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.

An in silico study on human carcinogenicity mechanism of polybrominated biphenyls exposure.

Polybrominated biphenyls (PBBs) are associated with an increased risk of thyroid cancer; however, relevant mechanistic studies are lacking. In this study, we investigated the mechanisms underlying PBB-induced human thyroid cancer. Molecular docking and molecular dynamics methods were employed to investigate the metabolism of PBBs by the cytochrome P450 enzyme under aryl hydrocarbon receptor mediation into mono- and di-hydroxylated metabolites. This was taken as the molecular initiation event. Subsequently, considering the interactions of PBBs and their metabolites with the thyroxine-binding globulin protein as key events, an adverse outcome pathway for thyroid cancer caused by PBBs exposure was constructed. Based on 2D quantitative structure activity relationship (2D-QSAR) models, the contribution of amino acid residues and binding energy were analyzed to understand the mechanism underlying human carcinogenicity (adverse effect) of PBBs. Hydrogen bond and van der Waals interactions were identified as key factors influencing the carcinogenic adverse outcome pathway of PBBs. Analysis of non-bonding forces revealed that PBBs and their hydroxylation products were predominantly bound to the thyroxine-binding globulin protein through hydrophobic and hydrogen bond interactions. The key amino acids involved in hydrophobic interactions were alanine 330, arginine 381 and lysine 270, and the key amino acids involved in hydrogen bond interactions were arginine 381 and lysine 270. This study provides valuable insights into the mechanisms underlying human health risk associated with PBBs exposure.

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.

Ultrasound-Based Nomogram for Predicting the Aggressiveness of Papillary Thyroid Carcinoma in Adolescents and Young Adults.

RATIONALE AND OBJECTIVES: Assessing the aggressiveness of papillary thyroid carcinoma (PTC) preoperatively might play an important role in guiding therapeutic strategy. This study aimed to develop and validate a nomogram that integrated ultrasound (US) features with clinical characteristics to preoperatively predict aggressiveness in adolescents and young adults with PTC. MATERIALS AND METHODS: In this retrospective study, a total of 2373 patients were enrolled and randomly divided into two groups with 1000 bootstrap sampling. The multivariable logistic regression (LR) analysis or least absolute shrinkage and selection operator LASSO regression was applied to select predictive US and clinical characteristics in the training cohort. By incorporating most powerful predictors, two predictive models presented as nomograms were developed, and their performance was assessed with respect to discrimination, calibration, and clinical usefulness. RESULTS: The LR_model that incorporated gender, tumor size, multifocality, US-reported cervical lymph nodes (CLN) status, and calcification demonstrated good discrimination and calibration with an area under curve (AUC), sensitivity and specificity of 0.802 (0.781-0.821), 65.58% (62.61%-68.55%), and 82.31% (79.33%-85.46%), respectively, in the training cohort; and 0.768 (0.736-0.797), 60.04% (55.62%-64.46%), and 83.62% (78.84%-87.71%), respectively, in the validation cohort. Gender, tumor size, orientation, calcification, and US-reported CLN status were combined to build LASSO_model. Compared with LR_model, the LASSO_model yielded a comparable diagnostic performance in both cohorts, the AUC, sensitivity, and specificity were 0.800 (0.780-0.820), 65.29% (62.26%-68.21%), and 81.93% (78.77%-84.91%), respectively, in the training cohort; and 0.763 (0.731-0.792), 59.43% (55.12%-63.93%), and 84.98% (80.89%-89.08%), respectively, in the validation cohort. The decision curve analysis indicated that using the two nomograms to predict the aggressiveness of PTC provided a greater benefit than either the treat-all or treat-none strategy. CONCLUSION: Through these two easy-to-use nomograms, the possibility of the aggressiveness of PTC in adolescents and young adults can be objectively quantified preoperatively. The two nomograms may serve as a useful clinical tool to provide valuable information for clinical decision-making.

Evaluation of synovial inflammation in juvenile idiopathic arthritis using superb microvascular imaging compared with power Doppler ultrasound.

