Using Network Pharmacology and Molecular Docking to Explore the Mechanism of Shan Ci Gu (Cremastra appendiculata) Against Non-Small Cell Lung Cancer

Background: In recent years, the incidence and mortality rates of non-small cell lung cancer (NSCLC) have increased significantly. Shan Ci Gu is commonly used as an anticancer drug in traditional Chinese medicine; however, its specific mechanism against NSCLC has not yet been elucidated. Here, the mechanism was clarified through network pharmacology and molecular docking.Methods: The Traditional Chinese Medicine Systems Pharmacology database was searched for the active ingredients of Shan Ci Gu, and the relevant targets in the Swiss Target Prediction database were obtained according to the structure of the active ingredients. GeneCards were searched for NSCLC-related disease targets. We obtained the cross-target using VENNY to obtain the core targets. The core targets were imported into the Search Tool for the Retrieval of Interacting Genes/Proteins database, and Cytoscape software was used to operate a mesh chart. R software was used to analyze the Gene Ontology biological processes (BPs) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. The core targets and active compounds were molecularly docked through Auto-Dock Vina software to predict the detailed molecular mechanism of Shan Ci Gu for NSCLC treatment. We did a simple survival analysis with hub gene to assess the prognosis of NSCLC patients.Results: Three compounds were screened to obtain 143 target genes and 1,226 targets related to NSCLC, of which 56 genes were related to NSCLC treatment. Shan Ci Gu treatment for NSCLC involved many BPs and acted on main targets including epidermal growth factor receptor (EGFR), ESR1, and SRC through signaling pathways including the endocrine resistance, EGFR tyrosine kinase inhibitor resistance, and ErbB signaling pathways. Shan Ci Gu might be beneficial for treating NSCLC by inhibiting cell proliferation and migration. Molecular docking revealed that the active compounds β-sitosterol, stigmasterol, and 2-methoxy-9,10-dihydrophenanthrene-4,5-diol had good affinity with the core target genes (EGFR, SRC, and ESR1). Core targets included EGFR, SRC, ESR1, ERBB2, MTOR, MCL1, matrix metalloproteinase 2 (MMP2), MMP9, KDR, and JAK2. Key KEGG pathways included endocrine resistance, EGFR tyrosine kinase inhibitor resistance, ErbB signaling, PI3K-Akt signaling, and Rap1 signaling pathways. These core targets and pathways have an inhibitory effect on the proliferation of NSCLC cells.Conclusion: Shan Ci Gu can treat NSCLC through a multi-target, multi-pathway molecular mechanism and effectively improve NSCLC prognosis. This study could serve as a reference for further mechanistic research on wider application of Shan Ci Gu for NSCLC treatment

Fine mapping and candidate gene analysis of proportion of four-seed pods by soybean CSSLs

Soybean yield, as one of the most important and consistent breeding goals, can be greatly affected by the proportion of four-seed pods (PoFSP). In this study, QTL mapping was performed by PoFSP data and BLUE (Best Linear Unbiased Estimator) value of the chromosome segment substitution line population (CSSLs) constructed previously by the laboratory from 2016 to 2018, and phenotype-based bulked segregant analysis (BSA) was performed using the plant lines with PoFSP extreme phenotype. Totally, 5 ICIM QTLs were repeatedly detected, and 6 BSA QTLs were identified in CSSLs. For QTL (qPoFSP13-1) repeated in ICIM and BSA results, the secondary segregation populations were constructed for fine mapping and the interval was reduced to 100Kb. The mapping results showed that the QTL had an additive effect of gain from wild parents. A total of 14 genes were annotated in the delimited interval by fine mapping. Sequence analysis showed that all 14 genes had genetic variation in promoter region or CDS region. The qRT−PCR results showed that a total of 5 candidate genes were differentially expressed between the plant lines having antagonistic extreme phenotype (High PoFSP > 35.92%, low PoFSP< 17.56%). The results of haplotype analysis showed that all five genes had two or more major haplotypes in the resource population. Significant analysis of phenotypic differences between major haplotypes showed all five candidate genes had haplotype differences. And the genotypes of the major haplotypes with relatively high PoFSP of each gene were similar to those of wild soybean. The results of this study were of great significance to the study of candidate genes affecting soybean PoFSP, and provided a basis for the study of molecular marker-assisted selection (MAS) breeding and four-seed pods domestication

