Search Results (5,427)

Background: Non-melanoma skin cancer (NMSC) is the most frequent cancer in fair-skinned populations and represents a growing public health concern due to its impact in terms of morbidity and treatment costs. While some meta-analyses have investigated cigarette smoking as a risk factor for NMSC, less is known about its prognostic implications in patients with NMSC. This systematic review and meta-analysis aims to fill this gap by assessing the association between smoking habits and survival in patients with NMSC. Methods: A systematic search was conducted in PubMed and EMBASE up to 25 February 2025, to identify prospective studies of patients with histologically confirmed NMSC that evaluated the association between smoking habits and survival. Study-specific hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) were pooled using random effects meta-analysis models. Results: A total of five studies published between 2015 and 2022 were included. The meta-analysis revealed that being a current or ever smoker at diagnosis was associated with a worse overall survival (summary HR 2.42, 95% CI 1.91–3.06). A similar result was observed when smoking exposure was assessed in terms of pack-years or number of cigarettes per day (summary HR 2.44, 95% CI 2.02–2.93). Conclusions: Our findings indicate that cigarette smoking is a negative prognostic factor in these patients, despite the generally excellent prognosis of NMSC. It is reasonable to assume that this unfavourable effect is largely due to the increased risk of developing other life-threatening conditions, in which smoking plays a causal role. These results underscore the clinical relevance of systematically integrating smoking cessation counselling into the routine management of patients with NMSC. Full article

Sustainable landslide risk management is critical for achieving resilient communities and supporting the United Nations Sustainable Development Goals, particularly in vulnerable mountainous regions of developing countries. This study presents experimental evidence supporting dimensionless analysis approaches for characterizing granular flow behavior, contributing to cost-effective landslide hazard assessment frameworks. We designed a 4 m experimental flume to investigate the influence of particle characteristics on flow velocity and runout distance, using two materials with contrasting shapes but similar density (~460 kg/m³) and nominal size (~5 mm): uniform crystal beads (φ = 25.2°) and non-uniform crushed granite particles (φ = 36.9°). High-resolution imaging (30 fps, 2336 × 1752 pixels) captured 30 flow experiments from initiation to deposition. Results demonstrate significant differences in flow behavior: crystal beads achieved 50% longer runout distances and 46% higher maximum velocities (380 cm/s vs. 260 cm/s) compared to granite particles. The Savage number ($N_{sav}$) effectively captured fundamental flow-regime differences, with granite particles exhibiting values seven times lower than crystal beads (3.69 vs. 23.91, p < 0.001), indicating greater frictional energy dissipation relative to collisional energy transfer. The Bagnold number confirmed inertially dominated regimes ($N_{Bag}$ > 10⁶) with negligible viscous effects in both materials. These findings demonstrate that accessible material characterization using standard triaxial testing and dimensionless analysis can significantly improve landslide runout prediction accuracy, supporting evidence-based decision-making for sustainable territorial planning and community protection. This research supports the development of practical risk assessment methodologies implementable in resource-limited settings, promoting sustainable development through improved natural hazard management. Full article

Chronic exposure to structural violence and environmental hazards may disrupt stress regulation, trigger inflammation, and impair iron metabolism in women. Iron deficiency has been associated with depression, but the combined impact of environmental stressors and anemia on maternal mental health remains understudied. We analyzed associations between 28 neighborhood-level environmental stressors, hemoglobin levels, and depressive symptoms (measured by the Patient Health Questionnaire-9) during early pregnancy, using retrospective data from 1964 pregnant patients (2015–2019) at an urban health center in Chicago. Demographic and residential data were linked to environmental indicators from the Chicago Health Atlas. Factor analysis reduced the environmental variables, and multivariable regression models examined associations with PHQ-9 scores at first pregnancy encounter. Participants were predominantly non-Hispanic Black (56%) and Hispanic (27%), with 13% anemic and 16% screening positive for depressive symptoms. Poverty, non-Hispanic Black race, single status, public or no insurance, and unemployment were associated with higher depressive symptoms. Among anemic individuals, neighborhood crime was significantly associated with depressive symptoms, while hemoglobin levels and gestational age were not. These findings highlight how environmental and social inequities contribute to maternal mental health disparities and support the need for integrated, equity-focused prenatal care interventions. Full article

