput sequencing technology. CR treatment reduced the alpha diversity indices (including Chao1, Observed_species, and Shannon index) of bacterial communities and had less of an effect on fungal community diversity. Principal component analysis (PCA) revealed distinct compositional differences in bacterial and fungal communities between the treatments. Compared with CC, CR treatment has altered the structure of the soil microbial community. In terms of bacterial communities, the relative abundance of Firmicutes increased from 12.89% to 17.97%, while the Proteobacteria increased by 6.8%. At the genus level, CR treatment significantly enriched beneficial genera such as RB41 (8.19%), Lactobacillus (4.56%), and Bacillus (1.50%) (p < 0.05). In contrast, the relative abundances of Alternaria and Fusarium in the fungal community decreased by 6.62% and 5.34%, respectively (p < 0.05). Venn diagrams and linear discriminant effect size analysis (LEfSe) further indicated that CR facilitated the enrichment of beneficial bacteria, such as Bacillus, whereas CC favored enrichment of pathogens, such as Firmicutes. Fusarium solani MG6 and F. oxysporum LG2 are the primary chili root-rot pathogens. Optimal growth occurs at 25 °C, pH 6: after 5 days, MG6 colonies reach 6.42 ± 0.04 cm, and LG2 5.33 ± 0.02 cm, peaking in sporulation (p < 0.05). In addition, there are significant differences in the utilization spectra of carbon and nitrogen sources between the two strains of fungi, suggesting their different ecological adaptability. Integrated analyses revealed that CR enhanced soil health and reduced the root rot incidence by optimizing the structure of soil microbial communities, increasing the proportion of beneficial bacteria, and suppressing pathogens, providing a scientific basis for microbial-based soil management strategies in chili cultivation. Full article

Enhanced colony nutrition can support brood development, resulting in better physiological conditions and increased resilience in adult honey bees, particularly under stress. This study investigated the effects of colony nutrition and adult dietary supplementation with green propolis on bee health under fungicide exposure. Colonies were managed under food restriction or nutritional supplementation for 22 weeks. Newly emerged bees from each colony were then caged and fed protein diets consisting of honey-pollen patties contaminated or not with fungicide, and sucrose sugar syrup with or without aqueous green propolis extract. Bees from supplemented colonies showed greater body weight, higher hemolymph protein levels, and higher consumption of protein food after seven days in cages. Fungicide exposure reduced hemolymph protein levels, altered the expression of detoxification and immune-related genes, and significantly decreased bee survival. Interestingly, propolis supplementation alone changed gene expression patterns and slightly reduced longevity compared to bees not exposed to propolis or fungicide. However, under fungicide stress, bees that ingested propolis survived longer, indicating a protective effect. While colony nutritional supplementation clearly promotes honey bee resilience against fungicide exposure, feeding propolis also showed promising effects, though further studies are needed to determine an optimal dietary concentration. Full article

Over the past years, increasing attention has been drawn to the adverse effects of agricultural pesticide use on pollinators, with honeybees being especially vulnerable. The aim of this study was to evaluate the levels of residues detectable and/or quantifiable of neonicotinoid pesticides and other pesticides in biological materials (bees, bee brood, etc.) and beehive products (honey, pollen, etc.) applied as seed dressings in rapeseed and sunflower plants in two growing seasons (2020–2021) in fields located in three agro-climatic regions in Romania. The study involved the comparative sampling of hive products (honey, pollen, adult bees, and brood) from experimental and control apiaries, followed by pesticide residue analysis in an accredited laboratory (Primoris) using validated chromatographic techniques (LC-MS/MS and GC-MS). Toxicological analyses of 96 samples, including bees, bee brood, honey, and pollen, confirmed the presence of residues in 46 samples, including 10 bee samples, 10 bee brood samples, 18 honey samples, and 8 pollen bread samples. The mean pesticide residue concentrations detected in hive products were 0.032 mg/kg in honey, 0.061 mg/kg in pollen, 0.167 mg/kg in bees, and 0.371 mg/kg in bee brood. The results highlight the exposure of honeybee colonies to multiple sources of pesticide residue contamination, under conditions where legal recommendations for the controlled application of agricultural treatments are not followed. The study provides relevant evidence for strengthening the risk assessment framework and underscores the need for adopting stricter monitoring and regulatory measures to ensure the protection of honeybee colony health. Full article