OBJECTIVES: This study aimed to investigate the diagnostic and prognostic performance of superb microvascular imaging (SMI) in evaluation of synovial inflammation in patients with juvenile idiopathic arthritis (JIA) compared with power Doppler ultrasound (PDUS). METHODS: Fifty-nine patients with active disease and 62 patients with inactive disease were enrolled. The synovial inflammation was evaluated via vascularity index (VI) of SMI and PDUS. The correlations between VIs and the inflammatory biomarkers were analysed by Spearman's coefficient. Receiver operating characteristics curves were plotted to examine the prognostic value of SMI and PDUS. RESULTS: The VI of SMI was significantly higher than that of PDUS in JIA patients regardless of the disease activity. The SMI and PDUS VI were significantly correlated with levels of erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), and serum amyloid A (SAA). The SMI VI was significantly higher in patients with relapse than in those with remission, and showed superior performance in predicting relapse in JIA patients with inactive disease. CONCLUSIONS: SMI may detect the synovial inflammation with greater sensitivity than PDUS in patients with JIA, and correlate well with the inflammatory biomarkers. SMI signal in the knees might play an important role in prediction of relapse in clinically inactive patients, thus allowing personalised treatment strategies for JIA patients.

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.

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.

Source toxicity characteristics of short- and medium-chain chlorinated paraffin in multi-environmental media: Product source toxicity, molecular source toxicity and food chain migration control through silica methods.

Short and medium-chain chlorinated paraffin (SCCP/MCCP) have been widely studied because of their extensive environmental hazards. In this study, product source toxicity, molecular source toxicity and food chain migration of SCCP and MCCP in multi-environmental media were comprehensively considered. The additive combination of SCCP and MCCP in the air, water and soil environment was adjusted, and PVC, PU and rubber products with the lowest source toxicity were screened. The source toxicity of SCCP and MCCP in the water environment was inhibited by design of the feed additive addition scheme (highest inhibition was 16.29 %), and the source toxicity of SCCP and MCCP in the soil environment was affected by different field management measures (highest inhibition was 38.22 %). A forage fertilizer addition plan, a cattle feed addition plan and a special population healthy complementary food regulation plan were developed to prevent the migration step by step and absorption of SCCP and MCCP in the terrestrial food chain. In addition, by means of density functional theory and analysis of key amino acid residues, the mechanism of toxicity difference between SCCP and MCCP was analyzed from the level of chemical interaction, and rationality of the inhibition scheme designed in this study was verified.

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.

Ultrasound-based Nomogram for Predicting the Pathological Nodal Negativity of Unilateral Clinical N1a Papillary Thyroid Carcinoma in Adolescents and Young Adults.

RATIONALE AND OBJECTIVES: To develop and validate a nomogram incorporating clinical and ultrasound (US) characteristics for predicting the pathological nodal negativity of unilateral clinically N1a (cN1a) papillary thyroid carcinoma (PTC) among adolescents and young adults. MATERIALS AND METHODS: From December 2016 to August 2021, 278 patients aged ≤ 30 years from two medical centers were enrolled and randomly assigned to the training and validation cohorts at a ratio of 2:1. After performing univariate and multivariate analyses, a nomogram combining all independent predictive factors was constructed and applied to the validation cohort. The performance of the nomogram was evaluated using receiver operating characteristic curves, calibration curves, and decision curve analysis . RESULTS: Multivariate logistic regression analysis showed that unilateral cN1a PTC in young patients with Hashimoto's thyroiditis, T1 stage, no intra-tumoral microcalcification, and tumors located in the upper third of the thyroid gland was more likely to be free of central lymph node metastases. The nomogram revealed good calibration and discrimination in both cohorts, with areas under the receiver operating characteristic curve of 0.764 (95% confidence interval [CI]: 0.684-0.843) and 0.728 (95% CI: 0.602-0.853) in the training and validation cohorts, respectively. The clinical application of the nomogram was further confirmed using decision curve analysis. CONCLUSION: This US-based nomogram may assist the assessment of central cervical lymph nodes in young patients with unilateral cN1a PTC, enabling improved risk stratification and optimal treatment management in clinical practice.

Ectopic thymic tissue in subglottis of children: evaluation and management.

OBJECTIVES: Ectopic thymic tissue in the subglottis is an extremely rare disease that causes airway obstruction. Few cases reported were accurately diagnosed before surgery. METHODS: A case of a 2-year-old boy with airway obstruction caused by a left subglottic mass was reported. The presentation of radiological imaging, direct laryngoscopy and bronchoscopy, pathology, and surgical management were reviewed. An extensive search in PubMed, EMBASE, Web of Science, Google Scholar, and EBSCO of English literature was performed without a limit of time. RESULTS: Besides our case, only six cases were reported since 1987. The definitive diagnosis on these patients were made with the findings of pathology, of which, five were ectopic thymus and two were ectopic thymic cysts. Our case was the only one with a correct suspicion preoperatively. Four cases underwent open surgical resection, and two cases underwent microlaryngeal surgery, while one deceased after emergency tracheostomy. No recurrences were found by six patients during the follow-up after successful treatments. CONCLUSION: Ectopic thymus is a rare condition, infrequently considered in the differential diagnosis of subglottic masses. Modified laryngofissure may be an effective approach to removing the subglottic ectopic thymus and reconstructing the intact subglottic mucosa.