Groundwater quality in the semi-arid region of Oum El Bouaghi, Northeastern Algeria, was assessed for irrigation suitability using hydrogeochemical analyses, water quality indices, and GIS techniques. The study analyzed 23 groundwater samples during dry and wet seasons in 2022–2023, several physicochemical parameters were measured. Results revealed neutral to slightly alkaline pH levels, except for one acidic sample, with salinity (EC: 527–5001 µS·cm⁻¹) exceeding WHO guidelines, particularly during the dry season due to evaporation and anthropogenic activities. Hydrogeochemical facies showed dominance of Na⁺-HCO₃⁻ and Ca²⁺-Cl⁻/SO₄²⁻ water types, indicating rock–water interactions and evaporation control, as confirmed by Gibbs plots. The IWQI classified water into five categories, with severe restrictions (IWQI < 40) in 13% of samples during the dry season, improving slightly in the wet season. Indices such as SAR, Na%, and RSC indicated low to moderate sodium hazard, while KR and PS highlighted salinity risks in specific areas. Spatial analysis revealed localized pollution hotspots, with the (GPI) identifying minimal to high contamination levels, linked to agricultural and geogenic sources. These findings underscore needs for sustainable groundwater management, including monitoring, optimized irrigation practices, and mitigation of anthropogenic impacts, to ensure long-term agricultural viability in this water-scarce region. 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

Liposarcomas represent a heterogeneous group of malignant mesenchymal neoplasms, with diverse histological subtypes and molecular alterations. This study aimed to investigate the gene expression profiles of SOX9, GATA3, and GATA4 in liposarcoma subtypes and to assess their associations with clinicopathological parameters. Forty-two formalin-fixed, paraffin-embedded liposarcoma samples were analyzed. Total RNA was extracted, reverse-transcribed, and quantified by qRT-PCR using GAPDH as an endogenous control. Relative quantification (RQ) values were categorized, and statistical analyses included Fisher’s exact test, Kaplan–Meier survival analysis, and Cox proportional hazards modeling. SOX9 expression significantly varied among histological subtypes (p = 0.017), with ALT/WDLS cases showing a predominance of high-level expression (RQ > 50 in 12/15 cases), in contrast to myxoid subtypes clustering mainly in the 10–50 RQ range. GATA4 overexpression correlated with smaller tumor size (<100 mm) (p = 0.049), being more frequent in 15/20 small tumors compared to 10/22 larger ones. GATA3 and GATA4 demonstrated the strongest inter-gene correlation (r = 0.68, p < 0.05), suggesting possible functional interplay. Kaplan–Meier analysis revealed no statistically significant survival differences for individual gene expression, but a high combined GATA3–GATA4 signature was associated with a favorable trend. These findings indicate that SOX9, GATA3, and GATA4 are broadly upregulated in liposarcomas, with subtype- and size-dependent expression patterns. The strong association between GATA3 and GATA4 expression supports their potential synergistic role in tumor biology. Integration of these molecular markers into diagnostic and prognostic workflows may enhance subtype characterization and inform targeted therapeutic strategies. Further studies in larger cohorts are warranted to validate these biomarkers and explore their mechanistic interplay in liposarcoma pathogenesis. Full article

In this paper, we propose a reinforcement-learning method in which an agent generates intrinsic rewards by evaluating its environment based on sensor data. The evaluation is perormed from three perspectives, one of which concerns the predictability of sensor inputs. This perspective focuses on the magnitude of the prediction error: a large error suggests environment uncertainty and leads to a low evaluation. However, prediction errors can arise from two distinct causes that previous method fail to distinguish. The first is the intrinsic unpredictability of a situation, where high prediction error persists even after sufficient learning. Such states are likely to be dangerous and should be assigned low evaluations to discourage the agent from entering them. The second is insufficient learning of the predictor itself, where high prediction error simply reflects the need for further exploration. These states should be assigned high evaluations to encourage learning. To address these cases this study introduced a method that evaluates environmental states by jointly considering the degree of danger and the necessity of further predictor learning with the learning progress for each sensor input. Two complimentary evaluation indices were proposed curiosity, which promotes exploration of insufficiently learned states, and fear, which discourages entry into unpredictable or hazardous states. The effectiveness of the proposed method was demonstrated through simulation experiments in a two-dimensional discrete environment. Full article

