Predictive modelling of peroxisome proliferator-activated receptor gamma (PPARγ) IC50 inhibition by emerging pollutants using light gradient boosting machine

SAR and QSAR in environmental research, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 23

Published: March 24, 2025

Peroxisome proliferator-activated receptor gamma (PPARγ), a critical nuclear receptor, plays pivotal role in regulating metabolic and inflammatory processes. However, various environmental contaminants can disrupt PPARγ function, leading to adverse health effects. This study introduces novel approach predict the inhibitory activity (IC50 values) of 140 chemical compounds across 13 categories, including pesticides, organochlorines, dioxins, detergents, flame retardants, preservatives, on PPARγ. The predictive model, based light-gradient boosting machine (LightGBM) algorithm, was trained dataset 1804 molecules showed r2 values 0.82 0.59, Mean Absolute Error (MAE) 0.38 0.58, Root Square (RMSE) 0.54 0.76 for training test sets, respectively. provides insights into interactions between emerging PPARγ, highlighting potential hazards risks these chemicals may pose public environment. ability inhibition by hazardous demonstrates value this guiding enhanced toxicology research risk assessment.

Language: Английский

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A review of machine learning and internet-of-things on the water quality assessment: methods, applications and future trends

Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 105182 - 105182

Published: May 1, 2025

Language: Английский

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A novel predictive framework for water quality assessment based on socio-economic indicators and water leaving reflectance

Groundwater for Sustainable Development, Journal Year: 2025, Volume and Issue: unknown, P. 101405 - 101405

Published: Jan. 1, 2025

Language: Английский

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Predictive Models for Optimal Irrigation Scheduling and Water Management: A Review of AI and ML Approaches

International Journal of Management Technology and Social Sciences, Journal Year: 2024, Volume and Issue: unknown, P. 94 - 110

Published: May 20, 2024

Purpose: Maintaining agricultural output, protecting water supplies, and lessening environmental effects all depend on effective management. Through a comprehensive review of the literature an in-depth analysis various AI ML techniques, this paper aims to put light cutting-edge approaches used in irrigation scheduling predictive modeling. The goal research is determine advantages, disadvantages, future directions ML-based management systems by means methodical algorithms, data sources, applications. Additionally, study seeks demonstrate how data-driven methods can enhance systems' sustainability, accuracy, precision. Stakeholders agriculture, resource management, conservation make well-informed decisions maximize techniques having thorough understanding theoretical underpinnings practical applications models. also attempts tackle issues like scalability, model interpretability, lack when implementing solutions for In final form, review's conclusions advance our use improve resilience efficiency, supporting adaptive sustainable strategies face rising scarcity concerns climate change. Design/Methodology/Approach: order gather information study, several articles from reliable sources were analyzed compared. Objective: To provide current gaps prediction models best suggest using fill these gaps. Results/ Findings: response growing challenges change, paper's findings highlight transformative potential optimizing scheduling, enhancing resilience, increasing strategies. Originality/Value: This uniqueness significance come its modeling ideal scheduling. It provides insights into new their possible optimization sustainability. Type Paper: Literature Review.

Language: Английский

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Statistical analysis of earth observing data for physicochemical water quality parameters estimation for Lake Beseka, Northern main Ethiopian rift, Ethiopia

Geology Ecology and Landscapes, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 21

Published: May 27, 2024

Water quality deterioration in the Main Ethiopian Rift Lakes is one of problems affecting health and socioeconomic development area. This study was aimed to develop a method assess water change Lake Beseka using satellite image reflectance data observed data. Multi-temporal Landsat imagery three variables were used physicochemical environment: pH, EC, TDS. Linear regression correlation accomplished between parameters surface different band operations. The best-fitted linear equation for pH found on SWIR1 while EC TDS, blue/green ratio highly fitted. Pearson coefficients TDS − 0.79, 0.86, 0.85, respectively. RMSE p-value validation analysis 0.25/0.005, 548/0.003, 367/0.004 estimated higher central portion lake grouped under brackish lower southwestern, southern, northeastern shores. years 2018 2021 relatively than 2007 2023. spatiotemporal variations due anthropogenic geogenic factors including hot springs groundwater discharge lake, water-level rise depth variation, evaporation. These findings are helpful understanding equations that developed from data, which essential estimating monitoring cost-effective time-saving manner.

