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
Line: 316
Function: require_once
Background: Idiopathic pulmonary fibrosis (IPF) is the most common type of fatal interstitial lung disease and IPF patients usually have a poor prognosis. Biomarkers that can predict the occurrence, process and prognosis of IPF will be useful for its diagnosis and treatment. This study aimed to identify the potential biomarkers of IPF and analyze the regulation of upstream miRNAs.
Methods: The miRNA and gene expression profiles were downloaded from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) and miRNAs (DEMs) between IPF and normal groups were identified. After co-expression gene pair analysis, functional enrichment analysis was performed. Then, the potential biomarkers of IPF were screened and validated. Finally, the upstream regulatory miRNA of biomarkers was predicted.
Results: A total of 343 DEGs and 21 DEMs were identified between IPF and normal samples. CLDN18, COL6A3, MYRF, PRSS8, RRAS, and SBNO1 were identified as potential IPF biomarkers. In addition, 17 miRNA-target relationship pairs were obtained. The up-regulation of hsa-miR-657, hsa-miR-671-5p, hsa-miR-198, and hsa-miR-940 could regulate the down-regulation of MYRF and the up-regulation of hsa-miR-198 and hsa-miR-373-3p could regulate the down-regulation of RRAS and CLDN18, respectively. Our data indicated that PRSS8, hsa-miR-614, and hsa-miR-503-5p might be involved in the migration and invasion of IPF related cells.
Conclusions: CLDN18, COL6A3, MYRF, PRSS8, RRAS, and SBNO1 might be potential IPF biomarkers. However, the specific role of these genes and miRNA in IPF needs further experimental research.
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http://dx.doi.org/10.1016/j.amjms.2021.06.027 | DOI Listing |
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