Antibiotic resistance genes (ARGs) have emerged as globally concerning environmental contaminants, posing serious threats to ecosystem health and public safety. This systematic review summarizes global research trends on ARGs across three key aspects: (i) identification and distribution in river and lake ecosystems, (ii) sources and environmental behaviors, and (iii) ecological and human health risks. Concentration data of ARGs in various rivers and lakes across China were compiled to reveal their spatial distribution patterns. The analysis of ARGs sources and environmental behaviors provides essential insights for designing effective mitigation strategies. Furthermore, this review highlights the potential ecological and human health hazards of ARGs and discusses limitations and improvement directions of current risk assessment methodologies. The main findings indicate that ARGs are widely present in rivers and lakes across China; higher abundances occur in eastern and southern regions compared with central–western and northern areas, such as 4.93 × 10²–8.10 × 10³ copies/mL in Qinghai Lake and 6.7 × 10⁷–1.76 × 10⁸ copies/mL in Taihu Lake. The environmental behaviors of ARGs are highly complex, involving multiple mechanisms and influenced by climatic conditions, nutrient levels, and additional environmental factors. Based on these findings, future efforts should prioritize long-term site-specific monitoring, evaluate their prolonged impacts on aquatic ecosystems, and develop integrated risk assessment models to support evidence-based environmental management. Full article

Drought is a major climatic hazard affecting water resources, agriculture, and livelihoods in semi-arid regions, with increasing severity under climate change. This study assessed long-term drought in Dura City, Palestine, from 2000 to 2023 using the Standardized Precipitation Index (SPI) at 3-, 6-, and 12-month timescales. Monthly precipitation and temperature data were obtained from local meteorological stations, with mean annual precipitation of 408 mm and average summer and winter temperatures of 28 °C and 12 °C, respectively. Trends were analyzed using the Mann–Kendall test and Sen’s slope estimator. SPI-3 values ranged from −3.13 to 3.87, including 67 moderates to severe drought months and 12 extreme wet months. SPI-6 ranged from −2.97 to 2.53, showing 34 drought months and 40 wet months, while SPI-12 ranged from −1.94 to 2.32, reflecting generally stable long-term precipitation. Annual rainfall exhibited no significant trend (Sen’s slope = −1.34 mm/year, p = 0.785), whereas yearly average temperature increased significantly by 0.054 °C/year (p = 0.02), raising evapotranspiration and drought risk. Results indicate high short- and medium-term drought variability despite stable annual precipitation, underscoring the need for integrated water management strategies, including rainwater harvesting, groundwater protection, and efficient irrigation, to improve resilience under evolving climate conditions. Full article

Spent automotive catalysts (SAC) not only contain significant amounts of platinum group metals (PGMs) but also hazardous heavy metals, rendering them a solid waste. A harmless technology for the efficient recovery of PGMs through copper smelting has been proposed. By investigating the effects of the CaO/SiO₂ mass ratio and Al₂O₃ content on the properties of the slag, the composition of the slag was adjusted. The influence of copper dosage, Na₂B₄O₇ dosage, smelting temperature, and smelting time on the recovery efficiency of PGMs was also discussed. The determined composition of the target slag was 36.44 wt% CaO, 45.56 wt% SiO₂, 12.00 wt% Al₂O₃, and 6.00 wt% MgO. The optimal processing conditions included 12 wt% Cu, 4 wt% Na₂B₄O₇, smelting temperature 1450 °C, and smelting time 90 min. Ultimately, the recovery efficiency of PGMs reached 99.5%. Compared to traditional plasma furnace smelting methods, PGMs were efficiently recovered at a lower melting temperature. A pilot-scale experiment with a mass of 30 kg also achieved a recovery rate of over 99% for PGMs. TCLP results indicate that the heavy metals were immobilized within the glass slag. Full article