High-voltage diodes, as key devices in power electronic systems, have important significance for system reliability and preventive maintenance in terms of storage life prediction. In this paper, we propose a hybrid modeling framework that integrates the Long Short-Term Memory Network (LSTM) and Transformer structure, and is hyper-parameter optimized by the Improved Artificial Bee Colony Algorithm (IABC), aiming to realize the high-precision modeling and prediction of high-voltage diode storage life. The framework combines the advantages of LSTM in time-dependent modeling with the global feature extraction capability of Transformer’s self-attention mechanism, and improves the feature learning effect under small-sample conditions through a deep fusion strategy. Meanwhile, the parameter type-aware IABC search mechanism is introduced to efficiently optimize the model hyperparameters. The experimental results show that, compared with the unoptimized model, the average mean square error (MSE) of the proposed model is reduced by 33.7% (from 0.00574 to 0.00402) and the coefficient of determination (R²) is improved by 3.6% (from 0.892 to 0.924) in 10-fold cross-validation. The average predicted lifetime of the sample was 39,403.3 h, and the mean relative uncertainty of prediction was 12.57%. This study provides an efficient tool for power electronics reliability engineering and has important applications for smart grid and new energy system health management. Full article

Apiculture is among the most weather-dependent sectors of agriculture; however, quantifying the impact of meteorological factors remains challenging. Beehive weight has long been recognized as an important indicator of colony health, strength, and food availability, as well as foraging activity. Atmospheric influences on hive weight dynamics have been a subject of research since the early 20th century. This study aims to estimate hourly hive weight variation by applying linear time-series models to hive weight data collected from active apiaries during intensive foraging periods, considering atmospheric predictors. We employed a rolling 24 h forward ARIMAX and SARIMAX model, incorporating meteorological variables as exogenous factors. The median estimates for the study period resulted in model RMSE values of 0.1 and 0.3 kg/h. From numerous meteorological variables, the hourly maximum temperature was found to be the most significant predictor. ARIMAX model results also exhibited a strong diurnal cycle, pointing out the weather-driven seasonality of hive weight variations. Full article

Thermoregulatory fanning behavior in honeybees is a vital indicator of colony health and environmental response. This study presents a novel dataset of 18,000 annotated video frames containing 57,597 instances capturing fanning behavior at the hive entrance across diverse conditions. Three state-of-the-art single-shot object detection models (YOLOv8, YOLO11, YOLO12) are evaluated using standard RGB input and two motion-enhanced encodings: Temporally Stacked Grayscale (TSG) and Temporally Encoded Motion (TEM). Results show that models incorporating temporal information via TSG and TEM significantly outperform RGB-only input, achieving up to 85% mAP@50 with real-time inference capability on high-performance GPUs. Deployment tests on the Jetson AGX Orin platform demonstrate feasibility for edge computing, though with accuracy–speed trade-offs in smaller models. This work advances real-time, non-invasive monitoring of hive health, with implications for precision apiculture and automated behavioral analysis. Full article

The European chickpea market raises concerns about health risks for consumers due to contamination by mycotoxins. Contamination levels can vary depending on the farming system, and rapid and reliable screening tools are desirable. In this study, marketed chickpea seed samples from organic and non-organic farming systems were analyzed for fungal and mycotoxin contamination. Aspergillus and Penicillium were the most frequently identified mycotoxigenic genera. Significant differences in fungal detection were observed among the three isolation methods used, whose combined application is proposed to enhance detection efficiency. The number of Aspergillus and Penicillium colonies was significantly higher in the organic samples. Molecular analysis identified different species within each genus, including several not previously reported in chickpea, as well as potentially aflatoxigenic species such as A. flavus/oryzae and A. parasiticus. LC-MS/MS analysis revealed aflatoxin production only by A. parasiticus, which was present in low amounts. However, the presence of potentially aflatoxigenic Aspergillus species suggests that chickpeas should be monitored to detect their safety and subsequently protect consumer health. A qPCR protocol targeting the omt-1 gene, involved in aflatoxin biosynthesis, proved to be a promising rapid tool for detecting potentially aflatoxigenic Aspergillus species. Full article

