Search Results (6,208)

Rhodotorula spp. are ubiquitous red-pigmented yeasts increasingly reported as opportunistic animal pathogens. Recognition matters because underdiagnosis can misguide therapy, especially in companion-animal otitis externa. This review supports laboratory and clinical decisions by summarising taxonomy and ecology, host risk factors, diagnostics, virulence factors, antifungal susceptibility, and veterinary cases. This review addresses: (1) taxonomy and ecology; (2) clinical epidemiology and predisposing factors (immunomodulation, prior antibacterial therapy, chronic inflammation); (3) diagnostics—cytology, organism burden, repeat or pure culture, MALDI-TOF MS, ITS sequencing—with a brief comparison of feasibility in veterinary practice; (4) virulence factors—adhesion and biofilm on abiotic surfaces, hydrolytic enzymes, capsule in some strains, haemolysins, urease, and carotenoids that protect against oxidative stress; (5) antifungal susceptibility and therapy—intrinsic resistance to echinocandins, often high azole MICs, and the most consistent in vitro activity of amphotericin B ± flucytosine; and (6) a synthesis of veterinary case reports. Rhodotorula spp. should not be dismissed as contaminants when clinical signs match laboratory evidence; distinguishing infection from colonisation requires clinicomicrobiological correlation. This review highlights the need for standardised susceptibility testing and veterinary breakpoints, prospective data on burden and outcomes, better data on biofilm behaviour on clinical materials, environmental surveillance, and practical diagnostic and treatment guidance. Full article

Soil nitrogen (N) and phosphorus (P) loss in watersheds is a critical source of water pollution. This study explores the spatial distribution, release potential, and environmental impacts of soil N and P in the downstream Daliao River basin by integrating field investigations and simulation experiments. Results showed that total nitrogen content in soils ranged from 256.09 to 3362.75 mg/kg, while that in sediments ranged from 114.85 to 1640.54 mg/kg. Total phosphorus content in soils varied from 250.18 to 1142.69 mg/kg, whereas in sediments it ranged from 327.23 to 586.24 mg/kg. The ammonia nitrogen release potentials of soils collected from rice paddies, corn farmlands, roadsides, and reed wetlands were 0.75, 0.86, 0.70, and 8.65 mg/L, respectively, with corresponding total phosphorus release potentials of 0.61, 1.01, 0.31, and 1.52 mg/L. For sediments, ammonia nitrogen and total phosphorus release potentials ranged from 0.96 to 1.21 mg/L and 0.44 to 0.52 mg/L, respectively. Temperature, pH, and dissolved oxygen were important factors influencing nitrogen and phosphorus release from soils and sediments. The export of nitrogen and phosphorus from soil reached 50.50 t/a and 21.63 t/a, respectively. During the soil erosion process in the Daliao River Basin, phosphorus exhibited a high release potential and served as the primary pollutant, whereas the release mechanism of ammonia nitrogen was more complex, showing seasonal variability. Soils in the downstream Daliao River basin have large specific surface areas and may pose a high pollution risk after discharge into water bodies due to prolonged adsorption of pollutants. It is recommended to propose promoting soil testing-based fertilization, constructing ecological engineering projects, developing sponge cities, and conducting environmental dredging to reduce N and P release from agricultural lands, construction areas, natural wastelands, and sediments. Full article

