Search Results (1,367)

Monitoring water quality is crucial for achieving clean water and sanitation goals, particularly in remote areas. The project “Morbidity vs. Water Quality for Human Consumption in Tonosí: A Pilot Study” aimed to enhance water quality assessments in Panama using advanced analytical techniques to assess volatile organic compounds, heavy metals, and microbiological pathogens. To support this, the Technical Unit for Water Quality (UTECH) was established, featuring a novel mobile laboratory with cutting-edge technology for accurate testing, minimal chemical reagent use, reduced waste generation, and equipped with a solar-powered battery system. The aim of this paper is to explore the design, deployment, and impact of the UTECH. Furthermore, this study presents results from three sampling points in Tonosí, where several parameters exceeded regulatory limits, demonstrating the capabilities of the UTECH and highlighting the need for ongoing monitoring and intervention. The study also assesses the environmental, social, and economic impacts of the UTECH in alignment with the Sustainable Development Goals and national initiatives. Finally, a SWOT analysis illustrates the UTECH’s potential to improve water quality assessments in Panama while identifying areas for sustainable growth. The study showcases the successful integration of advanced mobile laboratory technologies into water quality monitoring, contributing to sustainable development in Panama and offering a replicable model for similar initiatives in other regions. Full article

Emerging and persistent contaminants (EPCs) were detected at high concentrations in Chiang Mai’s Mae Kha Canal, identifying urban waterways as important sources of pollution in the Ping River system in northern Thailand. Maximum levels of metformin (20,000 ng/L), fexofenadine (15,900 ng/L), gabapentin (12,300 ng/L), sucralose (38,000 ng/L), and acesulfame (23,000 ng/L) point to inadequately treated wastewater as a plausible contributor. Downstream enrichment patterns relative to upstream sites highlight the cumulative impact of urban runoff. Five compounds—acesulfame, gemfibrozil, fexofenadine, TBEP, and caffeine—consistently emerged as reliable tracers of urban wastewater, forming a distinct chemical fingerprint of the riverine exposome. Median EPC concentrations were highest in Mae Kha, lower in other urban canals, and declined with distance from the city, reflecting spatial gradients in urban density and pollution intensity. Although most detected concentrations fell below predicted no-effect thresholds, ibuprofen frequently approached or exceeded ecotoxicological benchmarks and may represent a compound of ecological concern. Non-targeted analysis revealed a broader “chemical cocktail” of unregulated substances—illustrating a witches’ brew of pollution that likely escapes standard monitoring efforts. These findings demonstrate the utility of wide-scope surveillance for identifying key compounds, contamination hotspots, and spatial gradients in mixed-use watersheds. They also highlight the need for integrated, long-term monitoring strategies that address diffuse, compound mixtures to safeguard freshwater ecosystems in rapidly urbanizing regions. Full article

Precise odor source localization in turbulent and sparse environments plays a vital role in enabling robotic systems for hazardous chemical monitoring and effective disaster response. To address this, we propose Cooperative Gravitational-Rényi Infotaxis (CGRInfotaxis), a distributed decision-optimization framework that combines multi-agent collaboration with hybrid cognitive strategy to improve search efficiency and robustness. The method integrates a gravitational potential field for rapid source convergence and Rényi divergence-based probabilistic exploration to handle sparse detections, dynamically balanced via a regulation factor. Particle filtering optimizes posterior probability estimation to autonomously refine search areas while preserving computational efficiency, alongside a distributed interactive-optimization mechanism for real-time decision updates through agent cooperation. The algorithm’s performance is evaluated in scenarios with fixed and randomized odor source locations, as well as with varying numbers of agents. Results demonstrate that CGRInfotaxis achieves a near-100% success rate with high consistency across diverse conditions, outperforming existing methods in stability and adaptability. Increasing the number of agents further enhances search efficiency without compromising reliability. These findings suggest that CGRInfotaxis significantly advances multi-agent odor source localization in turbulent, sparse environments, offering practical utility for real-world applications. Full article

