Construction of an antidepressant priority list based on functional, environmental, and health risks using an interpretable mixup-transformer deep learning model.

As emerging pollutants, antidepressants (AD) must be urgently investigated for risk identification and assessment. This study constructed a comprehensive-effect risk-priority screening system (ADRank) for ADs by characterizing AD functionality, occurrence, persistence, bioaccumulation and toxicity based on the integrated assignment method. A classification model for ADs was constructed using an improved mixup-transformer deep learning method, and its classification accuracy was compared with those of other models. The accuracy of the proposed model improved by up to 23.25 % compared with the random forest model, and the reliability was 80 % more than that of the TOPSIS method. A priority screening candidate list was proposed to screen 33 high-priority ADs. Finally, SHapley Additive explanation (SHAP) visualization, molecular dynamics, and amino acid analysis were performed to analyze the correlation between AD structure and toxic receptor binding characteristics and reveal the differences in AD risk priority. ADs with more intramolecular hydrogen bonds, higher hydrophobicity, and electronegativity had a more significant risk. Van der Waals and electrostatic interactions were the primary influencing factors, and significant differences in the types and proportions of the main amino acids in the interaction between ADs and receptors were observed. The results of the study provide constructive schemes and insights for AD priority screening and risk management.

Kidney toxicity and transcriptome analyses of male ICR mice acutely exposed to the mushroom toxin α-amanitin.

Amatoxins are responsible for most fatal mushroom poisoning cases, as it causes both hepatotoxicity and nephrotoxicity. However, studies on amatoxin nephrotoxicity are limited. Here, we investigated nephrotoxicity over 4 days and nephrotoxicity/hepatotoxicity over 14 days in mice. The organ weight ratio, serological indices, and tissue histology results indicated that a nephrotoxicity mouse model was established with two stages: (1) no apparent effects within 24 h; and (2) the appearance of adverse effects, with gradual worsening within 2-14 days. For each stage, the kidney transcriptome revealed patterns of differential mRNA expression and significant pathway changes, and Western blot analysis verified the expression of key proteins. Amanitin-induced nephrotoxicity was directly related to RNA polymerase II because mRNA levels decreased, RNA polymerase II-related pathways were significantly enriched at the transcription level, and RNA polymerase II protein was degraded in the early poisoning stage. In the late stage, nephrotoxicity was more severe than hepatotoxicity. This is likely associated with inflammation because inflammation-related pathways were significantly enriched and NF-κB activation was increased in the kidney.

Coronary Microvascular Dysfunction and Diffuse Myocardial Fibrosis in Patients With Type 2 Diabetes Using Quantitative Perfusion MRI.

BACKGROUND: Imaging techniques that quantitatively and automatically measure changes in the myocardial microcirculation in patients with diabetes are lacking. PURPOSE: To detect diabetic myocardial microvascular complications using a novel automatic quantitative perfusion MRI technique, and to explore the relationship between myocardial microcirculation dysfunction and fibrosis. STUDY TYPE: Prospective. SUBJECTS: 101 patients with type 2 diabetes mellitus (T2DM) (53 without and 48 with complications), 20 healthy volunteers. FIELD STRENGTH/SEQUENCE: 3.0T; modified Look-Locker inversion-recovery sequence; saturation recovery sequence and dual-bolus technique; segmented fast low-angle shot sequence. ASSESSMENT: All participants underwent MRI to determine the rest myocardial blood flow (MBF), stress MBF, myocardial perfusion reserve (MPR), and extracellular volume (ECV), which represents the extent of myocardial fibrosis. STATISTICAL TESTS: Kolmogorov-Smirnov test, Shapiro-Wilk test, Kruskal-Wallis H test, Mann-Whitney U test, chi-square test, Spearman correlation coefficient, multivariable linear regression analysis. P < 0.05 was considered statistically significant. RESULTS: The rest MBF was not significantly different between the T2DM without complications group (1.1, IQR: 0.9-1.3) and the control group (1.1, 1.0-1.3) (P = 1.000), but it was significantly lower in the T2DM with complications group (0.8, 0.6-1.0) than in both other groups. The stress MBF and MPR were significantly lower in the T2DM without complications group (1.9, 1.5-2.3, and 1.7, 1.4-2.1, respectively) than in the control group (3.0, 2.6-3.5, and 2.7, 2.4-3.1, respectively), and were also significantly lower in the T2DM with complications group (1.1, 0.9-1.4, and 1.4, 1.2-1.8, respectively) than in the T2DM without complications group. A decrease in MBF and MPR were significantly associated with an increase in the ECV. DATA CONCLUSION: Quantitative perfusion MRI can evaluate myocardial microcirculation dysfunction. In T2DM, there was a significant decrease in both MBF and MPR compared to healthy controls, with the decrease being significantly different between T2DM with and without complications groups. The decrease of MBF was significantly associated with the development of myocardial fibrosis, as determined by ECV. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 3.