Accurate prediction of blast-induced air overpressure (AOp) is vital for environmental management and safety in mining and construction. Traditional empirical models are simple but fail to capture complex meteorological effects, while accurate black-box machine learning models lack interpretability, creating a significant dilemma for practical engineering. This study resolves this by applying explainable AI (XAI) to develop a transparent, “white-box” model that explicitly quantifies how meteorological parameters, wind speed, direction, and air temperature influence AOp. Using a dataset from an urban excavation site, the methodology involved comparing a standard USBM empirical model and a Multivariate Non-linear Regression (MNLR) model against a Symbolic Regression (SR) model implemented with the PySR tool. The SR model demonstrated superior performance on an independent test set, achieving an R² of 0.771, outperforming both the USBM (R² = 0.665) and MNLR (R² = 0.698) models, with accuracy rivaling a previous “black-box” neural network. The key innovation is SR’s ability to autonomously generate an explicit, interpretable equation, revealing complex, non-linear relationships between AOp and meteorological factors. This provides a significant engineering contribution: a trustworthy, transparent tool that enables engineers to perform reliable, meteorologically informed risk assessments for safer blasting operations in sensitive environments like urban areas. Full article

Taking into account both the health and environmental aspects of food, the EAT-Lancet Commission proposed a healthy reference diet (Planetary Health Diet—PHD). The aim of this narrative review is to summarize the results obtained in epidemiological studies on the association between the PHD and risk factors, non-communicable diseases, and cause-specific mortality. The literature search was conducted in February 2025 and was based on the PubMed electronic database. The results of this review are divided into four parts, which include the results of cohort studies, cross-sectional studies, case–control studies, and meta-analyses. This review, showing what types of studies have been conducted so far, allows for a summary of the current knowledge of the relationship between the PHD and risk factors, non-communicable diseases, and cause-specific mortality. Cohort studies provided most of the results, which confirmed that higher adherence to the PHD has a beneficial effect on human health, especially taking into account the lower risk of diabetes, cardiovascular disease (CVD) and CVD mortality, cancer and cancer mortality, as well as all-cause mortality. However, it is concluded that the association between the PHD and stroke, different types of stroke, hypertension, dyslipidemia, and some specific types of cancer must be confirmed. Specifically, randomized controlled trials should be conducted, as, to our knowledge, there is a lack of these types of studies to date. Such studies should be conducted in different regions using the Planetary Health Diet adapted to the local, cultural, geographical, and demographical aspects of a particular region. Full article

This narrative review explores the role of artificial light at night (ALAN) as an emerging environmental determinant of liver and metabolic health, with particular emphasis on its contribution to metabolic dysfunction-associated steatotic liver disease (MASLD). The objective was to synthesize and critically evaluate experimental and epidemiological evidence linking nocturnal light exposure, circadian disruption, and hepatic metabolic alterations. Literature was retrieved from PubMed, Scopus, Web of Science, and Google Scholar databases covering the period 1980–2025 using predefined search terms related to ALAN, circadian rhythm disturbance, melatonin suppression, sleep disruption, and MASLD. Relevant experimental studies in animal models and observational studies in humans were included. Evidence indicates that blue-enriched light (~460–480 nm) suppresses melatonin, desynchronizes central and hepatic circadian clocks, and disrupts glucose–lipid metabolism, leading to insulin resistance, oxidative stress, and hepatic steatosis. Chronic ALAN exposure also alters gut microbiota composition and increases intestinal permeability, suggesting a light–gut–liver axis in MASLD pathogenesis. Human epidemiological studies associate higher environmental ALAN exposure with obesity, metabolic syndrome, and poor sleep quality—recognized risk factors for MASLD. Recognizing ALAN as a modifiable environmental exposure highlights the need for public health strategies and clinical guidelines to mitigate its metabolic impact through improved lighting design and sleep hygiene. Full article

