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
Gastric cancer is a commonly found malignant tumor, yet research on biomarkers of gastric cancer still face tremendous challenges. This study is the first to use gas chromatography-mass spectrometry (GC-MS) to measure and compare the metabolic profiles of gastric cancer cell lines with varying degrees of differentiation (MKN-28, SGC-7901, and AGS) with that of a normal gastric epithelial cell line (GES-1). OPLS-DA models were established to distinguish gastric cancer cell lines from a normal gastric epithelial cell line. In this study, we identified 278 metabolites, of which 111 show similarity scores greater than 700. Most notably, 6 metabolites (alanine, α-ketoisocaproic acid, proline, glyceric acid, pantothenic acid, and adenosine) showed varying expression levels between gastric cancer cell lines and a normal gastric epithelial cell line. These metabolites are potential biomarkers of gastric cancer and may be of great significance for the diagnosis, treatment and prognosis of gastric cancer patients.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6958048 | PMC |
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