Search Results (190)

Salmonella is one of the main causes of food-borne illness worldwide. In most cases, Salmonella contamination can be traced back to food processing plants and/or to cross-contamination during food preparation. To avoid food-borne diseases, food processing plants use sanitizers and biocidal to reduce bacterial contaminants below acceptable levels. Despite these preventive actions, Salmonella can survive and consequently affect human health. This study investigates the adaptive capacity of the main Salmonella enterica serotypes isolated from the poultry production line, focusing on their replication, antimicrobial resistance, and biofilm formation under stressors such as acidic conditions, oxidative environment, and high osmolarity. Using growth curve analysis, crystal violet staining, and microscopy, we assessed replication, biofilm formation, and antimicrobial resistance under acidic, oxidative, and osmotic stress conditions. Disinfectant tolerance was evaluated by determining the Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal Concentration (MBC) of sodium hypochlorite. The antibiotic resistance was assessed using the Kirby–Bauer method. The results indicate that, in general, acidic and osmotic stress reduce the growth of Salmonella. However, no significant differences were observed specifically for serotypes Infantis, Heidelberg, and Corvallis. The S. Infantis isolates were the strongest biofilm producers and showed the highest prevalence of multidrug resistance (71%). Interestingly, S. Infantis forming biofilms required up to 8-fold higher concentrations of sodium hypochlorite for eradication. Furthermore, osmotic and oxidative stress significantly induced biofilm production in industrial S. Infantis isolates compared to a reference strain. Understanding how Salmonella responds to industrial stressors is vital for designing strategies to control the proliferation of these highly adapted, multi-resistant pathogens. Full article

In rapidly urbanizing environments, environmental stressors—such as air pollution, noise, heat, and green space depletion—substantially exacerbate public health burdens, contributing to the global rise of non-communicable diseases, particularly hypertension, cardiovascular disorders, and mental health conditions. Despite expanding research on green spaces and health (+76.9%, 2019–2025) and optimization and algorithmic approaches (+63.7%), the compounded and synergistic impacts of these stressors remain inadequately explored or addressed within current urban planning frameworks. This study presents a Mixed Methods Systematic Review (MMSR) to investigate the potential of AI-driven urban design optimizations in mitigating these multi-scalar environmental health risks. Specifically, it explores the complex interactions between urbanization, traffic-related pollutants, green infrastructure, and architectural intelligence, identifying critical gaps in the integration of computational optimization with nature-based solutions (NBS). To empirically substantiate these theoretical insights, this study draws on longitudinal 24 h dynamic blood pressure (BP) monitoring (3–9 months), revealing that chronic exposure to environmental noise (mean 79.84 dB) increases cardiovascular risk by approximately 1.8-fold. BP data (average 132/76 mmHg), along with observed hypertensive spikes (systolic > 172 mmHg, diastolic ≤ 101 mmHg), underscore the inadequacy of current urban design strategies in mitigating health risks. Based on these findings, this paper advocates for the integration of AI-driven approaches to optimize urban environments, offering actionable recommendations for developing adaptive, human-centric, and health-responsive urban planning frameworks that enhance resilience and public health in the face of accelerating urbanization. Full article

Forest mortality (FM) is influenced by several independent factors, including forest fragmentation (FF) at different spatial scales and multi-scales, site conditions, and stand characteristics. The aim of this study was to investigate the relationship and effect of FF at various spatial scales on the probability of Scots pine FM. The presented study also analyzed the relationship of the multi-scale fragmentation index effect on forest dieback. The relationship between multiple stressors emphasizes the distinct role of FF in influencing pine FM probability. Data on forest cover, deadwood volume of Scots pine forest, and environmental variables were obtained from the Forest Information System for Europe, the Polish National Forest Inventory, and existing databases, respectively. A generalized additive model approach was used to develop models. The results showed that, at small (50–600 m), large (800–3000 m), and multi spatial scales, the FF effect on Scots pine FM probabilities was statistically significant. There is a partial effect of multi-scale fragmentation on the probability of Scots pine FM, given a holistic view of the fragmentation effect that captures both small and large-scale effects. The study concludes that to calculate FF for a particular area, analyzing different scales and capturing multi-scale level fragmentation indices is crucial to studying the cumulative effect of fragmentation on the probability of Scots pine FM. Full article