Under global warming, the rising frequency and intensity of extreme climate events pose challenges to disaster prevention and sustainable development. Based on daily meteorological observations from 1970 to 2020 in Jilin Province, this study analyzes the spatiotemporal evolution and driving mechanisms of extreme temperature and precipitation events. Linear trend analysis and the Mann–Kendall test were employed to examine temporal trends and abrupt change years in extreme temperature and precipitation indices. Wavelet analysis was used to identify dominant periodicities and multi-scale variability. Empirical Orthogonal Function Analysis (EOF) revealed the spatial distribution characteristics of variability in extreme precipitation and temperature across Jilin Province, identifying high-incidence zones for extreme temperature and precipitation events. Additionally, Pearson correlation analysis was to investigate the correlation patterns between extreme climate indices in Jilin Province and geographical environmental factors alongside atmospheric circulation indicators. Results show that: (1) Warm-related temperature indices display significant upward trends, while cold-related indices generally decline, with abrupt changes mainly occurring in the 1980s–1990s and dominant periodicities of 3–5 years. Precipitation indices, though variable, show general increases with 3–4year cycles. (2) Spatially, most indices follow an east–high to west–low gradient. Temperature indices exhibit spatial coherence, while precipitation indices vary, especially between the northwest and central-southern regions. (3) The Arctic Oscillation (AO) exhibits a significant negative correlation with the extreme cold index, with correlation coefficients ranging from −0.31 to −0.46. It shows a positive correlation with the extreme warm index, with correlation coefficients between 0.16 and 0.18, confirming its regulatory role in cold air activity over Northeast China, particularly elevation and latitude, influence the spatial distribution of precipitation. These findings enhance understanding of extreme climate behaviors in Northeast China and inform regional risk management strategies. Full article

Obesity and overweight conditions, frequently accompanied by hypercholesterolemia, are major risk factors for cardiovascular disease. Lifestyle interventions remain the cornerstone of non-pharmacological treatment; however, their effectiveness in improving lipid profiles is limited. Intermittent hypoxic training (IHT) has recently emerged as a potential strategy to enhance metabolic outcomes. This study aimed to evaluate the effects of a 4-week intensive IHT program combined with a calorie-restricted diet on lipid profile and body composition in men with overweight or obesity and secondary hypercholesterolemia. Twenty physically inactive men (35.3 ± 5.4 years) were randomly assigned to either a hypoxic group (H, n = 10) or a normoxic control group (C, n = 10). Both groups followed the same training protocol and diet, differing only in environmental training conditions. Body composition, resting metabolic rate, and blood lipid parameters (total cholesterol, TC; high-density lipoprotein cholesterol, HDL-C; low-density lipoprotein cholesterol, LDL-C; non-high-density lipoprotein cholesterol, non-HDL-C; Triglycerides, TG) were assessed before and after the intervention. Compared with the C group, participants in the H group achieved significantly greater reductions in body mass (−5.4% vs. −2.6%, p < 0.05) and fat mass (−14.7% vs. −7%, p < 0.01). IHT also induced marked decreases in TC (−22.6%, p < 0.001), LDL-C (−25.8%, p < 0.001), non-HDL-C (−26.5%, p < 0.001), and TG (−31.4%, p < 0.01), along with a significant improvement in the atherogenic index of plasma (AIP, −24.4%, p < 0.05). In contrast, the C group showed only non-significant downward trends. No significant changes in HDL-C were observed in either group. These findings suggest that IHT combined with dietary restriction produces more favorable changes in lipid profile and body composition than normoxic training. IHT may therefore represent a promising adjunct to conventional lifestyle-based interventions in the management of obesity-related hypercholesterolemia. Full article

The Lower Passaic River (LPR), located within the New York/New Jersey Harbor Estuarine System, has experienced long-term industrial activities, resulting in elevated concentrations of trace metals in sediment and water. This study aims to assess the bioaccumulation behavior, potential human health risks, and sources of copper (Cu), lead (Pb), and mercury (Hg) in the LPR. Trace metal concentrations were measured in water, sediment, and seven edible aquatic species. Data were analyzed using statistical approaches, and evaluated by bioaccumulation factors (BAFs) and human health risk assessments based on U.S. Environmental Protection Agency (USEPA) guidelines. Results showed that Hg exhibited the highest bioaccumulation potential among the studied metals, except for Cu in Callinectes sapidus. Non-carcinogenic risks from the consumption of aquatic species followed the order Cu > Hg > Pb, with total target hazard quotient (TTHQ) values below 1, suggesting the non-carcinogenic health risk is negligible for adults and for most species in children, except C. sapidus and Morone americana. Carcinogenic risks for all species were within the acceptable threshold (Target Risk < 1 × 10⁻⁴). Sensitivity analysis indicated that body weight and exposure duration primarily influenced children’s carcinogenic risk, whereas trace metal concentrations were more significant for adults. Overall, this study provides insight into contaminant dynamics and health implications in a legacy-contaminated urban river system. Full article