Aquatic toxicity of tire microplastics on marine and freshwater organisms: An in silico approach.

Tire wear particles are a notable source of tire microplastics (TMPs) in the environment. However, only a few reports have focused on the aquatic toxicity effects of composite TMPs and their additives and the mechanistic analysis at the microscopic level. Therefore, this paper study the toxic effects of tire microplastics and their additives on zebrafish based on theoretical chemical calculation method (Taguchi orthogonal experiment method, full factorial experimental design, molecular docking, and molecular dynamics computational technique). We designed five kinds of proportioning schemes of tire rubber polymers and additive components (64 groups in each). The compound toxicity effects of the tire rubber polymers and their additives on zebrafish were simulated and calculated. The simulation results indicated styrene butadiene rubber had the most significant toxic effect on zebrafish. Subsequently, taking the composition ratio scheme of styrene butadiene rubber with the lowest biotoxicity effect as an example, we analyzed the main effects, second-order interactions, and third-order interactions of styrene butadiene rubber polymer and its additive combination in terms of biotoxicity using the fixed effects model. The toxic effects (developmental toxicity, neurotoxicity, and reproductive toxicity) of styrene butadiene rubber on marine and freshwater organisms could be drastically alleviated by adjusting the ratio of rubber additives. The analysis of the interaction between amino acid residues and non-bonds during the docking process of styrene butadiene rubber and toxic receptors revealed the interaction mechanisms between the styrene butadiene rubber polymer and its additives and between the additive molecules. Hydrophobic interaction was found to be the key factor for the binding of styrene butadiene rubber additives to nonpolar amino acids in the receptor proteins. Our findings are expected to provide theoretical support for identifying and regulating the toxicity characteristics of rubber TMPs and to aid in proposing a strategy to alleviate the toxic effects on aquatic organisms.

Ectopic thymic tissue in subglottis of children: evaluation and management

Abstract Objectives: Ectopic thymic tissue in the subglottis is an extremely rare disease that causes airway obstruction. Few cases reported were accurately diagnosed before surgery. Methods: A case of a 2-year-old boy with airway obstruction caused by a left subglottic mass was reported. The presentation of radiological imaging, direct laryngoscopy and bronchoscopy, pathology, and surgical management were reviewed. An extensive search in PubMed, EMBASE, Web of Science, Google Scholar, and EBSCO of English literature was performed without a limit of time. Results: Besides our case, only six cases were reported since 1987. The definitive diagnosis on these patients were made with the findings of pathology, of which, five were ectopic thymus and two were ectopic thymic cysts. Our case was the only one with a correct suspicion preoper-atively. Four cases underwent open surgical resection, and two cases underwent microlaryngeal surgery, while one deceased after emergency tracheostomy. No recurrences were found by six patients during the follow-up after successful treatments. Conclusion: Ectopic thymus is a rare condition, infrequently considered in the differential diagnosis of subglottic masses. Modified laryngofissure may be an effective approach to removing the subglottic ectopic thymus and reconstructing the intact subglottic mucosa.

Human developmental toxicity mechanism of polybrominated biphenyl exposure and health risk regulation strategy for special populations.

Polybrominated biphenyls (PBBs) can bioaccumulate in nature and are toxic to humans. Long-time exposure to PBBs in pregnant women can lead to the birth of an infant with abnormal conditions. Hence, in this study, we used molecular docking, molecular dynamics, Taguchi experimental design, and fractional factorial experimental design to identify the developmental toxicity characteristics of 10 typical developmental toxic pollutants such as PBBs to which humans are frequently exposed. Furthermore, the correlation and sensitivity analyses of molecular developmental toxicity and structural parameters were performed. The molecular key structural parameters of the pollutants affecting human development were screened. Moreover, the supplementary food factors that could alleviate the developmental toxicity of pollutants were screened to develop supplementary food schemes to prevent or alleviate human developmental toxicity in the special population (e.g., pregnant women, infants) exposed to the pollutants. The results showed that the developmental toxicity was controlled by the main effects of the 10 pollutants. Among the 10 pollutants with developmental toxicity, the most significant pollutant with the main effects was PBB-153 (37.06%). In addition, the correlation and sensitivity analyses of the molecular developmental toxicity of the pollutants and structural parameters showed that the total energy value and infrared C-H vibration frequency of the pollutants were significantly correlated with human developmental toxicity. Accordingly, 15 supplementary food cofactors were selected for the Taguchi experiment design, among which the top seven cofactors were designed by fractional factorial analysis. The most significant cofactor that alleviated the developmental toxicity of PBB-153 exposure was the combination of carotene and docosahexaenoic acid (DHA), with an improvement of 17.28%. The combination of carotene and DHA significantly alleviated the effects of toxicity caused by most of the other pollutants, indicating that the selected supplementary food has certain universality. In this study, we developed a method to identify the characteristics of the developmental toxicity of pollutant exposure and developmental toxicity alleviation. Our study provided theoretical support for the regulation strategy of developmental toxicity caused by pollutants such as PBBs.

