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
Coronary plaque destabilization involves alterations in microstructure and biochemical composition; however, no imaging approach allows such comprehensive characterization. Herein, the authors demonstrated a simultaneous microstructural and biochemical assessment of high-risk plaques in the coronary arteries in a beating heart using a fully integrated optical coherence tomography and fluorescence lifetime imaging (FLIm). It was found that plaque components such as lipids, macrophages, lipids+macrophages, and fibrotic tissues had unique fluorescence lifetime signatures that were distinguishable using multispectral FLIm. Because FLIm yielded massive biochemical readouts, the authors incorporated machine learning framework into FLIm, and ultimately, their approach enabled an automated, quantitative imaging of multiple key components relevant for plaque destabilization.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8733747 | PMC |
http://dx.doi.org/10.1016/j.jacbts.2021.10.005 | DOI Listing |
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