BP neural network prediction model of floor failure depth in North China coalfield

North China coalfields are seriously affected by bottom aquifers. In order to accurately the depth of damage at the working face, this paper combined actual measurement with neural network prediction model in analysis. Firstly, DC method with special electrode cable is employed to observe the bottom plate damage depth of 15091 in the comprehensive mining face of Jiulishan mine; secondly, based on large-scale data, genetic algorithm is applied to optimize BP neural network. The prediction model of bottom plate damage depth is set up by optimizing parameters. The mean square error of the prediction model was 0.011, the average percentage error was 5.983 %, and the prediction error based on prediction set was below 10 %. These results indicate that the model can be used for predicting the bottom slab damage depth. Finally, the prediction model was used to analyze the effect of mining thickness and top cutting pressure relief on the depth of damage of the working face floor. Results show that under stratified mining, the depth of damage of the bottom slab is reduced by 77.84 % under cut top pressure relief than uncut top pressure relief; under integrated mining, the depth of damage of the bottom slab is reduced by 59.17 % under cut top pressure relief than uncut top pressure relief; and the effect of mining thickness on the depth of damage of the bottom slab is positively correlated

Hypoglycemic and Hypolipidemic Effects of <i>Phellinus Linteus</i> Mycelial Extract from Solid-State Culture in A Rat Model of Type 2 Diabetes

Hypoglycemic and hypolipidemic effects of P. linteus have been observed in numerous studies, but the underlying molecular mechanisms are unclear. In this study, we prepared P. linteus extract (PLE) from mycelia of solid-state culture, and evaluated its hypoglycemic and hypolipidemic effects in rat models of high-fat diet (HFD)-induced and low-dose streptozotocin (STZ)-induced type 2 diabetes. PLE treatment effectively reduced blood glucose levels, and improved insulin resistance and lipid and lipoprotein profiles. The hypoglycemic effect of PLE was based on inhibition of key hepatic gluconeogenesis enzymes (FBPase, G6Pase) expression and hepatic glycogen degradation, and consequent reduction of hepatic glucose production. PLE also: (i) enhanced expression of CPT1A and ACOX1 (key proteins involved in fatty acid &#946;-oxidation) and low-density lipoprotein receptor (LDLR) in liver, thus promoting clearance of triglycerides and LDL-C; (ii) inhibited expression of 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) in liver, thus reducing cholesterol production; (iii) displayed strong hepatoprotective and renal protective effects. Our findings indicate that PLE has strong potential functional food application in adjuvant treatment of type 2 diabetes with dyslipidemia

Reduction of vanadium(V) in a microbial fuel cell: V(IV) Migration and Electron Transfer Mechanism

The effects of vanadium on the microbial fuel cell performance, migration and distribution of V(IV) as well as electron transfer mechanism of single-chamber MFC were investigated by SEM, Fourier Transform Infrared Spectroscopy (FTIR), Cyclic Voltammetry (CV) and Electrochemical Impedance Spectroscopy (EIS). With anolyte vanadium concentration of 100 mg/L, the shortest degradation cycle was 130.67 h, while the degradation rate was 99.44%. V(V) combined with hydroxyl and carboxyl groups to form V(IV) organic participates, part of which deposited on the anode surface, and the other part distributed in anolyte. V(V) around cathode was reduced to V(IV) receiving electrons from the anode, meanwhile V(V) in anolyte was reduced to V(IV) owing to the electrons transfer on membrane binding enzyme complex. V(V) participated in cathode reactions instead of oxygen, accelerating the synchronization and integrity of electrode reactions

Finite Element Analysis of Densification Process in High Velocity Compaction of Iron-Based Powder

A finite element model based on elastic–plastic theory was conducted to study the densification process of iron-based powder metallurgy during high velocity compaction (HVC). The densification process of HVC at different heights was simulated using MSC Marc 2020 software with the Shima–Oyane model, and compared with the experimental results. The numerical simulation results were consistent with the experimental results, proving the reliability of the finite element model. Through finite element analysis and theoretical calculation, the high-speed impact molding process of metal powder was analyzed, and the optimal empirical compaction equation for iron-based powder high-speed impact molding was obtained. At the same time, the influence of impact velocity and impact energy on the relative density distribution cloud map and numerical values of the compact was analyzed