Landslide disasters pose severe threats to mountainous regions, where accurate monitoring and scientific prediction are crucial for early warning and risk mitigation. This study addresses this challenge by focusing on the Outang Landslide, a representative large-scale bank slope in the Three Gorges Reservoir area known for its significant deformation responses to rainfall and reservoir-level fluctuations. The landslide’s behavior, characterized by notable hysteresis and nonlinear trends, poses a significant challenge to accurate prediction. To address this, we derived high-precision time-series deformation data by applying atmosphere-corrected Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) to Sentinel-1A imagery, with validation from GNSS measurements. A systematic analysis was then conducted to uncover the correlation, hysteresis, and spatial heterogeneity between landslide deformation and key influencing variables (rainfall, water level, temperature). Furthermore, we proposed a Spatio-Temporal Enhanced Convolutional Neural Network (STE-CNN), which innovatively converts influencing variables into grayscale images to enhance spatial feature extraction, thereby improving prediction accuracy. The results indicate that: (1) From June 2022 to March 2024, the landslide showed an overall downward displacement trend, with maximum settlement and uplift rates of −49.34 mm/a and 21.77 mm/a, respectively; (2) Deformation exhibited significant correlation, hysteresis, and spatial variability with environmental factors, with dominant variables shifting across seasons—leading to intensified movement in flood seasons and relative stability in dry seasons; (3) The improved STE-CNN outperforms typical prediction models in forecasting landslide deformation.This study presents an integrated methodology that combines InSAR monitoring, multi-factor mechanistic analysis, and deep learning, offering a reliable solution for landslide early warning and risk management. Full article

Sleep is essential for child development, influencing cognition, emotional regulation, behavior, and physical health. Recent studies increasingly frame sleep as both a key developmental process and a modifiable factor shaped by, and shaping environmental risks—including digital screen exposure and psychosocial stress. This systematic review synthesized empirical findings from cross-sectional and cohort studies published between 2019 and 2024 on the associations between sleep duration, quality, and patterns and developmental outcomes in typically developing children aged 6–12 years. Searches were conducted in EBSCO, Scopus, and Web of Science databases, yielding 99 records, of which 20 met inclusion criteria. Methodological quality was evaluated using Joanna Briggs Institute tools. Findings show consistent associations between better sleep and enhanced cognitive performance, emotional well-being, and reduced behavioral problems. Some studies identified sleep as a mediator between screen use and behavioral difficulties, whit additional moderating effects related to gender and socioeconomic status. However, most studies used cross-sectional designs and self-reported measures, limiting causal interpretation. Overall, sleep emerge as a potentially modifiable factor influencing developmental outcomes, based on correlational evidence. Future research should prioritize longitudinal and ecologically valid designs, objective measures, and computational approaches to identify sleep-related risk profiles and guide early interventions. Full article