Growing interest in the future applications of nanotechnology in medicine has led to groundbreaking developments in nanosensors. Nanosensors are excellent platforms that provide reliable solutions for continuous monitoring and real-time detection of clinical targets. Nanosensors have attracted great attention due to their remarkable sensitivity, portability, selectivity, and automated data acquisition. The exceptional nanoscale properties of nanomaterials used in the nanosensors boost their sensing potential even at minimal concentrations of analytes present in a clinical sample. Along with applications in diverse sectors, the beneficial aspects of nanosensors have been exploited in healthcare systems to utilize their applications in diagnosing, treating, and preventing diseases. Hence, in this review, we have presented an overview of the disease-prognostic applications of nanosensors in chronic diseases through a detailed literature analysis. We focused on the advances in various nanosensors in the field of major diseases such as cancer, cardiovascular diseases, diabetes mellitus, and neurodegenerative diseases along with other prevalent diseases. This review demonstrates various categories of nanosensors with different nanoparticle compositions and detection methods suitable for specific diagnostic applications in clinical settings. The chemical properties of different nanoparticles provide unique characteristics to each nanosensors for their specific applications. This will aid the detection of potential biomarkers or pathological conditions that correlate with the early detection of various diseases. The potential challenges and possible recommendations of the applications of nanosensors for disease diagnosis are also discussed. The consolidated information present in the review will help to better understand the disease-prognostic potentials of nanosensors, which can be utilized to explore new avenues in improved therapeutic interventions and treatment modalities. Full article

Exposure to per- and polyfluoroalkyl substances (PFASs) can cause detrimental health effects. The consumption of contaminated food is viewed as a major exposure pathway for humans, but the relationship between agriculture and PFASs has not been investigated thoroughly, and it is becoming a pressing issue since health advisories are continuously being reassessed. This semi-systematic literature review connects the release, environmental fate, and agriculture uptake of PFASs to enhance comprehension and identify knowledge gaps which limit accurate risk assessment. It focuses on the heavily agricultural state of Minnesota, USA, which is representative of the large Midwestern US Corn Belt in terms of agricultural activities, because PFASs have been monitored in Minnesota since the beginning of the 21st century. PFAS contamination is a complex issue due to the over 14,000 individual PFAS compounds which have unique chemical properties that interact differently with air, water, soil, and biological systems. Moreover, the lack of field studies and monitoring of agricultural sites makes accurate risk assessments challenging. Researchers, policymakers, and farmers must work closely together to reduce the risk of PFAS exposure as the understanding of their potential health effects increases and legacy PFASs are displaced with shorter fluorinated replacements. Full article

Molecular sensor systems, e.g., implantables and wearables, provide extensive health-related monitoring. Glucose sensor systems have historically prevailed in wearable bioanalysis applications due to their continuous and reliable glucose monitoring, a feat not yet accomplished for other biomarkers. However, the advancement of reagentless detection methodologies may facilitate the creation of molecular sensor systems for multiple analytes. Improving the sensitivity and selectivity of molecular sensor systems is also crucial for biomarker detection under intricate physiological circumstances. The term multidomain molecular sensor systems is utilized to refer, in general, to both biological and chemical sensor systems. This review examines methodologies for enhancing signal amplification, improving selectivity, and facilitating reagentless detection in multidomain molecular sensor devices. The review also analyzes the fundamental components of multidomain molecular sensor systems, including substrate materials, bodily fluids, power, and decision-making units. The review article further investigates how extensive data gathered from multidomain molecular sensor systems, in conjunction with current data processing algorithms, facilitate biomarker detection for precision medicine. Full article

