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
Tumor cell percentage (TCP) is an essential characteristic of biopsy samples that directly affects the sensitivity of molecular testing in clinical practice. Apart from clarifying diagnoses, rapid evaluation of TCP combined with various neuronavigation systems can be used to support decision making in neurosurgery. It is known that ambient mass spectrometry makes it possible to rapidly distinguish healthy from malignant tissues. In connection with this, here we demonstrate the possibility of using non-imaging ambient mass spectrometry to evaluate TCP in glial tumor tissues with a high degree of confidence. Molecular profiles of histologically annotated human glioblastoma tissue samples were obtained using the inline cartridge extraction ambient mass spectrometry approach. XGBoost regressors were trained to evaluate tumor cell percentage. Using cross-validation, it was estimated that the TCP was determined by the regressors with a precision of approximately 90% using only low-resolution data. This result demonstrates that ambient mass spectrometry provides an accurate method todetermine TCP in dissected tissues even without implementing mass spectrometry imaging. The application of such techniques offers the possibility to automate routine tissue screening and TCP evaluation to boost the throughput of pathology laboratories. Rapid estimation of tumor cell percentage during neurosurgery.
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Source |
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http://dx.doi.org/10.1007/s00216-021-03220-y | DOI Listing |
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