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
Aristolochic acids are known to contribute to various renal disorders; therefore, expanding the availability of analytical methodology to detect these compounds is important in order to assess the quality of Chinese herbal medicines in which they can be found. Twelve medicinal herbal samples were procured from various sources and extracted in duplicate prior to a "fingerprint" analysis using conventional HPLC-DAD. Multivariate analysis was performed on the entire chromatographed fingerprints. The resulting output was a partial least-square discriminant analysis model, which was able to evaluate the potential presence of aristolochic acids I and II as well as providing an individual herbal "fingerprint". The results of this study provide evidence that the presence of aristolochic acids contained within certain herbal extractions could be detected using a simple method, although some limitations apply to this method for quality control, since newly detected samples for aristolochic acid (positives) will need further confirmation with purity checks or MS hyphenation.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1002/jssc.201000905 | DOI Listing |
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