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
Proteomics provide potential in the discovery of new sensitive biomarkers for environmental pollution. To evaluate this potential, we have utilized ProteinChip technology to analyze the proteomic profile of blue mussels (Mytilus edulis) from polluted marine habitats surrounding the island of Karmøy, Norway. Two different types of contamination, heavy metals and polyaromatic hydrocarbons (PAHs), were compared to a clean reference site. Differentially expressed proteins/peptides were found, which showed a specific induction or a general suppression associated with the field site of origin. By combining sets of protein markers in a tree-building algorithm, we were able to correctly classify samples from these sites with an accuracy of 90%.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1002/pmic.200300828 | DOI Listing |
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