Owing to their high vertical resolution, remote sensing data from meteorological satellite hyperspectral infrared sounders are well-suited for the identification, monitoring, and early warning of high-impact weather events. The effective utilization of full field-of-view (FOV) observations from satellite infrared sounders in high-impact weather applications remains a major research focus and technical challenge worldwide. This study proposes a generalized variational retrieval framework to estimate full FOV cloud fraction and precipitable water vapor (PWV) from observations of the Geostationary Interferometric Infrared Sounder (GIIRS) onboard the Fengyun-4A (FY-4A) satellite. Based on this method, experiments are performed using high-frequency FY-4A/GIIRS observations during the landfall periods of Typhoon Lekima (2019) and Typhoon Higos (2020). A three-step channel selection strategy based on information entropy is first designed for FY-4A/GIIRS. A constrained generalized variational retrieval method coupled with a cloud cost function is then established. Cloud parameters, including effective cloud fraction and cloud-top pressure, are initially retrieved using the Minimum Residual Method (MRM) and used as initial cloud information. These parameters are iteratively optimized through cost-function minimization, yielding full FOV cloud fields and atmospheric profiles. Full FOV brightness temperature simulations are conducted over cloudy regions to quantitatively evaluate the retrieved cloud fractions, and the derived PWV is further applied to the identification and analysis of hazardous weather events. Experimental results demonstrate that incorporating cloud parameters as auxiliary inputs to the radiative transfer model improves the simulation of FY-4A/GIIRS brightness temperature in cloud-covered areas and reduces brightness temperature biases. Compared with ERA5 Total Column Water Vapour (TCWV) data, the PWV derived from full FOV profiles containing cloud parameter information shows closer agreement and, at certain FOVs, more effectively indicates the occurrence of high-impact weather events. The simplified methodology proposed in this study provides a robust basis for the future assimilation and operational utilization of infrared data over cloud-affected regions in numerical weather prediction models. Full article

Approximately 27.6% of Italian beaches are currently affected by erosion, despite the widespread implementation of coastal defence structures. Around 10,500 installations—mainly groins and detached breakwaters—occupy nearly 24.6% of the national shoreline. Although primarily designed to protect tourist beaches, these hard-engineered structures often degrade coastal landscapes, alter nearshore circulation, and pose risks to swimmers. Nevertheless, beaches remain a fundamental asset for the “3S” (Sun, Sea, Sand) tourism sector, which contributes approximately 2.2% to Italy’s GDP, accounting for over 175 million tourists’ overnight stays in 2024, frequently concentrated near protected coastal zones. In this study, drowning incidents along the Italian coastline were analyzed using press reports complemented by official statistics. Between 2016 and 2021, an average of 145 fatalities occurred per bathing season. Sudden drownings following medical emergencies accounted for 41% of cases, non-swimmers for 18%, accidental falls into the water for 3%, and water sports activities for an additional 3%. Rip currents on natural beaches were responsible for 22% of drownings, whereas those generated by coastal defence structures accounted for 12%. A further 12% of non-swimmer fatalities are suspected to have resulted from falls into depressions or channels formed in proximity to these structures. Evidence from previous studies and seabed morphology analyses indicates that coastal defence structures can generate rip currents through two main mechanisms: (1) hydraulic pressure exerted against groins, which drives offshore flow, and (2) water outflow between pairs of breakwaters resulting from wave setup behind them. Both processes, though often less intense, are also observed near submerged structures. The erosional channels formed by these currents may persist well beyond storm events, maintaining dangerous conditions for bathers. As Italy continues to rely predominantly on hard coastal protection measures, improving the understanding of drowning dynamics associated with these structures is crucial. This should be accompanied by regulatory updates requiring designers and coastal managers to systematically assess related hazards and to propose effective mitigation and safety strategies. Full article

