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
Among the numerous unknown metabolites representative of our exposure, focusing on toxic compounds should provide more relevant data to link exposure and health. For that purpose, we developed and applied a global method using data independent acquisition (DIA) in mass spectrometry to profile specifically electrophilic compounds originating metabolites. These compounds are most of the time toxic, due to their chemical reactivity toward nucleophilic sites present in biomacromolecules. The main line of cellular defense against these electrophilic molecules is conjugation to glutathione, then metabolization into mercapturic acid conjugates (MACs). Interestingly, MACs display a characteristic neutral loss in MS/MS experiments that makes it possible to detect all the metabolites displaying this characteristic loss, thanks to the DIA mode, and therefore to highlight the corresponding reactive metabolites. As a proof of concept, our workflow was applied to the toxicological issue of the oxidation of dietary polyunsaturated fatty acids, leading in particular to the formation of toxic alkenals, which lead to MACs upon glutathione conjugation and metabolization. By this way, dozens of MACs were detected and identified. Interestingly, multivariate statistical analyses carried out only on extracted HRMS signals of MACs yield a better characterization of the studied groups compared to results obtained from a classic untargeted metabolomics approach.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1021/acs.analchem.9b03146 | DOI Listing |
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