MYB transcription factors constitute a diverse and functionally versatile family, playing central roles in regulating plant responses to a range of abiotic stressors. Based on previous research, we identified and characterized a maize MYB transcription factor gene, ZmMYBR24, which is involved in responses to salt, alkali, and low-temperature stress. This study aimed to investigate the function and mechanism of ZmMYBR24 in response to salt, alkali, and low-temperature stresses. We hypothesized that ZmMYBR24 regulates biosynthetic pathways to influence maize resistance to multiple abiotic stresses. The results indicate that ZmMYBR24 expression was markedly upregulated (p < 0.01) and the fold-change in gene expression ranged from 1.54 to 25.69 when plants were exposed to these combined stresses. Phenotypically, the zmmybr24 mutant line exhibited more pronounced inhibition of seedling and root growth under stress compared to the wild-type B73 line. Based on a correlation expression pattern analysis and mutant line evaluation, ZmMYBR24 was confirmed to be a positive regulatory transcription factor for multiple types of abiotic stress resistance. An RNA-seq analysis of both lines revealed differentially expressed genes (DEGs), with gene ontology (GO) and KEGG enrichment analyses indicating that ZmMYBR24 may mediate stress responses by modulating the expression of genes involved in flavonoid biosynthesis. Notable differences were observed in the expression of pathway-associated genes between the mutant and wild-type plants. A haplotype analysis across 80 inbred maize lines revealed 16 ZmMYBR24 coding region haplotypes—comprising 25 SNPs and 17 InDels—with HAP12 emerging as a superior haplotype. These results demonstrate that ZmMYBR24 enhances maize yields by regulating the flavonoid biosynthesis pathway in response to adverse climatic conditions including salt, alkaline conditions, and low temperatures. Collectively, these findings offer novel insights into the molecular mechanisms underlying maize adaptation to combined abiotic stresses and lay the groundwork for breeding programs targeting multi-stress resistance. Full article

Carbonaceous–siliceous–argillaceous rock-type uranium deposits, a major uranium resource in China, pose significant environmental risks due to heavy metal contamination. Geochemical investigations in the former Zoige uranium mine revealed elevated As, Cd, Cr, Cu, Ni, U, and Zn concentrations in soils and sediments, particularly at river confluences and downstream regions, attributed to leachate migration from ore bodies and tailings ponds. Surface samples exhibited high Cd bioavailability. The integrated BCR and mineral analysis reveals that Acid-soluble and reducible fractions of Ni, Cu, Zn, As, and Pb are governed by carbonate dissolution and Fe-Mn oxide dynamics via silicate weathering, while residual and oxidizable fractions show weak mineral-phase dependencies. Positive Matrix Factorization identified natural lithogenic, anthropogenic–natural composite, mining-related sources. Pollution assessments using geo-accumulation index and contamination factor demonstrated severe contamination disparities: soils showed extreme Cd pollution, moderate U, As, Zn contamination, and no Cr, Pb pollution (overall moderate risk); sediments exhibited extreme Cd pollution, moderate Ni, Zn, U levels, and negligible Cr, Pb impacts (overall extreme risk). USEPA health risk models indicated notable non-carcinogenic (higher in adults) and carcinogenic risks (higher in children) for both age groups. Ecological risk assessments categorized As, Cr, Cu, Ni, Pb, and Zn as low risk, contrasting with Cd (extremely high risk) and sediment-bound U (high risk). These findings underscore mining legacy as a critical environmental stressor and highlight the necessity for multi-source pollution mitigation strategies. Full article

