Advancing chronic toxicity risk assessment in freshwater ecology by molecular characterization-based machine learning.

The continuously increased production of various chemicals and their release into environments have raised potential negative effects on ecological health. However, traditional labor-intensive assessment methods cannot effectively and rapidly evaluate these hazards, especially for chronic risk. In this study, machine learning (ML) was employed to construct quantitative structure-activity relationship (QSAR) models, enabling the prediction of chronic toxicity to aquatic organisms by leveraging the molecular characteristics of pollutants, namely, the molecular descriptors, fingerprints, and graphs. The limited dataset size hindered the notable advantages of the graph attention network (GAT) model for the molecular graphs. Considering computational efficiency and performance (R2 = 0.78; RMSE = 0.77), XGBoost (XGB) was used for reliable QSAR-ML models predicting chronic toxicity using small- or medium-sized tabular data and the molecular descriptors. Further kernel density estimation analysis confirmed the high accuracy of the model for pollutant concentrations ranging from 10-3 to 102 mg/L, effectively aligning with most environmental scenarios. Model interpretation showed SlogP and exposure duration as the primary influential factors. SlogP, representing the distribution coefficient of a molecule between lipophilic and hydrophilic environments, had a negative effect on the toxicity outcomes. Additionally, the exposure duration played a crucial role in determining the chronic toxicity. Finally, the chronic toxicity data of bisphenol A validated the robustness and reliability of the model established in this research. Our study provided a robust and feasible methodology for chronic ecological risk evaluation of various types of pollutants and could facilitate and increase the use of ML applications in environmental fields.

Buffering effect of the economizer against PCDD/Fs in flue gas from solid waste incineration plants.

The emission of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) from solid waste incineration is always a crucial concern for the society. Less attention has been paid to differentiate its formation and migration in the low temperature range of economizer, leading to a fuzzy understanding on the control of PCDD/Fs before flue gas cleaning. This study first reveals the buffering effect against PCDD/Fs in the economizer, which is contrary to the well-known memory effect, and first recognizes the intrinsic mechanism by 36 sets of full-scale experimental data under three typical operating conditions. Results indicated that the buffering effect, which includes interception and releasing, could remove averagely 82.9 % of PCDD/Fs in flue gas and reconcile PCDD/Fs profiles. The interception effect is dominant and in compliance with the condensation law. The low temperature range of economizer is exactly suitable for the condensation of lowly chlorinated congeners, which condense behind highly chlorinated ones. The releasing effect was non-staple but stimulated by the sudden change of operating condition, proving that PCDD/Fs formation rarely exists in the economizer. The buffering effect is mainly controlled by the physical migration of PCDD/Fs among different phases. The condensation of PCDD/Fs leads to their migration from vapor phase to aerosol and solid phases during flue gas cooling in the economizer. There is no need for excessive anxiety about PCDD/Fs formation in the economizer because it rarely exists. Intensifying the condensation process of PCDD/Fs in the economizer can help relieve the pressure of end-of-pipe measures for PCDD/Fs control.

Free-breathing dynamic contrast-enhanced MRI for assessment of pulmonary lesions using golden-angle radial sparse parallel imaging.

BACKGROUND: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) has been shown to be a promising technique for assessing lung lesions. However, DCE-MRI often suffers from motion artifacts and insufficient imaging speed. Therefore, highly accelerated free-breathing DCE-MRI is of clinical interest for lung exams. PURPOSE: To test the performance of rapid free-breathing DCE-MRI for simultaneous qualitative and quantitative assessment of pulmonary lesions using Golden-angle RAdial Sparse Parallel (GRASP) imaging. STUDY TYPE: Prospective. POPULATION: Twenty-six patients (17 males, mean age = 55.1 ± 14.4) with known pulmonary lesions. FIELD STRENGTH/SEQUENCE: 3T MR scanner; a prototype fat-saturated, T1 -weighted stack-of-stars golden-angle radial sequence for data acquisition and a Cartesian breath-hold volumetric-interpolated examination (BH-VIBE) sequence for comparison. ASSESSMENT: After a dual-mode GRASP reconstruction, one with 3-second temporal resolution (3s-GRASP) and the other with 15-second temporal resolution (15s-GRASP), all GRASP and BH-VIBE images were pooled together for blind assessment by two experienced radiologists, who independently scored the overall image quality, lesion delineation, overall artifact level, and diagnostic confidence of each case. Perfusion analysis was performed for the 3s-GRASP images using a Tofts model to generate the volume transfer coefficient (Ktrans ) and interstitial volume (Ve ). STATISTICAL TESTS: Nonparametric paired two-tailed Wilcoxon signed-rank test; Cohen's kappa; unpaired Student's t-test. RESULTS: 15s-GRASP achieved comparable image quality with conventional BH-VIBE (P > 0.05), except for the higher overall artifact level in the precontrast phase (P = 0.018). The Ktrans and Ve in inflammation were higher than those in malignant lesions (Ktrans : 0.78 ± 0.52 min-1 vs. 0.37 ± 0.22 min-1 , P = 0.020; Ve : 0.36 ± 0.16 vs. 0.26 ± 0.1, P = 0.177). Also, the Ktrans and Ve in malignant lesions were also higher than those in benign lesions (Ktrans : 0.37 ± 0.22 min-1 vs. 0.04 ± 0.04 min-1 , P = 0.001; Ve : 0.26 ± 0.12 vs. 0.10 ± 0.00, P = 0.063). DATA CONCLUSION: This feasibility study demonstrated the performance of high spatiotemporal resolution free-breathing DCE-MRI of the lung using GRASP for qualitative and quantitative assessment of pulmonary lesions. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2018;48:459-468.

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With a special focus on Jiangkou County in Guizhou Province, this paper explored the ecological compensation standards and compensation methods of local key public welfare forest protected area by using questionnaire and contingent valuation method. The results showed that the minimum compensation which the local foresters could accept was 314.14-365.15 yuan·hm-2 per year, and the opportunity cost was 9750 yuan multiplied by the protected forest area. The willingness to accept of foresters was affected by many factors, such as health status, education level, ethnicity and local township. The compensation methods local foresters expected were various, but mainly were cash and technology compensation. Finally, this paper put forward some policy suggestions on improving system, increasing compensation standards, strengthening propaganda, and enriching compensation methods.