Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
This study employs network pharmacology to uncover the pharmacological mechanisms underlying Shen-qi-di-huang decoction's efficacy in treating uremia. We identified a total of 927 differentially expressed genes (DEGs) through differential expression analysis and the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database and analysis platform, of which 607 were downregulated and 320 were upregulated. We also obtained the effective biological components and related target gene information of Chinese herbal medicines such as Renshen, Huangqi, shudihuang, Shanyao, Fuling, Mudanpi, and Shanzhuyu in Shen-qi-di-huang decoction and constructed a regulatory relationship network between molecular components and target genes in Shen-qi-di-huang decoction. We then constructed a protein-protein interaction (PPI) network of 15 targeted genes (RXRA, ND6, CYP1B1, SLPI, CDKN1A, RB1, HIF1A, MYC, HSPB1, IFNGR1, NQO1, IRF1, RASA1, PSMG1 and MAP2K4) using the STRING database and visualized the PPI network using the software Cytoscape. In addition, we revealed the key molecular functions of uremia through Gene Ontology (GO) enrichment analysis, mainly including neuron apoptotic process, cellular response to oxidative stress, regulation of neuron apoptotic process, neuron projection cytoplasm, RNA polymerase II transcription regulator complex, plasma membrane bounded cell projection cytoplasm, NADH and NADPH dehydrogenase (quinone) activity, protein kinase inhibitor and ubiquitin protein ligase binding, etc. Finally, we identified important biological pathways in uremia through Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, which mainly concentrated in Kaposi sarcoma-associated, small cell lung cancer, Gastric cancer, Hepatitis B and C, Hepatocellular carcinoma, Thyroid cancer, Bladder cancer, MAPK signaling pathway, ErbB signaling pathway, Th17 cell differentiation, HIF-1 signaling pathway, Thyroid hormone signaling pathway and Cell cycle, etc. Using integrated bioinformatical analysis, we elucidated key pharmacological mechanisms based on targeted genes, which was enable early identification of patients with uremia and would contribute to early clinical diagnosis and treatment of patients.
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