Control list of high-priority chemicals based on 5-HT-RI functionality and the human health interference effects selective CNN-GRU deep learning model.

The antidepressant drug known as 5-HT reuptake inhibitor (5-HT-RI) was commonly detected in biological tissues and result in significant adverse health effects. Homology modeling was used to characterize the functionalities (efficacy and resistance), and the adverse outcome pathway was used to characterize its human health interferences (olfactory toxicity, neurotoxicity, and gut microbial interference). The convolutional neural network coupled with the gated recurrent unit (CNN-GRU) deep learning method was used to construct a comprehensive model of 5-HT-RI functionality and human health interference effects selectivity with small sample data. The architecture with 2 SE, 320 neuronal nodes and 6-folds cross-validation showed the best applicability. The results showed that the confidence interval of the constructed model reached 90 % indicating that the model had reliable prediction ability and generalization ability. Based on the CNN-GRU deep learning model, seven high-priority chemicals with a weak comprehensive effect, including D-VEN, (1R,4S)-SER, S-FLX, CTP, S-CTP, NEF, and VEN, were screened. Based on the molecular three-dimensional structure information, a comprehensive-effect three-dimensional quantitative structure-activity relationship (3D-QSAR) model was constructed to confirm the reliability of the constructed control list of 5-HT-RI high-priority chemicals. Analysis with the ranking of calculated values based on the molecular dynamics method and predicted values based on the CNN-GRU deep learning model, we found that the consistency of the three methods was above 85 %. Additionally, by analyzing the sensitivity, molecular electrostatic potential, polar surface area of the comprehensive-effect CNN-GRU deep learning model, and the electrostatic field of the 3D-QSAR models, we found that the significant effects of five key characteristics (DM, Qyy, Qxz, I, and BP), molecular electronegativity, and polarity significantly affected the high-priority degree of 5-HT-RI. In this study, we provided reasonable and reliable prediction tools and discussed theoretical methods for the risk assessment of functionality and human health interference of emerging pollutants such as 5-HT-RI.

Reduction strategies of polycyclic aromatic hydrocarbons in farmland soils: Microbial degradation, plant transport inhibition, and their mechanistic analysis.

This study focuses on the abatement of polycyclic aromatic hydrocarbons (PAHs), a global pollutant, in farmland soils. Seven controlled PAHs in China were used as the target ligands, and four key target receptors degradable PAHs and two key target receptors transport PAHs were used as the target receptors. Firstly, the degradation abilities of the four key target receptors on PAHs were quantified, and the dominant target receptors that could efficiently degrade PAHs were screened out. Then, the co-degradation abilities of PAHs under the coexistence of the dominant target receptors (microbial diversity) were assessed, and 30 external condition-adding schemes to promote the microbial (co-)degradation of PAHs were designed. In addition, the microbial dominant target receptor mutants and the plant key target receptor mutants were obtained, the degradation and transportation of PAHs were improved by 8.06%∼22.27% and 39.86%∼45.43%. Finally, the mechanism analysis of PAHs biodegradation and transportation found that the Van der Waals interactions dominated the enhancement of PAHs' degradation in soil, and the solvation capacity dominated the decrease of PAHs' transportation in plant. This study aims to provide theoretical support for the prevention and control of PAHs residue pollution in farmland soil, as well as the protection of human dietary health.