Attention-deficit/hyperactivity disorder (ADHD) in adults has become an increasingly recognized clinical entity, with growing attention in research and healthcare settings. ADHD can significantly affect multiple domains of adult functioning, including education, employment, interpersonal relationships, and both mental and physical health. However, despite the expanding body of literature, gaps in understanding persist. This narrative review synthesizes current evidence on adult ADHD. The literature was systematically searched in databases such as PubMed, Scopus, and PsycINFO using predefined keywords related to ADHD in adults. Inclusion criteria focused on peer-reviewed articles published between 2010 and 2025, addressing epidemiology, etiology, diagnosis, treatment, and functioning. Exclusion criteria included studies with pediatric populations only or lacking methodological rigor. ADHD in adults is prevalent worldwide, with considerable heterogeneity across studies. Its etiology involves complex interactions between genetic, neurobiological, and environmental factors. Clinical presentation in adulthood differs from childhood, with symptoms such as inattention, emotional dysregulation, and executive dysfunction predominating. Diagnostic challenges include retrospective assessment of childhood symptoms and comorbidity with mood and anxiety disorders. Pharmacotherapy and cognitive–behavioral interventions show efficacy, particularly when combined in integrated care models. ADHD negatively affects quality of life and occupational and social functioning and increases the risk of comorbid disorders, including psychoactive substance use. Adult ADHD is a multifaceted condition requiring a comprehensive, multidisciplinary approach to diagnosis and management. Future research should aim to refine diagnostic tools, explore neurobiological markers, and tailor interventions to individual profiles. Expanding knowledge on adult ADHD will improve identification, treatment outcomes, and overall quality of life for affected individuals. Full article

Background: Chronic obstructive pulmonary disease (COPD) is a complex condition influenced by both environmental and genetic factors. Among the genetic determinants, polymorphisms in the CHRNA3/5 and EPHX1 genes have been implicated in nicotine dependence and susceptibility to COPD in several populations. However, evidence remains limited in admixed populations such as Brazilians. Methods: This cross-sectional study investigated the association between CHRNA3 (rs1051730, rs8034191) and EPHX1 (rs2234922) polymorphisms with tobacco nicotine dependence and COPD in a Brazilian cohort. Genotyping was performed using TaqMan^® SNP assays, and pulmonary function was assessed via spirometry according to ATS/ERS standards. Associations between genetic variants, tobacco intake, and COPD status were evaluated using χ² and Fisher’s exact tests, with odds ratios (ORs) and 95% confidence intervals (CIs). Post hoc power analyses were conducted to estimate detectable effect sizes. Results: A total of 123 active or former smokers were analyzed. The CHRNA3 variants (rs1051730 and rs8034191) showed a trend toward higher prevalence among individuals with heavy tobacco intake (>40 pack-years), though no significant allelic or genotypic differences were found between COPD and control groups (p > 0.05). The EPHX1 rs2234922 A allele was significantly more frequent in COPD patients, suggesting increased disease risk (p < 0.05), while the GG genotype appeared protective. Post hoc power analyses indicated moderate power (≈0.56–0.63) for the observed associations. Conclusions: In this Brazilian population, the CHRNA3/5 polymorphisms may influence nicotine dependence, while EPHX1 rs2234922 appears to be associated with COPD susceptibility. These findings support a potential genetic contribution to disease risk and tobacco nicotine dependence, warranting further large-scale studies to confirm these associations and explore their therapeutic implications. Full article