This paper presents a comprehensive machine learning (ML) framework for predicting liquefaction risk, a crucial aspect of seismic hazard assessment. A benchmark geotechnical dataset with multi-dimensional input features was used to evaluate several ML classifiers, followed by hyperparameter optimization through stratified 5-fold cross-validation. Optimized models were combined into a soft Voting Ensemble to enhance stability and accuracy of liquefaction potential prediction. The proposed ensemble model achieved a mean accuracy of 90.12% and a recall of 97.23%, outperforming individual models in most folds. The ensemble’s effectiveness was further evidenced by its precision-recall (PR) and receiver operating characteristic (ROC) curves, with areas under the curve (AUC) of 0.962 and 0.931, respectively—closely matching those of the Gradient Boosting classifier, indicating comparable discriminatory performance. Additionally, SHapley Additive exPlanations (SHAP) analysis was conducted on the ensemble model to assess contributions of each geotechnical inputs to the predictions, revealing that normalized shear wave velocity ($V_{S1}$) as the most influential variable in liquefaction prediction. The proposed framework demonstrates a robust, interpretable, and performance-consistent approach for liquefaction risk assessment. Full article

Rapid industrialization in peri-urban centers has accelerated the accumulation of potentially toxic elements (PTEs) in agricultural soils, with implications for food safety and public health concerns. This study quantified PTEs (Cu, Cd, Cr, Pb, and Zn) in soils and yam (Colocasia esculenta) tubers from Kampala’s Luzira Industrial Area. Soil contamination levels were evaluated using the geoaccumulation index (I_geo), contamination factor (CF), and pollution load index (PLI), while soil-to-crop transfer of the PTEs was assessed using the biological accumulation factor (BAF). Statistical analyses (One Way Analysis of Variance, Pearson bivariate correlation, and Principal Component Analysis) were applied to identify relationships among PTEs and sampling sites. Soils exhibited marked industrial influence, with PTE concentrations in the order Zn > Pb > Cu > Cr > Cd. The PLI values above unity confirmed cumulative pollution, with hotspots dominated by Zn, Pb, and Cu. Yam tubers contained lower PTE concentrations but reflected a similar contamination pattern as in the soils. The BAF values were <1 for all the PTEs except Zn, pointing to its greater solubility and mobility in the area’s acidic soils. Health risk assessment indicated that yam consumption was the dominant exposure pathway, with hazard indices (HI) for children exceeding the safe threshold at all industrial sites (HI = 1.14–2.06), and total cancer risks (TCR) ranging from 1.27 × 10⁻⁴ to 5.83 × 10⁻⁴, well above the US EPA limit. For adults, the TCR also surpassed 1 × 10⁻⁴ at sampling points SP3 and SP4. These results found potential transfer of the PTEs from soils into yam tubers, with Cd and Cr being the key drivers of dietary risk. Full article

The global spread of glyphosate (GLY) via agricultural runoff poses a significant threat to ecosystems, human health, and the environment, underscoring the need for sustainable agricultural practices. A comprehensive study on glyphosate contamination in runoff water, flowing surface waters, groundwater-influenced, and stagnant water samples was conducted from 2019 to 2021, across a diverse range of landscape types and environmental zones. This research constitutes a novel contribution to the field, focused on several distinct regions, including agricultural regions, tourist zones, and ecologically sensitive areas, including the Beka Natura Reserve, Natura 2000 sites and the Coastal Landscape Park in Poland. Glyphosate residues, with a maximum concentration range of 43.0–8406 ng/L, were detected in 63.5% of water samples collected from protected and unprotected areas. Glyphosate concentrations in water at high-tourism areas were highest in runoff samples from recreational and protected areas, including the Czarna Wda River in Ostrowo (512 ± 9.91 ng/L). Investigated water samples showed target hazard quotient values for glyphosate < 1, indicating no human health risk, and risk quotient values for GLY < 0.1, indicating a low ecotoxicological risk. The presented study is aligned with the United Nations’ 2030 Agenda for Sustainable Development, aiming to contribute to global sustainability goals. Full article