Giant spin Hall effect in AB-stacked MoTe2/WSe2 bilayers.

The spin Hall effect (SHE), in which an electrical current generates a transverse spin current, plays an important role in spintronics for the generation and manipulation of spin-polarized electrons. The phenomenon originates from spin-orbit coupling. In general, stronger spin-orbit coupling favours larger SHEs but shorter spin relaxation times and diffusion lengths. However, correlated magnetic materials often do not support large SHEs. Achieving large SHEs, long-range spin transport and magnetism simultaneously in a single material is attractive for spintronics applications but has remained a challenge. Here we demonstrate a giant intrinsic SHE coexisting with ferromagnetism in AB-stacked MoTe2/WSe2 moiré bilayers by direct magneto-optical imaging. Under moderate electrical currents with density <1 A m-1, we observe spin accumulation on transverse sample edges that nearly saturates the spin density. We also demonstrate long-range spin Hall transport and efficient non-local spin accumulation that is limited only by the device size (about 10 µm). The gate dependence shows that the giant SHE occurs only near the interaction-driven Chern insulating state. At low temperatures, it emerges after the quantum anomalous Hall breakdown. Our results demonstrate moiré engineering of Berry curvature and electronic correlation for potential spintronics applications.

Synthesis of environmentally friendly neonicotinoid insecticide with proper functional properties by theoretical methodologies.

Modern insecticide substitutes using acetylcholine receptors (nAChR) as biochemical targets, such as neonicotinoid insecticides (NNIs), have been extensively researched. Only 12 compounds have been experimentally realized since the initial discovery of imidacloprid. Increasingly, the bottleneck in this field is to rapidly determine the synthesizability of NNI substitutes. Here, we designed a coupled evaluation system for synthesis prediction and validation, including the synthesis probability, reaction path difficulty, and electron transfer characteristics of NNIs and their substitutes. Firstly, a total of 1475 eigenvalues were generated and 52 critical eigenvalues were screened out through the Pearson's correlation coefficient. The positive and unlabeled (PU) machine learning was constructed using the critical eigenvalues NNIs, including 12 experimentally synthesized NNIs (positive samples) and 73 unsynthesized NNI substitutes (unlabeled samples). Results identified 3 NNI substitutes that were highly promising candidates for synthesis (synthesis probability > 0.5). The results of density functional theory demonstrated the ranking of their reaction ease was UN-1 (31.4 kcal/mol) > UN-2 (81.6 kcal/mol) > UN-3 (3.35 ×103 kcal/mol). Time-dependent density functional theory revealed that changes in the electron distribution and electron excitation type were critical factors affecting their synthesizability, and the local excitation type was more favorable for the synthesizability of NNI substituents. The findings provide significant guidance for NNIs synthesis, reducing the possible space of unlabeled samples to 95.89% of their original size, while also minimizing the cost of research on subsequent NNI substitutes.

Serum neurofilament light chain predicts spinal cord atrophy in neuromyelitis optica spectrum disorder.

Levels of serum neurofilament light chain (sNfL) and serum glial fibrillary acidic protein (sGFAP) are useful biomarkers of disease activity and disability in neuromyelitis optica spectrum disorder (NMOSD). Here we investigated the association of sNfL and sGFAP levels with brain and spinal cord volumes in patients with NMOSD. Fifteen patients with NMOSD were enrolled in this prospective study. The median baseline level of sNfL was 42.2 (IQR, 16.1-72.6) pg/mL and decreased to 8.5 (IQR, 7.4-16.6) pg/mL at the end of the study. The reduction in sNfL was associated with a 7.5% loss of cervical spinal cord volume (CSCV) (p = 0.001). The levels of sGFAP reduced from 239.2 (IQR, 139.0-3393.3) pg/mL at baseline to 108.5 (IQR, 74.2-154.6) pg/mL. However, there was no strong correlation between sGFAP levels and CSCV changes during the follow-up period. Our data suggested that sNfL level is a useful biomarker for predicting spinal cord atrophy in patients with NMOSD.