Drosophila suzukii is an invasive pest of many fruit crops worldwide. Employing the Sterile Insect Technique (SIT) could mitigate D. suzukii population growth and crop damage. This study evaluated the efficacy of SIT on commercial fruit, by (1) validating the quality of irradiated sterile males (male mating competitiveness, courtship, and flight performance) in the laboratory, and (2) assessing population suppression and fruit damage reduction in commercial raspberry fields. Treatment with SIT was compared to the grower’s standard chemical insecticide program throughout the season. The principal metrics of efficacy were trap counts of wild adult female D. suzukii in crops and larvae per fruit during harvesting. These metrics together with monitoring of border areas allowed targeting of high-pressure areas with higher releases of sterile males, to maximise efficacy for a given release number. The sterile male D. suzukii were as competitive as their fertile non-irradiated counterparts in laboratory mating competitiveness and flight performance studies while fertility egg-to-pupae recovery was reduced by 99%. In commercial raspberry crops, season-long releases of sterile males significantly suppressed the wild D. suzukii population, compared to the grower standard control strategy; with up to 89% reduction in wild female D. suzukii and 80% decrease in numbers of larvae per harvested fruit. Additionally, relative fruit waste (i.e., percentage of harvested fruits rejected for sale) at harvest was reduced for early, mid and late harvest crops, by up to 58% compared to the grower standard control. SIT has the potential to provide an effective and sustainable strategy for managing D. suzukii in raspberries, increasing marketable yield by reducing adult populations, fruit damage and waste fruit. SIT could therefore serve as a valuable tool for integrated pest management practices in berry production systems. Full article

Dexamethasone, widely used as an exogenous glucocorticoid in clinical and animal practice, has recently been recognized as an environmental contaminant of concern. Existing evidence documents its ability to induce persistent dyslipidemia in adult offspring. In this study, plasma cholesterol levels in male rats exposed to dexamethasone prenatally (PDE) were increased. Meanwhile, developmental tracking revealed a reduction in hepatic low-density lipoprotein receptor (LDLR) promoter H3K27 acetylation (H3K27ac) and corresponding transcriptional activity across gestational-to-postnatal stages. Mechanistic investigations established glucocorticoid receptor/histone deacetylase2 (GR/HDAC2) axis-mediated epigenetic programming of LDLR through H3K27ac modulation in PDE offspring, potentiating susceptibility to hypercholesterolemia. Additionally, in peripheral blood mononuclear cells (PBMC) of PDE male adult offspring, LDLR H3K27ac level and expression were also decreased and positively correlated with those in the liver. Clinical studies further substantiated that male newborns prenatally treated with dexamethasone exhibited increased serum cholesterol levels and consistent reductions in LDLR H3K27ac levels and corresponding transcriptional activity in PBMC. This study establishes a complete evidence chain linking PDE with epigenetic programming and cholesterol metabolic dysfunction, proposing PBMC epigenetic biomarkers as a novel non-invasive monitoring tool for assessing the developmental toxicity of chemical exposures during pregnancy. This has significant implications for improving environmental health risk assessment systems. Full article

Per- and polyfluoroalkyl substances (PFAS) are synthetically produced chemicals that are causing a major One Health crisis. These “forever chemicals” are widely distributed globally in air, water, and soil, and because they are highly mobile and extremely difficult to degrade in the environment. They cause additional health concerns in a circular bioeconomy and food system that recycles and reuses by-products and numerous types of waste materials. Uptake of PFAS by plants and food-producing animals ultimately leads to the consumption of PFAS-contaminated food that is associated with numerous adverse health and developmental effects in humans. Contaminated meat, milk, and eggs are some of the main sources of human PFAS exposure. Although there is no safe level of PFAS exposure, maximum tolerable PFAS consumption guidelines have been established for some countries. However, there is no international PFAS monitoring system, and there are no standardized international guidelines and mechanisms to prevent the consumption of PFAS-contaminated foods. Urgent action is needed to stop PFAS production except for critical uses, implementing effective water-purification treatments, preventing spreading sewage sludge on land and pastures used to produce food, and requiring marketers and manufacturers to use packaging that is free of PFAS. Full article

