Published: Jan. 1, 2024
Language: Английский
BMC Public Health, Journal Year: 2025, Volume and Issue: 25(1)
Published: March 1, 2025
Metabolic diseases (MDs), exemplified by diabetes, hypertension, and dyslipidemia, have become increasingly prevalent with rising living standards, posing significant public health challenges. The MDs are influenced a complex interplay of genetic factors, lifestyle choices, socioeconomic conditions. Additionally, environmental pollutants, particularly air pollutants (APs), attracted increasing attention for their potential role in exacerbating these MDs. However, the impact APs on remains unclear. This study introduces novel machine learning (ML) pipeline, an Algorithm Spatial Relationships Analysis between Exposome Diseases (ASEMD), to analyze spatial associations at prefecture-level city scale China. ASEMD pipeline comprises three main steps: (i) autocorrelation is evaluated using Moran's I statistic Local Indicators Association (LISA) maps. (ii) dimensionality reduction similarities identification clusters Principal Component (PCA), k-means clustering, Jaccard index calculations, further validated through (iii) AP exposure adjusted demographic confounders predict models (e.g., eXtreme Gradient Boosting (XGBoost), Random Forest (RF), Decision Tree (DT), LightGBM, Multi-Layer Perceptron (MLP)). SHAP values employed identify key that linked Model performance 10-fold cross-validation five different metrics. data utilized include CHARLS (2015) meteorological (2013-2015). Significant correlations were found prevalence higher rates observed alignment elevated concentrations. By adjusting confounders, effectively predicted risk developing (AUROC=0.890, 0.877, 0.710 respectively). results showed $$\mathrm CO$$ , PM_{2.5}$$ AQI$$ strongly correlated whereas NO_{2}$$ PM_{10}$$ significantly associated dyslipidemia. For O_{3}$$ mostly correlated. Sensitivity analyses across regions types underscored robustness our conclusions. successfully integrates ML models, epidemiological methods, analysis techniques, providing robust framework understanding interactions We also identified specific APs, including $$PM_{10}$$ SO_{2}$$ as being hypertension central northern cities. Future region-specific strategies or interventions, especially those areas high pollutant levels, needed mitigate pollution's metabolic health.
Language: Английский
Citations
0
Water, Journal Year: 2025, Volume and Issue: 17(7), P. 936 - 936
Published: March 23, 2025
Groundwater, which constitutes 95% of the world’s freshwater resources, is widely used for drinking and domestic water supply, agricultural irrigation, energy production, bottled commercial use. In recent years, due to pressures from climate change excessive urbanization, a noticeable decline in groundwater levels has been observed, particularly arid semi-arid regions. The corresponding changes have analyzed using diverse range methodologies, including data-driven modeling techniques. Recent evidence shown notable acceleration utilization such advanced techniques, demonstrating significant attention by research community. Therefore, major aim present study conduct bibliometric analysis investigate application evolution machine learning (ML) techniques research. this sense, studies published between 2000 2023 were examined terms scientific productivity, collaboration networks, themes, methods. findings revealed that ML offer high accuracy predictive capacity, especially quality, level estimation, pollution modeling. United States, China, Iran stand out as leading countries emphasizing strategic importance management. However, outcomes demonstrated low international cooperation led deficiencies solving transboundary problems. aimed encourage more widespread effective use management environmental planning processes drew transparent interpretable algorithms, with potential yield rewarding opportunities increasing adoption technologies decision-makers.
Language: Английский
Citations
0
Pathogens, Journal Year: 2025, Volume and Issue: 14(4), P. 386 - 386
Published: April 15, 2025
Staphylococcus aureus is a formidable pathogen notorious for its antibiotic resistance and diverse virulence mechanisms, including toxin production, biofilm formation, immune evasion. This article explores innovative anti-virulence strategies to disarm S. by targeting critical factors without exerting bactericidal pressure. Key approaches include inhibiting adhesion neutralizing toxins, disrupting quorum sensing (e.g., Agr system inhibitors), blocking iron acquisition pathways. Additionally, interventions two-component regulatory systems are highlighted. While promising, challenges such as strain variability, resilience, pharmacokinetic limitations, evolution underscore the need combination therapies advanced formulations. Integrating with traditional antibiotics host-directed offers sustainable solution combat multidrug-resistant aureus, particularly methicillin-resistant strains (MRSA), mitigate global public health crisis.
Language: Английский
Citations
0
Current Opinion in Biotechnology, Journal Year: 2025, Volume and Issue: 93, P. 103304 - 103304
Published: April 17, 2025
Language: Английский
Citations
0
Published: Jan. 1, 2025
Language: Английский
Citations
0
Journal of Hazardous Materials, Journal Year: 2024, Volume and Issue: 478, P. 135474 - 135474
Published: Aug. 9, 2024
Language: Английский
Citations
2
Water Research, Journal Year: 2024, Volume and Issue: 265, P. 122282 - 122282
Published: Aug. 22, 2024
Language: Английский
Citations
1
Published: Jan. 1, 2024
Language: Английский
Citations
0