Screening eco-friendliness tire antioxidants alternatives: functional 2,2,4-trimethyl-1,2-dihydroquinoline derivatives design and toxicity evaluation.

Antioxidants which are indispensable functional additives used in rubber tires, are released into aquatic habitats from tire wear particles (TWP), collected in water bodies, and threaten the aquatic ecosystem. This study aimed to design eco-friendly derivatives of 2,2,4-trimethyl-1,2-dihydroquinoline (TMQ) with increased antioxidant activity to use as tire antioxidants. Initially, seventy highly efficient derivatives of TMQ were designed by hydroxylation modifications at multiple sites. The antioxidant activity of hydroxyl derivatives was characterized based on DFT method and compared with TMQ. Twenty derivatives showing a significant (greater than 9%) increase in antioxidant activity compared to TMQ were selected for the next stage. The toxicity risk of these twenty TMQ derivatives was assessed using various toxicokinetic methods. Finally, six TMQ derivatives with significantly lower toxicity risk compared to that of TMQ were evaluated for potential developmental toxicity. They were characterized using molecular docking and molecular dynamics techniques to assess the developmental toxicity risk in silver salmon by absorption of their ROO·, HO·, O2·- and O3 derivatives. TMQ-6 and TMQ-48 showed the lowest toxicity among all TMQ derivatives by a rather large margin. The study throws light on the path of future endeavors to develop highly efficient and greener tire antioxidants.

Personalized estimates of morphometric similarity in multiple sclerosis and neuromyelitis optica spectrum disorders.

Brain morphometric alterations involve multiple brain regions on progression of the disease in multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD) and exhibit age-related degenerative changes during the pathological aging. Recent advance in brain morphometry as measured using MRI have leveraged Person-Based Similarity Index (PBSI) approach to assess the extent of within-diagnosis similarity or heterogeneity of brain neuroanatomical profiles between individuals of healthy populations and validate in neuropsychiatric disorders. Brain morphometric changes throughout the lifespan would be invaluable for understanding regional variability of age-related structural degeneration and the substrate of inflammatory demyelinating disease. Here, we aimed to quantify the neuroanatomical profiles with PBSI measures of cortical thickness (CT) and subcortical volumes (SV) in 263 MS, 207 NMOSD, and 338 healthy controls (HC) from six separate central datasets (aged 11-80). We explored the between-group comparisons of PBSI measures, as well as the advancing age and sex effects on PBSI measures. Compared to NMOSD, MS showed a lower extent of within-diagnosis similarity. Significant differences in regional contributions to PBSI score were observed in 29 brain regions between MS and NMOSD (P < 0.05/164, Bonferroni corrected), of which bilateral cerebellum in MS and bilateral parahippocampal gyrus in NMOSD represented the highest divergence between the two patient groups, with a high similarity effect within each group. The PBSI scores were generally lower with advancing age, but their associations showed different patterns depending on the age range. For MS, CT profiles were significantly negatively correlated with age until the early 30 s (ρ = -0.265, P = 0.030), while for NMOSD, SV profiles were significantly negatively correlated with age with 51 year-old and older (ρ = -0.365, P = 0.008). The current study suggests that PBSI approach could be used to quantify the variation in brain morphometric changes in CNS inflammatory demyelinating disease, and exhibited a greater neuroanatomical heterogeneity pattern in MS compared with NMOSD. Our results reveal that, as an MR marker, PBSI may be sensitive to distribute the disease-associated grey matter diversity and complexity. Disease-driven production of regionally selective and age stage-dependency changes in the neuroanatomical profile of MS and NMOSD should be considered to facilitate the prediction of clinical outcomes and assessment of treatment responses.