As a critical ecologicalbarrier in the semi-arid to semi-humid transition zone of northern China, the interaction between afforestation and climatic stressors in the Yellow River Basin constitutes a pivotal scientific challenge for regional sustainable development. However, the synthesis effects of afforestation and climate on primary productivity require further investigation. Integrating multi-source remote sensing data (2000–2020), meteorological observations with the Standardized Precipitation Evapotranspiration Index (SPEI) and an improved CASA model, this study systematically investigates spatiotemporal patterns of vegetation net primary productivity (NPP) responses to extreme drought events while quantifying vegetation coverage’s regulatory effects on ecosystem drought sensitivity. Among drought events identified using a three-dimensional clustering algorithm, high-intensity droughts caused an average NPP loss of 23.2 gC·m⁻² across the basin. Notably, artificial irrigation practices in the Hetao irrigation district significantly mitigated NPP reduction to −9.03 gC·m⁻². Large-scale afforestation projects increased the NDVI at a rate of 3.45 × 10⁻⁴ month⁻¹, with a contribution rate of 78%, but soil moisture competition from high-density vegetation reduced carbon-sink benefits. However, mixed forest structural optimization in the Three-North Shelterbelt Forest Program core area achieved local carbon-sink gains, demonstrating that vegetation configuration alleviates water competition pressure. Drought amplified the suppressive effect of afforestation through stomatal conductance-photosynthesis coupling mechanisms, causing additional NPP losses of 7.45–31.00 gC·m⁻², yet the April–July 2008 event exhibited reversed suppression effects due to immature artificial communities during the 2000–2004 baseline period. Our work elucidates nonlinear vegetation-climate interactions affecting carbon sequestration in semi-arid ecosystems, providing critical insights for optimizing ecological restoration strategies and climate-adaptive management in the Yellow River Basin. Full article

Adhesive bonding has emerged as a transformative joining method across multiple industries, offering lightweight, durable, and versatile alternatives to traditional fastening techniques. This review provides a comprehensive exploration of adhesive bonding, from fundamental adhesion mechanisms, mechanical and molecular, to application-specific criteria and the characteristics of common adhesive types. Emphasis is placed on challenges affecting bond quality and longevity, including defects such as kissing bonds, porosity, voids, poor cure, and substrate failures. Critical aspects of surface preparation, bond line thickness, and adhesive ageing under environmental stressors are analysed. Furthermore, this paper highlights the pressing need for sustainable solutions, including the disassembly and recyclability of bonded joints, particularly within the automotive and aerospace sectors. A key insight from this review is the lack of a unified framework to assess defect interaction, stochastic variability, and failure prediction, which is mainly due complexity of multi-defect interactions, the compositional expense of digital simulations, or the difficulty in obtaining sufficient statistical data needed for the stochastic models. This study underscores the necessity for multi-method detection approaches, advanced modelling techniques (i.e., debond-on-demand and bio-based formulations), and future research into defect correlation and sustainable adhesive technologies to improve reliability and support a circular materials economy. Full article

Heat stress (HS), an important environmental stressor for healthy poultry farming, has been shown to have a detrimental effect on production performance and induce serious diseases through immune system damage. As the avian peripheral immune system’s primary organ, spleen is subject to complex biological processes in response to HS injury. Histopathological characterization demonstrated that HS resulted in the destruction of the splenic red and white medulla, a decrease in cell density and organ atrophy. These changes directly impaired pathogen clearance and immune surveillance. At the physiological level, the impact of HS is characterized by disrupted metabolic homeostasis through interrupting neuroendocrine function. This, in turn, results in a significant suppression of humoral immune response. The oxidative-inflammatory cascade constitutes the core pathology of this disease. Energy metabolism disorder triggered by mitochondrial dysfunction and redox imbalance form a vicious circle, which promotes apoptosis signaling cascade. Meanwhile, over-activation of intrinsic immune system triggers a series of inflammatory factors, which further amplifies effects of tissue damage. The present prevention and control strategies are centered on synergistic anti-inflammatory and antioxidant interventions with nutrient modulators and plant actives. Nevertheless, it is imperative for future studies to incorporate multi-omics technologies in order to analyze the metabolic mechanisms and patterns of stress and establish a precise intervention strategy based on immune homeostatic regulation. This review systematically investigated the multilevel regulatory mechanisms of HS-induced spleen injury, which provides a theoretical basis for the mechanistic analysis and technological innovation of the prevention and control of HS syndrome in poultry. Full article