Language: Английский

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Modeling the vulnerability of water resources to pollution in a typical mining area, SE Nigeria using speciation, geospatial, and multi-path human health risk modeling approaches

Modeling Earth Systems and Environment, Journal Year: 2024, Volume and Issue: 10(5), P. 5923 - 5952

Published: Aug. 23, 2024

Language: Английский

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Performance of artificial intelligence model (LSTM model) for estimating and predicting water quality index for irrigation purposes in order to improve agricultural production

Environmental Monitoring and Assessment, Journal Year: 2024, Volume and Issue: 196(11)

Published: Oct. 13, 2024

Language: Английский

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Exploring the Recent Trends, Progresses, and Challenges in the Application of Artificial Intelligence in Water Quality Assessment and Monitoring in Nigeria: A Systematic Review

Environmental science and engineering, Journal Year: 2024, Volume and Issue: unknown, P. 339 - 366

Published: Jan. 1, 2024

Language: Английский

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Human health risk assessment of drinking water using heavy metal pollution index: a GIS-based investigation in mega city

Applied Water Science, Journal Year: 2024, Volume and Issue: 15(1)

Published: Dec. 28, 2024

Contaminated drinking water poses a significant threat to public health, particularly in urban areas where industrial and environmental pollutants may affect quality. However, there is lack of comprehensive studies that evaluate the specific health risks associated with harmful metal contaminants water. This study seeks address this gap by assessing quality contamination using pollution indices human risk assessments. The findings will help identify potential for residents guide development targeted interventions improved management strategies. groundwater samples were collected from five different zones Kasur rural area. A total 25 random sampling hand pumps during 4 months (March–June, 2021) determining various physiochemical attributes (pH, electric conductivity, turbidity, hardness, chloride, phosphate) potentially toxic elements (arsenic, cadmium, lead) standard protocols. Results revealed almost all physicochemical close World Health Organization (WHO) guidelines. assessment pH levels ranged 7.4 9.0, electrical conductivity (EC) between 150 µS/cm 800 µS/cm, average turbidity 12 ± 3.29 NTU, hardness varied 200 1000 mg/L. Chloride phosphate concentrations averaged 304 1.28 mg/L 4.51 1.99 mg/L, respectively. Cadmium 0.15 0.53 while lead arsenic reached up 7.47 exceeding WHO Heavy index (HPI) values sites less than critical value 100. considering HPI classes, locations had high (> 30) class indicating critically polluted heavy metals. Through exposure water, metals impact on non-carcinogenic (HI > 1), according hazard determined analysis children, infants, adults. As compared carcinogenic values, posed adults children infants as mean CR adults, 1.48E + 00, 1.40E 7.60E-01, It suggested supplies, need installation treatment plants minimize issues.

Language: Английский

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Pollution Source Identification and Suitability Assessment of Groundwater Quality for Drinking Purposes in Semi-Arid Regions of the Southern Part of India

Water, Journal Year: 2023, Volume and Issue: 15(22), P. 3995 - 3995

Published: Nov. 17, 2023

The quality of groundwater plays an important role in human health, and it majorly influences the agricultural process southern part India. present study mainly focused on evaluating used for domestic purpose semi-arid regions samples were collected 36 locations, covering entire investigation zone. analyzed various physical chemical characteristics compared with world health organization standards. entropy-weighted water index (EWQI) revealed that 16.67% required primary-level treatment before they could be drinking purposes. About 72.23% good-to-medium category purposes, as was identified through weighted overlay analysis. ionic relationship plot to identify source contamination carbonate weathering anthropogenic activities are primary sources contamination. results show contaminated zones offer more helpful solutions strengthen management policy region.

Language: Английский

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