A multi-framework for bisphenols based on their high performance and environmental friendliness: Design, screening, and recommendations.

Bisphenols (BPs) have gained significant attention due to their extensive use in the production of medical equipment, packaging materials, and everyday commodities. Urgent attention is required for assessing and identifying the risks associated with BP exposure to the environment and human health, as well as developing regulatory strategies. In this paper, 29 common BPs were selected as the research object, high-performance BP substitutes with environmental and human health friendliness characteristics were designed and screened. The above eight BP substitutes were considered as examples, and the first-level evaluation indicators of BPs and their substitutes were predicted using a random forest classification/regression model. Subsequently, the key indicators affecting the first-level evaluation indicators were ranked. The ranking results were environmental friendliness (64.30%) > human health risk (18.00%) > functionality (17.69%), indicating that environmental friendliness was the main influencing factor for the first-level evaluation indicators of BPs and their substitutes. Therefore, the study employed density functional theory (DFT) to simulate the biodegradation pathways of BPs and their substitutes in contaminated soil and landfill leachate, using Derivative-50 as an example. Furthermore, the environmental risk associated with the degradation products was evaluated, and regulatory recommendations based on risk identification were proposed.

Potential thyroid hormone disorder risks of tire antioxidants to aquatic food chain organisms after absorbing free radicals in marine and freshwater environments.

Tire antioxidants are essential functional chemical additives in tire rubber production. Because of the characteristic easy precipitation in the water environment, the environmental pollution problem caused by tire antioxidants is concerning. To reveal the mechanism by which tire antioxidants reduce common oxidative factors (free radicals) in the environment and to control the potential biological thyroid hormone disorder risk of tire antioxidant derivatives, eight commonly used antioxidants in tire production were selected for analysis. Firstly, the ability of tire antioxidants to reduce three different free radicals was quantitatively characterized based on Gaussian calculation method and inferring the radical reduction mechanism of tire antioxidants. Moreover, using the PaDEL-Descriptor software and random forest algorithm found that the N-octanol/water partition coefficient, a structure descriptor of tire antioxidant molecules, significantly correlated with their reducing ability. Second, molecular docking and molecular dynamics methods were used to assess the thyroid hormone disorder risk to aquatic organisms of eight antioxidants after reducing three free radicals. And this is the first study to construct an assessment score list of potential thyroid hormone disorder risk of the derivatives of tire antioxidants after reducing free radicals to marine and freshwater aquatic organisms based on the risk entropy method. Through the screening of this list, it was found that the derivative of the antioxidant 2,2,4-trimethyl-1,2-dihydroquinoline oxidized by free radicals had the highest risk of thyroid hormone disorder. In addition, the top organism in the aquatic food chain was the most affected. This study also revealed that van der Waals interactions and hydrogen bonding were the main influencing factors of thyroid hormone disorder risk to aquatic organisms of the derivatives of tire antioxidants that reduce free radicals based on amino acid residue analysis. Overall, the results provide theoretical support for the selection of antioxidants and the avoidance and control of environmental risks in the tire rubber production process.

SCUBE2 mediates bone metastasis of luminal breast cancer by modulating immune-suppressive osteoblastic niches.

Estrogen receptor (ER)-positive luminal breast cancer is a subtype with generally lower risk of metastasis to most distant organs. However, bone recurrence occurs preferentially in luminal breast cancer. The mechanisms of this subtype-specific organotropism remain elusive. Here we show that an ER-regulated secretory protein SCUBE2 contributes to bone tropism of luminal breast cancer. Single-cell RNA sequencing analysis reveals osteoblastic enrichment by SCUBE2 in early bone-metastatic niches. SCUBE2 facilitates release of tumor membrane-anchored SHH to activate Hedgehog signaling in mesenchymal stem cells, thus promoting osteoblast differentiation. Osteoblasts deposit collagens to suppress NK cells via the inhibitory LAIR1 signaling and promote tumor colonization. SCUBE2 expression and secretion are associated with osteoblast differentiation and bone metastasis in human tumors. Targeting Hedgehog signaling with Sonidegib and targeting SCUBE2 with a neutralizing antibody both effectively suppress bone metastasis in multiple metastasis models. Overall, our findings provide a mechanistic explanation for bone preference in luminal breast cancer metastasis and new approaches for metastasis treatment.