The prevention and control of mine inrush water has always been a major challenge for safety. By identifying the type of water source and analyzing the real-time changes in water composition, sudden water inrush accidents can be monitored in a timely manner to avoid major accidents. This paper proposes a novel explainable machine learning model for source type identification of mine inrush water. The paper expands the original monitoring system into the XinJi No.2 Mine in Huainan Mining Area. Based on the online water composition data, using the Spearman coefficient formula, it analyzes the water chemical characteristics of different aquifers to extract key discriminant factors. Then, the Conv1D-GRU model was built to deeply connect factors for precise water source identification. The experimental results show an accuracy rate of 85.37%. In addition, focused on the interpretability, the experiment quantified the impact of different features on the model using SHAP (Shapley Additive Explanations). It provides new reference for the source type identification of mine inrush water in mine disaster prevention and control. Full article

Water systems serve as multifaceted environmental pools for antibiotic-resistant bacteria (ARB) and resistance genes (ARGs), influencing human, animal, and ecosystem health. This review synthesizes current understanding of how antibiotics, ARB, and ARGs enter surface, ground, and drinking waters via wastewater discharge, agricultural runoff, hospital effluents, and urban stormwater. We highlight key mechanisms of biofilm formation, horizontal gene transfer, and co-selection by chemical stressors that facilitate persistence and spread. Case studies illustrate widespread detection of clinically meaningful ARB (e.g., Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumoniae) and mobile ARGs (e.g., sul1/2, tet, bla variants) in treated effluents, recycled water, and irrigation return flows. The interplay between treatment inefficiencies and environmental processes underscores the need for advanced treatment technologies, integrated monitoring, and policy interventions. Addressing these challenges is critical to curbing the environmental dissemination of resistance and protecting human and ecosystem health. Full article

Bisphenols (BPs), particularly bisphenol A (BPA) and its structural analogues, are synthetic compounds widely used in plastics and industrial materials. These substances are also recognised as endocrine-disrupting chemicals (EDCs) due to their ability to interfere with hormonal systems, which has significant implications for aquatic organisms. This review summarises the occurrence, environmental distribution, and toxicity of BPs in fish, with a focus on estrogenic, androgenic, thyroid, and glucocorticoid disruptions. Studies consistently show that exposure to BPs leads to altered gene expression, developmental abnormalities, impaired reproduction, and disrupted hormonal signalling in various fish species. Although BPA alternatives like bisphenol S, bisphenol F, or bisphenol AF were introduced as safer options, emerging evidence suggests they may pose equal or greater risks. Regulatory measures are evolving, particularly within the European Union, but legislation remains limited for many bisphenol analogues. This review emphasises the need for comprehensive environmental monitoring, stricter regulatory frameworks, and the development of genuinely safer alternatives to minimise the ecological and health impacts of BPs in aquatic systems. Full article

Background: Peyronie’s disease (PD) is a chronic inflammatory condition that affects the penile albuginea. Oxidative stress (OS) plays a crucial role in the development of the disease, prompting us to investigate OS levels at the site of the disease and in peripheral blood. This article presents our second study in which the OS was evaluated by calculating the OS index (OSI) in blood samples taken directly from the penile corpora cavernosa of patients with PD. Our innovative diagnostic method, which focuses on the analysis of oxidative stress (OS) in the corpora cavernosa of the penis, allows us to accurately identify the “chemical” signals (OS levels) of the pathology in the area where it is present. Methods: Our study included 102 PD patients from our Peyronie’s care center and 100 control cases. To conduct a comprehensive OS analysis, we measured both the total oxidant status (TOS) and total antioxidant status (TAS) and calculated the oxidative stress index (OSI) as OSI = TOS/TAS × 100. Blood samples were collected from the penis and a vein in the upper extremity, and OS was measured using d-ROMs and PATs (FRAS kit). Results: Pearson’s analyses revealed a significant statistical correlation between penile OSI values and PD plaque volumes (p = 0.003), while no correlation was found between systemic OSI values and plaque volumes (p = 0.356). Penile OSI values decreased significantly after PD plaque removal (p < 0.0001). A comparison of penile OSI values in PD patients (post plaque removal) and the control group showed no significant differences (p = 0.418). Conclusions: The lack of correlation between systemic OSI values and Peyronie’s plaque volume suggests that direct sampling from the site of the disease is preferable for OS studies. Conducting a penile OSI study could provide a precise oxidative marker dependent on plaque volume. In addition, the penile OSI study can biochemically monitor the therapeutic result, alongside penile ultrasound imaging. Full article