Strategies to Control Human Health Risks Arising from Antibiotics in the Environment: Molecular Modification of QNs for Enhanced Plant-Microbial Synergistic Degradation.

In the present work, a comprehensive screening and evaluation system was established to improve the plant-microbial synergistic degradation effects of QNs. The study included the construction of a 3D-QSAR model, the molecular modification, environmental friendliness and functional evaluation of drugs, degradation pathway simulation, and human health risk assessment. Molecular dynamics was applied to quantify the binding capacity of QNs toward the plant degradation enzyme (peroxidase) and microbial degradation enzymes (manganese peroxidase, lignin peroxidase, and laccase). The fuzzy comprehensive evaluation method was used in combination with the weighted average method for normalization and assigning equal weights to the plant and microbial degradation effect values of the QNs. Considering the synergistic degradation effect value as the dependent variable and the molecular information of the QNs as the independent variable, a 3D-QSAR model was constructed for the plant-microbial synergistic degradation effect of QNs. The constructed model was then employed to conduct the molecular modification, environmental friendliness and functional evaluation, degradation pathway simulation, and human health risk assessment of transformation products using pharmacokinetics and toxicokinetics. The results revealed that the synergistic degradation effect 3D-QSAR (CoMSIA) model exhibited good internal and external prediction ability, fitting ability, stability, and no overfitting phenomenon. Norfloxacin (NOR) was used as the target molecule in the molecular modification. A total of 35 NOR derivatives with enhanced plant-microbial synergistic degradation effect (1.32-21.51%) were designed by introducing small-volume, strongly electronegative, and hydrophobic hydrogen bond receptor groups into the active group of the norfloxacin structure. The environment-friendliness and the functionality of NOR were evaluated prior to and after the modification, which revealed seven environment-friendly FQs derivatives exhibiting moderate improvement in stability and bactericidal efficacy. The simulation of the NOR plant and microbial degradation pathways prior to and after the modification and the calculation of the reaction energy barrier revealed Pathway A (D-17 to D-17-2) and Pathway B (D-17 to D-17-4) as the most prone degradation pathways in plants and Pathway A (D-17 to D-17-1) and Pathway B (D-17 to D-17-4) as the most prone degradation pathways in microorganisms. This demonstrated that the degradation of the modified NOR derivatives was significantly enhanced, with the hydroxylation and piperazine ring substitution reaction playing an important role in the degradation process. Finally, the parameters, including hepatotoxicity, mutagenicity, and rodent carcinogenicity, among others, predicted using the pharmacokinetics and toxicokinetics analyses revealed a significant reduction in the human health risk associated with the modified NOR, along with a considerable reduction in the toxicity of its transformation products, implying that the human health risk associated with the transformation products was reduced remarkably. The present study provides a theoretical basis for novel ideas and evaluation programs for improving the plant-microbial synergistic degradation of the QNs antibiotics for source control and drug design, thereby reducing the residues of these antibiotics and the associated hazard in the complex plant-soil environment, ultimately decreasing the potential risks to human health.

Radiogenomic Analysis of Papillary Thyroid Carcinoma for Prediction of Cervical Lymph Node Metastasis: A Preliminary Study.

