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: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
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
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Function: require_once
Background: Chronic obstructive pulmonary disease (COPD) is one of the most common respiratory diseases with undefined pathogenesis and unsatisfactory therapeutic options. Shenqi Wan (SQW), a traditional Chinese medicinal compound, has demonstrated certain preventive and therapeutic effects on COPD. However, the underlying molecular mechanisms remain incompletely understood. In this study, we used weighted gene co-expression network analysis (WGCNA) and machine learning to identify biomarkers for COPD, combined with network pharmacology and experimental validation to evaluate how SQW reduces airway inflammation in COPD.
Methods: Targets of SQW in treating COPD and its network regulation mechanism were predicted via network pharmacology. Meanwhile, potential biomarkers were predicted using WGCNA and machine learning algorithms and validated in COPD patients. The relationship between the core pathway and key target was analyzed by ingenuity pathway analysis (IPA) to reveal the regulatory mechanism of SQW. We evaluated the efficacy of SQW treatment in LPS/MS-induced COPD mice by evaluating lung function, histopathological parameters, and levels of inflammatory markers and oxidative stress. The distribution and expression of OPN/CD44/PI3K loop-related proteins were examined through immunofluorescence staining and Western Blotting. In vitro, we added LPS to BEAS-2B cells to mimic the inflammatory microenvironment and transfected the cells with OPN overexpression plasmid to observe the improvement induced by SQW.
Results: GO and KEGG analyses demonstrated that SQW inhibited inflammation and oxidative stress via the PI3K/Akt pathway, thereby improving COPD. Machine learning algorithms identified OPN as a potential biomarker, with elevated expression observed in the lung tissue of COPD patients. IPA indicated that OPN may modulate the CD44-mediated activation of the PI3K/AKT pathway, forming a positive feedback regulatory mechanism. SQW ameliorated lung function and pathological injury in mice; further, it reduced inflammation, oxidative stress, and OPN/CD44/PI3K positive feedback loop-related protein expression in both mice and cells. After OPN overexpression, the levels of inflammatory factors and ROS were significantly increased, and the OPN/CD44/PI3K signal was further activated, weakening the ameliorative effect of the SQW drug-containing serum.
Conclusion: Overall, SQW contributed to ameliorating COPD by reducing airway inflammation and oxidative stress through inhibiting the OPN/CD44/PI3K positive feedback loop.
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http://dx.doi.org/10.1016/j.intimp.2024.113624 | DOI Listing |
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