Background: Clear cell renal cell carcinoma (ccRCC) is a prevalent urological malignancy, accounting for approximately 1.6% of all cancer-related deaths in 2022. While endocrine-disrupting chemicals (EDCs) have been implicated as risk factors for ccRCC, the toxicological profiles and immune mechanisms underlying Bisphenol A (BPA) exposure in ccRCC progression remain inadequately understood. Materials and Methods: Protein–protein interaction (PPI) analysis and visualization were performed on overlapping genes between ccRCC and BPA exposure. This was followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses to elucidate potential underlying mechanisms. Subsequently, 108 distinct machine learning algorithm combinations were evaluated to identify the optimal predictive model. An integrated CoxBoost and Ridge regression model was constructed to develop a prognostic signature, the performance of which was rigorously validated across two independent external datasets. Finally, molecular docking analyses were employed to investigate interactions between key genes and BPA. Results: A total of 114 overlapping targets associated with both ccRCC and BPA were identified. GO and KEGG analyses revealed enrichment in cancer-related pathways, including pathways in cancer, endocrine resistance, PD-L1 expression and PD-1 checkpoint signaling, T-cell receptor signaling, endocrine function, and immune responses. Machine learning algorithm selection identified the combined CoxBoost-Ridge approach as the optimal predictive model (achieving a training set concordance index (C-index) of 0.77). This model identified eight key genes (CHRM3, GABBR1, CCR4, KCNN4, PRKCE, CYP2C9, HPGD, FASN), which were the top-ranked by coefficient magnitude in the prognostic model. The prognostic signature demonstrated robust predictive performance in two independent external validation cohorts (C-index = 0.74 in cBioPortal; C-index = 0.81 in E-MTAB-1980). Furthermore, molecular docking analyses predicted strong binding affinities between BPA and these key targets (Vina scores all <−6.5 kcal/mol), suggesting a potential mechanism through which BPA may modulate their activity to promote renal carcinogenesis. Collectively, These findings suggested potential molecular mechanisms that may underpin BPA-induced ccRCC progression, generating hypotheses for future experimental validation. Conclusions: These findings enhance our understanding of the molecular mechanisms by which BPA induces ccRCC and highlight potential targets for therapeutic intervention, particularly in endocrine and immune-related pathways. This underscores the need for collaborative efforts to mitigate the impact of environmental toxins like BPA on public health. Full article

This study establishes a structured framework to identify and evaluate risk factors that may hinder the achievement of sustainable development goals in green buildings and sustainable infrastructure projects. Fifty-six risk factors are identified and categorized into four risk groups, including stakeholder and management, financial and economic, technological and resource, and process and regulatory risks. The risk factors are evaluated across four risk indices related to probability of occurrence, manageability, impact on building performance, and project cost. Further, the severity of risks based on combining the four indices’ effects is quantified using a new Green Risk Index (GRI), while the relationships among all risk indices are determined. The strongest positive correlation is observed between the probability and the impact on cost, whereas a negative relationship is found between the probability and manageability. The analysis demonstrates that a risk factor related to the lack of knowledge about energy-saving procedures and environmental concerns during the design phase is the most critical, as it has the highest severity based on the GRI. “Non-compliance with environmental standards in project design” is also identified as a critical risk factor due to its high effect on building performance. Additionally, the risk factor associated with unstable funds from investors shows the highest effect on manageability. Process and regulatory is identified as the most critical risk group, encompassing the maximum number of key risk factors, and has the highest average weight related to the GRI. These findings reveal crucial vulnerabilities and underline the importance of targeted strategies to strengthen the use of nature-based solution frameworks for mitigating the risk effects in green buildings and sustainable infrastructures. Full article

The escalating threat of cyanobacterial blooms necessitates a deeper understanding of the environmental factors regulating their toxicity. While light intensity effects are well-documented, it remains unclear whether photoperiod regulates microcystin (MC) production. This study investigates the effects of five light–dark (LD) cycles on the growth and MC-LR production of two Microcystis strains in batch culture under a light intensity of 25 μmol m⁻² s⁻¹. Longer photoperiods enhanced early growth, although long-term biomass accumulation proved strain-dependent. Regarding toxin production, cellular MC-LR (total toxin per cell) during the initial 9-day phase was analyzed using a mixed-effects model. The analysis revealed significant main effects of photoperiod and cell density, supporting both direct and growth-mediated indirect effects of photoperiod. Moreover, a significant strain × photoperiod × day interaction (p < 0.001) was observed, indicating additional strain-specific and time-dependent regulation. Conversely, a general linear model of the strictly intracellular MC-LR at the 27-day endpoint showed significant independent effects of photoperiod and cell density, with no interaction. The photoperiod effect strengthened after controlling for cell density. These findings reveal a phase-dependent regulation of toxicity, suggesting that risk assessment based solely on biomass is inadequate. Sustainable bloom management should therefore incorporate photoperiod dynamics and adopt phase-specific strategies. Full article