BACKGROUND: Papillary thyroid carcinoma (PTC) is characterized by frequent metastases to cervical lymph nodes (CLNs), and the presence of lymph node metastasis at diagnosis has a significant impact on the surgical approach. Therefore, we established a radiomic signature to predict the CLN status of PTC patients using preoperative thyroid ultrasound, and investigated the association between the radiomic features and underlying molecular characteristics of PTC tumors. METHODS: In total, 270 patients were enrolled in this prospective study, and radiomic features were extracted according to multiple guidelines. A radiomic signature was built with selected features in the training cohort and validated in the validation cohort. The total protein extracted from tumor samples was analyzed with LC/MS and iTRAQ technology. Gene modules acquired by clustering were chosen for their diagnostic significance. A radiogenomic map linking radiomic features to gene modules was constructed with the Spearman correlation matrix. Genes in modules related to metastasis were extracted for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, and a protein-protein interaction (PPI) network was built to identify the hub genes in the modules. Finally, the screened hub genes were validated by immunohistochemistry analysis. RESULTS: The radiomic signature showed good performance for predicting CLN status in training and validation cohorts, with area under curve of 0.873 and 0.831 respectively. A radiogenomic map was created with nine significant correlations between radiomic features and gene modules, and two of them had higher correlation coefficient. Among these, MEmeganta representing the upregulation of telomere maintenance via telomerase and cell-cell adhesion was correlated with 'Rectlike' and 'deviation ratio of tumor tissue and normal thyroid gland' which reflect the margin and the internal echogenicity of the tumor, respectively. MEblue capturing cell-cell adhesion and glycolysis was associated with feature 'minimum calcification area' which measures the punctate calcification. The hub genes of the two modules were identified by protein-protein interaction network. Immunohistochemistry validated that LAMC1 and THBS1 were differently expressed in metastatic and non-metastatic tissues (p=0.003; p=0.002). And LAMC1 was associated with feature 'Rectlike' and 'deviation ratio of tumor and normal thyroid gland' (p<0.001; p<0.001); THBS1 was correlated with 'minimum calcification area' (p<0.001). CONCLUSIONS: The radiomic signature proposed here has the potential to noninvasively predict the CLN status in PTC patients. Merging imaging phenotypes with genomic data could allow noninvasive identification of the molecular properties of PTC tumors, which might support clinical decision making and personalized management.

Optimal Allocation of Water Resources and Eco-Compensation Mechanism Model Based on the Interval-Fuzzy Two-Stage Stochastic Programming Method for Tingjiang River.

In this work, based on the upper line of water resources utilization and the bottom line of water environmental quality of "Three Lines, Single Project", a fuzzy optimization method was introduced into the Tingjiang River water resources optimal allocation and eco-compensation mechanism model, which is based on the interval two-stage (ITS) stochastic programming method. In addition, a Tingjiang River water resources allocation and eco-compensation mechanism model based on the interval fuzzy two-stage (IFTS) optimization method was also constructed. The objective functions of both models were to maximize the economic benefits of the Tingjiang River. The available water resources in the basin, the water environmental quality requirements, and regional development requirements were used as constraints, and under the five hydrological scenarios of extreme dryness, dryness, normal flow, abundance, and extreme abundance, the water resources allocation plan of various sectors (industry, municipal, agriculture, and ecology) in the Tingjiang River was optimized, and an eco-compensation mechanism was developed. In this work, the uncertainty of the maximum available water resources in each region and the whole basin was considered. If the maximum available water resources were too high, it would lead to a large waste of water resources, whereas if the maximum available water resources were too low, regional economic development would be limited. Therefore, the above two parameters were set as fuzzy parameters in the optimization model construction in this work. The simulation results from the IFTS model showed that the amount of water available in the river basin directly affects the water usage by various departments, thereby affecting the economic benefits of the river basin and the amount of eco-compensation paid by the downstream areas. The average economic benefit of the Tingjiang River after the optimization of the IFTS model simulation was [3868.51, 5748.99] × 108 CNY, which is an increase of [1.67%, 51.9%] compared to the economic benefit of the basin announced by the government in 2018. Compared to the ITS model, the economic benefit interval of the five hydrological scenarios of extreme dryness, dryness, normal flow, abundance, and extreme abundance was reduced by 28.54%, 44.9%, 31.49%, 40.37%, and 36.43%, respectively, which can improve the economic benefits of the basin and provide more accurate decision-making schemes. In addition, the IFTS simulation showed that the eco-compensation quota paid by downstream Guangdong Province to upstream Fujian Province is [28,116.4, 30,738.6] × 104 CNY, which is a reduction of [8461.404, 110,836] × 104 CNY compared to the 2018 compensation scheme of the government. Compared to the ITS model, the range of eco-compensation values was observed to increase by 9.94%, 54.81%, 15.85%, 50.31%, and 82.90%, respectively, under the five hydrological scenarios, which reduces the burden of ecological expenditure downstream and provides a broader decision-making space for decision-makers and thus enables improved decision-making efficiency. At the same time, after the optimization of the IFTS model, the additional water consumption of the second stage of the Tingjiang River during the extremely dry year decreased by 62.11% compared to the results of the ITS model. The additional water consumption of the industrial sector decreased by 68.39%, the municipal sector decreased by 59.27%, and in the first phase of water resources allocation for 14 districts and counties in the Tingjiang River, industrial and municipal sectors are the main two sectors. After introducing the fuzzy method into the IFTS model, the difference in the water consumption by these two sectors in the basin under different hydrological scenarios can be alleviated, and the waste of water resources caused by too low water allocation or excessive water allocation can be avoided. The national and local (the downstream region) eco-compensation quotas can be indirectly reduced, and the risk of water resources allocation and eco-compensation decision-making in the basin can be effectively reduced.

