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
Empiric broad-spectrum antimicrobial treatments of urinary tract infections (UTIs) have contributed to widespread antimicrobial resistance. Clinical adoption of evidence-based treatments necessitates rapid diagnostic methods for pathogen identification (ID) and antimicrobial susceptibility testing (AST) with minimal sample preparation. In response, a microfluidic droplet-based platform is developed for achieving both ID and AST from urine samples within 30 min. In this platform, fluorogenic hybridization probes are utilized to detect 16S rRNA from single bacterial cells encapsulated in picoliter droplets, enabling molecular identification of uropathogenic bacteria directly from urine in as little as 16 min. Moreover, in-droplet single-bacterial measurements of 16S rRNA provide a surrogate for AST, shortening the exposure time to 10 min for gentamicin and ciprofloxacin. A fully integrated device and screening workflow were developed to test urine specimens for one of seven unique diagnostic outcomes including the presence/absence of Gram-negative bacteria, molecular ID of the bacteriaas , an , or other organism, and assessment of bacterial susceptibility to ciprofloxacin. In a 50-specimen clinical comparison study, the platform demonstrates excellent performance compared to clinical standard methods (areas-under-curves, AUCs >0.95), within a small fraction of the turnaround time, highlighting its clinical utility.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7967084 | PMC |
http://dx.doi.org/10.1002/advs.202003419 | DOI Listing |
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