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
Digital pathology has the potential to quantify tumor markers accurately and reproducibly with various cellular and subcellular localizations in tissues, thus filling a need in cancer research. As a case study, we quantified the percentage of necrosis, microvessels density, and monocarboxylate transporter 4 (MCT4) expression in two ovarian cancer patient-derived xenograft (PDX) models subcutaneously injected in NOD/SCID mice. PDX models were treated with bevacizumab, an antiangiogenic drug, that targets vascular endothelial growth factor A (VEGF-A). Specific signal analysis algorithms allowed us to study morphologic, vascular, and metabolic modifications induced by antiangiogenic therapy by a quantitative, reproducible, and reliable approach.
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Source |
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http://dx.doi.org/10.1007/978-1-0716-2703-7_6 | DOI Listing |
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