Atrial fibrillation (AF) is the most prevalent sustained arrhythmia, associated with significant morbidity, mortality, and healthcare burdens. Despite therapeutic advances, recurrence rates remain high, particularly in persistent AF, underscoring the need for deeper mechanistic insight. Epigenetic regulation—comprising DNA methylation, histone modifications, chromatin remodeling, RNA methylation, and non-coding RNAs—has emerged as a key contributor to the structural, electrical, and inflammatory remodeling underlying AF. These mechanisms operate at the interface of genetic susceptibility and environmental exposure, offering a dynamic framework for understanding disease progression. Systemic stressors such as aging, obesity, diabetes, hypertension, hypoxia, and alcohol have been shown to induce epigenetic reprogramming in atrial tissue, further promoting atrial cardiomyopathy and arrhythmogenesis. Additionally, circulating epigenetic markers, particularly microRNAs, are being investigated for their potential in AF diagnosis, risk stratification, and therapeutic monitoring. Therapeutic strategies targeting epigenetic pathways—ranging from histone deacetylase inhibitors and miRNA-based therapeutics to CRISPR/dCas9-mediated epigenome editing—are under investigation. Additionally, sodium-glucose cotransporter 2 inhibitors may indirectly influence epigenetic programs and miRNA expression relevant to atrial remodeling. While promising, these approaches require further validation in terms of safety, delivery specificity, and long-term efficacy. High-resolution epigenomic mapping and integrative multi-omic approaches may enhance understanding of AF heterogeneity and enable personalized treatment strategies. This review provides an integrated appraisal of epigenetic mechanisms in AF and outlines their emerging diagnostic and therapeutic relevance. Full article

We present and demonstrate a highly birefringent fiber Bragg grating (Hi-Bi FBG) that was fabricated using a femtosecond laser to induce a sawtooth stress region near the FBG. The FBG is fabricated with a femtosecond laser point-by-point method, while the sawtooth stress region is generated in fiber cladding using the femtosecond laser along a sawtooth path. This sawtooth stressor can introduce an anisotropic and asymmetric refractive index profile in the cross-section of the fiber, resulting in additional birefringence up to 2.97 × 10⁻⁴ along the axial direction of the FBG. The central wavelengths of the Hi-Bi FBG at the fast and slow axes exhibit different sensitivities to temperature and strain, allowing simultaneous measurement of the strain and temperature by tracking the resonant wavelength shifts in the two axes. The experimental results show that the temperature sensitivities of the fast and slow axes are 10.32 pm/°C and 10.42 pm/°C, while the strain sensitivities are 0.91 pm/µε and 0.99 pm/µε. The accuracy of this proposed sensor in measuring strain and temperature is estimated to be 2.2 µε and 0.2 °C. This approach addresses the issue of cross-sensitivity between temperature and strain and offers some advantages of low cost, compact size, and significant potential for advancements in practical multi-parameter sensing applications. Full article