Honey bees play a vital role in ecosystem stability, and the need to monitor colony health has driven the development of IoT-based systems in beekeeping, with recent studies exploring both empirical and machine learning approaches to detect and analyze key hive conditions. In this study, we present an IoT-based system that leverages sensors to record and analyze the acoustic signals produced within a beehive. The captured audio data is transmitted to the cloud, where it is converted into mel-spectrogram representations for analysis. We explore multiple data pre-processing strategies and machine learning (ML) models, assessing their effectiveness in classifying queenless states. To evaluate model generalization, we apply transfer learning (TL) techniques across datasets collected from different hives. Additionally, we implement the feature extraction process and deploy the pre-trained ML model on a deep edge IoT device (Arduino Zero). We examine both memory consumption and execution time. The results indicate that the selected feature extraction method and ML model, which were identified through extensive experimentation, are sufficiently lightweight to operate within the device’s memory constraints. Furthermore, the execution time confirms the feasibility of real-time queenless state detection in edge-based applications. Full article

Honey bees (Apis mellifera ligustica) are essential pollinators in both ecosystems and agricultural production. However, their populations are declining due to various factors, including pesticide exposure. Despite their importance, the reproductive castes, particularly drones, remain understudied in terms of pesticide effects. To investigate the effects of azoxystrobin and picoxystrobin on honey bee drones, the drones were exposed to different concentrations of azoxystrobin and picoxystrobin for 14 days; the drone survival, body weight, nutrient content, reproductive organs, and sperm concentration were assessed. Results showed that exposure to both fungicides caused a significant reduction in drone survival rates, with survival rates decreasing progressively as the duration of exposure increased. Compared to the control group, the body weights of drones in all treatment groups were significantly lower on days 7 and 14. Nutrient analysis revealed that low concentrations of azoxystrobin and picoxystrobin increased protein levels, while free fatty acid content decreased significantly in all treatment groups. No significant changes were observed in the total carbohydrate content. Morphological examination of reproductive organs showed that the lengths of the mucus glands and seminal vesicles in drones were significantly shorter in the treatment groups compared to the control group. Furthermore, exposure to azoxystrobin and picoxystrobin resulted in a significant decline in sperm concentration in the drones. These findings indicate that azoxystrobin and picoxystrobin have adverse effects on the health and reproductive capacity of honey bee drones. The present study highlights the need to reassess the risks posed by these fungicides to pollinators, particularly given the critical role of drones in maintaining the genetic diversity and resilience of honey bee colonies. Further research is warranted to elucidate the underlying mechanisms of these effects and explore potential mitigation strategies. Full article

Antibiotic resistance is one of the most significant public health issues today. As a consequence, there is an urgent need for novel classes of antibiotics. This necessitates the development of highly efficient screening methods for the rapid identification of antibiotic-producing bacteria. Here, we describe a new method for high-throughput screening of antimicrobial compounds (AMC) producing halophilic bacteria. Our methodology used a newly designed 3D-printed Petri plate replicator used for drop deposition and colony replication. We employed this device in combination with a modified agar overlay assay to screen more than 7400 bacterial colonies. A total of 54 potential AMC producers were discovered at a success rate of 0.7%. Although 40% of them lost their antibacterial activity during the secondary screening, 22 strains retained inhibitory activity and were able to suppress the growth of one or more safe relatives of the ESKAPE group pathogens. The ethyl acetate extract from the most potent strain, Virgibacillus salarius POTR191, demonstrated moderate antibacterial activity against Enterococcus faecalis, Acinetobacter baumanii, and Staphylococcus epidermidis with minimal inhibitory concentrations of 128 μg/mL, 128 μg/mL, and 512 μg/mL, respectively. We propose that our replica plate assay could be used for target-based antimicrobial screening of various extremophilic bacteria. Full article