The treatment processes from a wastewater treatment plant (WWTP) are known for their complexity and highly nonlinear behavior, which makes them challenging to analyze, model, and especially, to control. This research studies how machine learning (ML) with a focus on deep learning (DL) techniques can be applied to optimize the treatment processes of WWTPs, highlighting those case studies that propose ML and DL methods that directly address this issue. This research aims to study the ML and DL systematic applications in optimizing the wastewater treatment processes from an industrial plant, such as the modeling of complex physical–chemical processes, real-time monitoring and prediction of critical wastewater quality indicators, chemical reactants consumption reduction, minimization of plant energy consumption, plant effluent quality prediction, development of data-driven type models as support in the decision-making process, etc. To perform a detailed analysis, 87 articles were included from an initial set of 324, using criteria such as wastewater combined with ML, DL, and artificial intelligence (AI), for articles from 2010 or newer. From the initial set of 324 scientific articles, 300 were identified using Litmaps, obtained from five important scientific databases, all focusing on addressing the specific problem proposed for investigation. Thus, this paper identifies gaps in the current research, discusses ML and DL algorithms in the context of optimizing wastewater treatment processes, and identifies future directions for optimizing these processes through data-driven methods. As opposed to traditional models, IA models (ML, DL, hybrid and ensemble models, digital twin, IoT, etc.) demonstrated significant advantages in wastewater quality indicator prediction and forecasting, in energy consumption forecasting, in temporal pattern recognition, and in optimal interpretability for normative compliance. Integrating advanced ML and DL technologies into the various processes involved in wastewater treatment improves the plant systems’ predictive capabilities and ensures a higher level of compliance with environmental standards. Full article

Luminescent metal–organic frameworks (MOFs) are used for the detection of organophosphorus pesticides (OPs) due to their large surface area and pore volume as well as their special optical properties. However, most self-luminescent MOFs are not only complex to synthesize and unstable in water but also feature a “turn-off” sensing system, which has highly restricted their practical applications in OP detection. Herein, a “turn-on” fluorescence sensor based on the guest-induced luminescence MOF Ru(bpy)₃²⁺@UiO-66 was constructed, which realized the sensitive detection of OPs through a dual-enzyme system for the first time. Compared with self-luminescent MOFs, Ru(bpy)₃²⁺@UiO-66 was not only more easily synthesized but also had higher chemical and photostability in water. In this strategy, by means of the hydrolysis of AChE and ChOx, H₂O₂ will be produced, which can oxidize Fe²⁺ to Fe³⁺, thereby quenching the fluorescence of Ru(bpy)₃²⁺@UiO-66. In the presence of OPs, the activity of AChE can be inhibited, resulting in the inability to generate H₂O₂ and Fe³⁺, which will turn on the fluorescence signal of Ru(bpy)₃²⁺@UiO-66. As a result, the Ru(bpy)₃²⁺@UiO-66 sensing system not only had high sensitivity for OPs detection but also possessed a satisfactory detection recovery rate for parathion-methyl in real samples, which provides a new approach for OP detection in food safety as well as environmental monitoring. Full article