Exploring the Potential Hormonal Effects of Tire Polymers (TPs) on Different Species Based on a Theoretical Computational Approach.

Tire polymers (TPs) are the most prevalent type of microplastics and are of great concern due to their potential environmental risks. This study aims to determine the toxicity of TPs with the help of molecular-dynamics simulations of their interactions with receptors and to highlight the differences in the toxicity characteristics of TPs in different environmental media (marine environment, freshwater environment, soil environment). For this purpose, five TPs-natural rubber, styrene-butadiene rubber (SBR), butadiene rubber, nitrile-butadiene rubber, and isobutylene-isoprene rubber-were analyzed. Molecular-dynamics calculations were conducted on their binding energies to neurotoxic, developmental, and reproductive receptors of various organisms to characterize the toxic effects of the five TPs. The organisms included freshwater species (freshwater nematodes, snails, shrimp, and freshwater fish), marine species (marine nematodes, mussels, crab, and marine fish), and soil species (soil nematodes, springtails, earthworms, and spiders). A multilevel empowerment method was used to determine the bio-toxicity of the TPs in various environmental media. A coupled-normalization method-principal-component analysis-factor-analysis weighting method-was used to calculate the weights of the TP toxicity (first level) categories. The results revealed that the TPs were the most biologically neurotoxic to three environmental media (20.79% and 10.57% higher compared with developmental and reproductive toxicity, respectively). Regarding the effects of TPs on organisms in various environmental media (second level), using a subjective empowerment approach, a gradual increase in toxicity was observed with increasing trophic levels due to the enrichment of TPs and the feeding behavior of organisms. TPs had the greatest influence in the freshwater-environment organisms according to the subjective empowerment approach employed to weight the three environmental media (third level). Therefore, using the minimum-value method coupled with the feature-aggregation method, the interval-deflation method coupled with the entropy-weighting method, and the standard-deviation normalization method, the three toxicity characteristics of SBR in three environmental media and four organisms were determined. SBR was found to have the greatest impact on the overall toxicity of the freshwater environment (12.38% and 9.33% higher than the marine and soil environments, respectively). The greatest contribution to neurotoxicity (26.01% and 15.95% higher than developmental and reproductive toxicity, respectively) and the greatest impact on snails and shrimp among organisms in the freshwater environment were observed. The causes of the heterogeneity of SBR's toxicity were elucidated using amino-acid-residue analysis. SBR primarily interacted with toxic receptors through van der Waals, hydrophobic, π-π, and π-sigma interactions, and the more stable the binding, the more toxic the effect. The toxicity characteristics of TMPs to various organisms in different environments identified in this paper provide a theoretical basis for subsequent studies on the prevention and control of TMPs in the environment.

Switchable moiré potentials in ferroelectric WTe2/WSe2 superlattices.

Moiré materials with superlattice periodicity many times the atomic length scale have shown strong electronic correlations and band topology with unprecedented tunability. Non-volatile control of the moiré potentials could allow on-demand switching of superlattice effects but has remained challenging to achieve. Here we demonstrate the switching of the correlated and moiré band insulating states, and the associated nonlinear anomalous Hall effect, by the ferroelectric effect. This is achieved in a ferroelectric WTe2 bilayer of the Td structure with a centred-rectangular moiré superlattice induced by interfacing with a WSe2 monolayer of the H structure. The results can be understood in terms of polarization-dependent charge transfer between two WTe2 monolayers, in which the interfacial layer has a much stronger moiré potential depth; ferroelectric switching thus turns on and off the moiré insulating states. Our study demonstrates the potential for creating new functional moiré materials by incorporating intrinsic symmetry-breaking orders.