Objectives: To evaluate how a 10-day multi-stressor field-training course—combining high physical and psycho-emotional demands, caloric restriction, and severe sleep deprivation—affects systemic oxidative/antioxidative status and biomarkers of nucleic-acid and skeletal-muscle damage in trained military cadets. Methods: Seventy-five healthy cadets (8 women, 67 men; 22–34 y) completed the course. Standardised operational rations (700–800 kcal day⁻¹) and two 20 min tactical naps per 24 h were enforced. Pre- and post-course venous blood was collected after an overnight fast. Plasma superoxide-dismutase activity (SOD), reduced and oxidised glutathione (GSH, GSSG), malondialdehyde (MDA), and hydrogen peroxide (H₂O₂) were quantified by colourimetric/fluorometric assays; 8-hydroxy-2-deoxyguanosine (8-OHdG) and myoglobin were measured by ELISA. The oxidative-stress index (OSI) was calculated as GSSG·GSH⁻¹. Within-subject differences were assessed with Wilcoxon signed-rank tests; associations between biomarker changes were explored by Spearman correlation. Results: After training, GSH (+175%, p < 0.001) and GSSG (+32%, p < 0.001) rose significantly, whereas SOD (−19%, p = 0.002), H₂O₂ (−20%, p = 0.015), MDA (−50%, p < 0.001), 8-OHdG (−23%, p < 0.001), and OSI (−47%, p < 0.001) declined. Myoglobin remained unchanged (p = 0.603). Reductions in MDA correlated inversely with increases in GSSG (rₛ = −0.25, p = 0.041), while H₂O₂ changes correlated positively with GSSG (rₛ = 0.25, p = 0.046), indicating a glutathione-driven adaptive response. Conclusions: Ten consecutive days of vigorous, calorie- and sleep-restricted field training elicited a favourable redox adaptation characterised by enhanced glutathione-mediated antioxidant capacity and lower circulating oxidant concentrations, without evidence of DNA or skeletal-muscle damage. The data suggest that, in physically prepared individuals, prolonged multi-stressor exposure can strengthen endogenous antioxidant defences rather than precipitate oxidative injury. Full article

Persistent environmental contaminants pose a substantial threat to agricultural ecosystems, necessitating robust methodologies for evaluation and mitigation of their effects. This study establishes a direct correlation between environmental impact assessment and sustainable agricultural management, showing the feasibility of using multi-scale bioindication and remote sensing technology to effectively monitor the impact of soil pollution in agricultural ecosystems. The key values of this research lie in the ability of the described approach to integrate advanced proximal/remote sensing and in situ analyses to assess the effects of soil contamination on bioindicators, providing a comprehensive framework for evaluating environmental stressors. The proposed methodology was tested on maize (Zea mays L.) and employs unmanned aerial vehicle-based multi/hyperspectral and thermal imaging to detect vegetation stress indicators such as normalized difference vegetation index and thermal anomalies. The interdisciplinary approach adopted in this research significantly enhances the value of the study by not only focusing on isolated results but also validating the entire methodological workflow. This cross-disciplinary integration ensures that the workflow retains its relevance across various environmental scenarios, enriching the results’ applicability and providing a robust framework for ongoing studies. The research objective of this work was achieved through experimental tests on soils contaminated with heavy metals and organic pollutants exceeding regulatory thresholds that revealed distinct spectral and thermal signatures, demonstrating the efficacy of integrated sensing for detailed environmental assessment. The findings underscore the role of bioindicators as pivotal tools for bridging environmental monitoring and sustainability by providing actionable insights into pollutant impacts and their cascading effects on ecosystems and human health. By equipping stakeholders with precise contamination detection tools, this study aims to provide a methodological approach to expand environmental impact assessment frameworks, supporting sustainable decision-making and risk management. These methodologies contribute to aligning agricultural practices with broader sustainability objectives, ensuring resilient food systems and ecosystem health. Full article

