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
Sarcomas, a diverse group of malignant tumors originating from connective tissues, present substantial diagnostic challenges due to their histological heterogeneity. Traditional diagnostic methods include histomorphology along with immunohistochemistry is necessary for primary evaluation. Fluorescence in situ hybridization (FISH) is a supplementary tool that helps with additional findings. However it is very difficult sometimes to accurately classify sarcoma subtypes despite all these tools. Recent advancements in DNA methylation profiling have emerged as a promising approach to enhance the precision of sarcoma diagnosis. This paper delves into the role of DNA methylation classifiers in diagnosing sarcomas, emphasizing their potential to improve diagnostic accuracy, inform treatment decisions, and ultimately enhance patient outcomes.
Download full-text PDF |
Source |
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http://dx.doi.org/10.1016/j.prp.2024.155634 | DOI Listing |
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