Determination of protein-bound α-amanitin in mouse plasma: A potential new indicator of poisoning with the mushroom toxin α-amanitin.

Approximately 70%∼90% of mushroom poisoning deaths are caused by the class of mushroom toxins known as amatoxins. However, the rapid elimination of amatoxins from plasma within 48 h after mushroom ingestion limits the practical value of plasma amatoxin analysis as a diagnostic indicator of Amanita mushroom poisoning. To increase the positive detection rate and extend the detection window of amatoxin poisoning, we developed a new method to detect protein-bound α-amanitin based on the hypothesis that RNAP II-bound α-amanitin released from the tissue into the plasma could be degraded by trypsin hydrolysis and then detected by conventional liquid chromatography-mass spectrometry (LC‒MS). Toxicokinetic studies on mice intraperitoneally injected with 0.33 mg/kg α-amanitin were conducted to obtain and compare the concentration trends, detection rates, and detection windows of both free α-amanitin and protein-bound α-amanitin. By comparing detection results with and without trypsin hydrolysis in the liver and plasma of α-amanitin-poisoned mice, we verified the credibility of this method and the existence of protein-bound α-amanitin in plasma. Under the optimized trypsin hydrolysis conditions, we obtained a time-dependent trend of protein-bound α-amanitin in mouse plasma at 1-12 days postexposure. In contrast to the short detection window (0-4 h) of free α-amanitin in mouse plasma, the detection window of protein-bound α-amanitin was extended to 10 days postexposure, with a total detection rate of 53.33%, ranging from the limit of detection to 23.94 µg/L. In conclusion, protein-bound α-amanitin had a higher positive detection rate and a longer detection window than free α-amanitin in mice.

Application of a developed triple-classification machine learning model for carcinogenic prediction of hazardous organic chemicals to the US, EU, and WHO based on Chinese database.

Cancer, the second largest human disease, has become a major public health problem. The prediction of chemicals' carcinogenicity before their synthesis is crucial. In this paper, seven machine learning algorithms (i.e., Random Forest (RF), Logistic Regression (LR), Support Vector Machines (SVM), Complement Naive Bayes (CNB), K-Nearest Neighbor (KNN), XGBoost, and Multilayer Perceptron (MLP)) were used to construct the carcinogenicity triple classification prediction (TCP) model (i.e., 1A, 1B, Category 2). A total of 1444 descriptors of 118 hazardous organic chemicals were calculated by Discovery Studio 2020, Sybyl X-2.0 and PaDEL-Descriptor software. The constructed carcinogenicity TCP model was evaluated through five model evaluation indicators (i.e., Accuracy, Precision, Recall, F1 Score and AUC). The model evaluation results show that Accuracy, Precision, Recall, F1 Score and AUC evaluation indicators meet requirements (greater than 0.6). The accuracy of RF, LR, XGBoost, and MLP models for predicting carcinogenicity of Category 2 is 91.67%, 79.17%, 100%, and 100%, respectively. In addition, the constructed machine learning model in this study has potential for error correction. Taking XGBoost model as an example, the predicted carcinogenicity level of 1,2,3-Trichloropropane (96-18-4) is Category 2, but the actual carcinogenicity level is 1B. But the difference between Category 2 and 1B is only 0.004, indicating that the XGBoost is one optimum model of the seven constructed machine learning models. Besides, results showed that functional groups like chlorine and benzene ring might influence the prediction of carcinogenic classification. Therefore, considering functional group characteristics of chemicals before constructing the carcinogenicity prediction model of organic chemicals is recommended. The predicted carcinogenicity of the organic chemicals using the optimum machine leaning model (i.e., XGBoost) was also evaluated and verified by the toxicokinetics. The RF and XGBoost TCP models constructed in this paper can be used for carcinogenicity detection before synthesizing new organic substances. It also provides technical support for the subsequent management of organic chemicals.