Feather pecking (FP) is a significant welfare and economic problem in laying hen husbandry. While there is growing evidence that the glutamatergic system plays a crucial role in regulating FP behavior, the biological mechanisms remain unclear, largely due to the limited uptake of peripheral glutamate across the blood–brain barrier (BBB). Here, we applied a multi-omics approach combined with physiology assays to answer this question from the perspective of the gut–brain axis. A total of 108 hens were randomly assigned to two groups (treatment and control) with six replicates each, and the treatment group was subjected to chronic environmental stressors including re-housing, noise, and transport. We found that chronic exposure to environmental stressors induced severe FP, accompanied by reduced production performance and increased anxiety- and depression-related behaviors, compared to controls. In addition, the immune system was potentially disrupted in FP chickens. Notably, gut microbiota diversity and composition were significantly altered, leading to decreased microbial community stability. Non-targeted metabolomic analysis identified a variety of differential metabolites, primarily associated with arginine and histidine biosynthesis. A significant increase in glutamate levels was also observed in the hippocampus of FP chickens. Transcriptome analysis revealed the upregulated expressions of glutamate-related receptors GRIN2A and SLC17A6 in the hippocampus. Correlation analysis indicated that GRIN2A and SLC17A6 are positively associated with arginine levels in the duodenum, while Romboutsia in the duodenum is negatively correlated with arginine. These findings suggest that intestinal bacteria, including Romboutsia, may influence FP behavior by altering plasma arginine and histidine levels. These changes, in turn, affect glutamate levels and receptor gene expression in the hippocampus, thereby regulating the glutamatergic system. Our research offers insights into novel strategies for mitigating harmful behaviors in poultry farming, with potential benefits for animal performance and welfare. Full article

Intertidal organisms experience daily environmental fluctuations, including changes in temperature, UV radiation, and aerial exposure during low tide, requiring physiological strategies for survival. One adaptation is the “preparation for oxidative stress” (POS), where antioxidants are upregulated preemptively to mitigate oxidative damage. While POS has been documented in over 120 species, in the case of intertidal species, most studies focus on single stressors under controlled-laboratory conditions. This study investigated POS in the sea urchin Echinometra lucunter under natural multi-stress conditions. Sampling occurred over a single day (from 5 a.m. to noon), analyzing three conditions: submerged (S), aerially exposed for 2 h (AE), and reimmersed for 2 h (R). There was a ~4 °C temperature increase in the AE group compared to the S group, with a peak of solar radiation during reoxygenation. Antioxidant enzyme activity—catalase, glutathione transferase (GST), and superoxide dismutase (SOD)—and lipid peroxidation (TBARS) were assessed in gonad and intestine tissues. GST activity increased by fourfold in the intestines of AE individuals, while TBARS was elevated in gonads, where no antioxidant upregulation happened. These results suggest that the POS-response (increase in GST) was triggered by the interaction of temperature and aerial exposure. This research emphasizes the critical importance of field studies in understanding complex, natural multi-stressor environments. Full article

Accurate estimation of green canopy cover (GCC) in rubber plantations is crucial for monitoring vegetation health and assessing stress impacts. This study validates satellite-derived GCC estimates using unmanned aerial vehicle (UAV)-based remote sensing, ground observations, spaceborne remote sensing (satellite imagery), and supervised machine learning regression approaches. Sentinel-2 and Landsat imagery were utilized to derive spectral vegetation indices (SVIs) under varying stress conditions, while UAV-based GCC assessments provided high-resolution reference data for validation. The findings revealed that while certain SVIs exhibited strong correlations with canopy density under stable conditions, their predictive accuracy declined significantly during extreme stress events, such as Pestalotiopsis outbreaks and seasonal leaf fall periods. To improve estimation accuracy, supervised machine learning regression models were developed, with Random Forest (RF) outperforming Support Vector Machines (SVMs), Classification and Regression Trees (CARTs), and Linear Regression (LR). RF achieved the highest predictive accuracy (R² = 0.82, RMSE = 6.48, MAE = 4.97), demonstrating its reliability in capturing non-linear interactions between canopy heterogeneity and environmental stressors. These results highlight the limitations of traditional vegetation indices and emphasize the importance of multi-sensor integration and advanced modeling techniques for more precise GCC monitoring. Full article