Environmentally Friendly Quinolones Design for a Two-Way Choice between Biotoxicity and Genotoxicity through Double-Activity 3D-QSAR Model Coupled with the Variation Weighting Method.

Quinolone (QN) antibiotics are widely used, which lead to their accumulation in soil and toxic effects on ryegrass in pasture. In this study, we employed ryegrass as the research object and selected the total scores of 29 QN molecules docked with two resistant enzyme structures, superoxide dismutase (SOD, PDB ID: 1B06) and proline (Pro, PPEP-2, PDB ID: 6FPC), as dependent variables. The structural parameters of QNs were used as independent variables to construct a QN double-activity 3D-QSAR model for determining the biotoxicity on ryegrass by employing the variation weighting method. This model was constructed to determine modification sites and groups for designing QNs molecules. According to the 3D contour map of the model, by considering enrofloxacin (ENR) and sparfloxacin (SPA) as examples, 23 QN derivatives with low biotoxicity were designed, respectively. The functional properties and environmental friendliness of the QN derivatives were predicted through a two-way selection between biotoxicity and genotoxicity before and after modification; four environmentally friendly derivatives with low biotoxicity and high genotoxicity were screened out. Mixed toxicity index and molecular dynamics methods were used to verify the combined toxicity mechanism of QNs on ryegrass before and after modification. By simulating the combined pollution of ENR and its derivatives in different soils (farmland, garden, and woodland), the types of combined toxicity were determined as partial additive and synergistic. Binding energies were calculated using molecular dynamics. The designed QN derivatives with low biotoxicity, high genotoxicity, and environmental friendliness can highly reduce the combined toxicity on ryegrass and can be used as theoretic reserves to replace QN antibiotics.

Tumor Proliferation and Invasiveness Derived From Ultrasound Appearances of Invasive Breast Cancers: Moving Beyond the Routine Differential Diagnosis.

OBJECTIVES: To investigate the correlation between ultrasound (US) appearances of invasive breast cancers and tumor proliferation and invasiveness measured according to the histologic grade, Ki-67 expression, axillary lymph node metastasis (ALNM), and lymphovascular invasion (LVI). METHODS: This study evaluated 676 patients who underwent primary surgical treatment of invasive breast cancers. The preoperative US reports and postoperative pathologic and immunohistochemical results of the patients were retrospectively reviewed. Ultrasound characteristics were evaluated according to the American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) lexicon. Logistic regression analyses were used to identify independent predictive US features that were correlated with tumor proliferation and invasiveness of breast cancers. Odds ratios (ORs) were calculated. RESULTS: Posterior acoustic enhancement and calcifications on US images were independent predictive factors of a higher histologic grade and a higher Ki-67 level (OR, 1.69-6.54; P < .05). Meanwhile, a noncircumscribed margin (OR, 2.61; P < .05) and posterior acoustic shadow (OR, 1.62; P < .05) were independent predictors of ALNM. An irregular shape (OR, 2.13; P < .05) and calcifications (OR, 1.69; P < .05) were independent risk factors for LVI. Infiltrative breast cancers scored as BI-RADS category 5 had higher probability to be associated with ALNM (OR, 3.33; P < .0005) and LVI (OR, 2.87; P < .0005). CONCLUSIONS: Ultrasound features of invasieve breast cancers might have a predictive value for tumor proliferation and invasiveness. The US features correlated with a high cellular proliferation rate were different from those associated with ALNM. The tumor shape, margin, posterior acoustic pattern, and calcifications at US are suggested to be considered by clinicians when making clinical decisions.