Triazine Herbicides Risk Management Strategies on Environmental and Human Health Aspects Using In-Silico Methods.

As an effective herbicide, 1, 3, 5-Triazine herbicides (S-THs) are used widely in the pesticide market. However, due to their chemical properties, S-THs severely threaten the environment and human health (e.g., human lung cytotoxicity). In this study, molecular docking, Analytic Hierarchy Process-Technique for Order Preference by Similarity to the Ideal Solution (AHP-TOPSIS), and a three-dimensional quantitative structure-active relationship (3D-QSAR) model were used to design S-TH substitutes with high herbicidal functionality, high microbial degradability, and low human lung cytotoxicity. We discovered a substitute, Derivative-5, with excellent overall performance. Furthermore, Taguchi orthogonal experiments, full factorial design of experiments, and the molecular dynamics method were used to identify three chemicals (namely, the coexistence of aspartic acid, alanine, and glycine) that could promote the degradation of S-THs in maize cropping fields. Finally, density functional theory (DFT), Estimation Programs Interface (EPI), pharmacokinetic, and toxicokinetic methods were used to further verify the high microbial degradability, favorable aquatic environment, and human health friendliness of Derivative 5. This study provided a new direction for further optimizations of novel pesticide chemicals.

Gate-tunable heavy fermions in a moiré Kondo lattice.

The Kondo lattice-a matrix of local magnetic moments coupled through spin-exchange interactions to itinerant conduction electrons-is a prototype of strongly correlated quantum matter1-4. Usually, Kondo lattices are realized in intermetallic compounds containing lanthanide or actinide1,2. The complex electronic structure and limited tunability of both the electron density and exchange interactions in these bulk materials pose considerable challenges to studying Kondo lattice physics. Here we report the realization of a synthetic Kondo lattice in AB-stacked MoTe2/WSe2 moiré bilayers, in which the MoTe2 layer is tuned to a Mott insulating state, supporting a triangular moiré lattice of local moments, and the WSe2 layer is doped with itinerant conduction carriers. We observe heavy fermions with a large Fermi surface below the Kondo temperature. We also observe the destruction of the heavy fermions by an external magnetic field with an abrupt decrease in the Fermi surface size and quasi-particle mass. We further demonstrate widely and continuously gate-tunable Kondo temperatures through either the itinerant carrier density or the Kondo interaction. Our study opens the possibility of in situ access to the phase diagram of the Kondo lattice with exotic quantum criticalities in a single device based on semiconductor moiré materials2-9.

In-silico analysis of atmospheric diffusion, crop planting degrading scheme, and health risk of dioxins from a domestic waste incineration plant.

Based on a domestic waste incineration power generation project, the dioxin emission from the waste incineration plant (WIP), phytoextraction and microbial degradation of dioxins, and dioxins human health risks reduction were investigated through in-silico methods. Based on the dioxins concentrations in soil (9.97 × 10-9-7.00 × 10-5ng/g) predicted by atmospheric dispersion model system and the Level-III fugacity model, planting schemes under different wind directions were designed considering the dioxin absorption capacity and the economic benefits for crops (i.e., barley, peanut, pea, maize and wheat). The dioxins in soils can be further degraded by five crops' rhizosphere microorganisms and fertilizers, simulated through molecular dynamic simulations. The enhanced degradation rates of dioxin by rhizosphere microorganisms of five crops reached 15.70 %-28.66 %. Finally, healthy dietary plans were developed to reduce the risk of dioxin exposure to the sensitive populations living around WIP. Results showed that the consumption of maize, fungus, mushroom and bamboo fungus could effectively reduce dioxins toxicity to humans by 58.13 %. The systematic approach developed in this study provided theoretical support for soil remediation and human health risk control of dioxins-contaminated sites.