Associations between and risks of trace elements related to skin and liver damage induced by arsenic from coal burning

Long-term exposure to high levels of arsenic has been documented to induce skin and liver damage, affecting hundreds of millions of people. While arsenic-induced skin and liver damage and trace element alterations have been studied, their correlations and risks have not been explained. Based on the above premise, this study included a total of 172 subjects from a coal-burning arsenic poisoning area. The levels of 18 trace elements in hair and six liver function indices in serum were detected, and the associations between and risks of trace elements related to skin and liver damage were analyzed. Finally, the receiver operating characteristic (ROC) curve and areas under the curve (AUC) were used to analyze the diagnostic values of certain trace elements for arsenic-induced skin and liver damage. The results found that a decrease in Se was a risk factor for arsenic-induced skin and liver damage (OR = 8.33 and 1.92, respectively). Furthermore, increases in Al and V were risk factors for arsenic-induced skin damage (OR = 1.05) and liver damage (OR = 13.16), respectively. In addition, the results found that Se and Al possessed certain diagnostic values for arsenic-induced skin damage (AUC = 0.93, 0.80), that Se possessed a diagnostic value for liver damage (AUC = 0.93), and that the combination of Se and Al increased the diagnostic value for skin damage (AUC = 0.96). This study provides an important research basis for further understanding the reasons for arsenic-induced skin and liver damage, for screening and identifying candidate diagnostic biomarkers, and for improving prevention and control strategies for arsenism.

Pharmacology mechanism of Flos magnoliae and Centipeda minima for treating allergic rhinitis based on pharmacology network

Chinese herbs such as Flos magnoliae (FM) and Centipeda minima (CM) can be effective in treating allergic rhinitis (AR). However, there is little research on the therapeutic mechanism of these two drugs acting on AR at the same time. In order to systematically understand the mechanism of action of two drugs acting on AR at the same time, we searched various databases to obtain 31 components and 289 target proteins of FM, 25 components and 465 target proteins of CM. The interaction networks of FM, CM, and AR proteins were constructed by Cytoscape-v3.2.1 software. The core protein of two network intersections was obtained by using Venny 2.1.0. The R platform was used for the core target protein gene ontology (GO) comment analysis and KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis. Thirteen common targets and seven acting pathways were obtained. The results of animal experiments showed that FM and CM volatile oil could effectively improve the symptoms of AR by regulating the common targets. In summary, this study successfully explained the potential therapeutic mechanism of FM and CM in the treatment of AR. At the same time, it indicates that the two drugs can be compatible as a new application.

PathwayMap: Molecular Pathway Association with Self-Normalizing Neural Networks

Drug discovery suffers from high attrition because compounds initially deemed as promising can later show ineffectiveness or toxicity resulting from a poor understanding of their activity profile. In this work, we describe a deep self-normalizing neural network model for the prediction of molecular pathway association and evaluate its performance, showing an AUC ranging from 0.69 to 0.91 on a set of compounds extracted from ChEMBL and from 0.81 to 0.83 on an external data set provided by Novartis. We finally discuss the applicability of the proposed model in the domain of lead discovery. A usable application is available via PlayMolecule.org .