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
The aim of this study was to collect and identify airborne bacteria in Norway, Sweden and Finland and to compare three different technologies for identifying collected airborne bacterial isolates: the "gold standard" method 16S rDNA sequencing, MALDI-TOF MS using the MALDI Biotyper 2.0 and the MIDI Sherlock Microbial Identification System (MIDI MIS system). Airborne bacteria were collected during three different periods from May to October 2009 using air sampling directly on agar plates. A total of 140 isolates were collected during three sampling campaigns, and 74 % (103) of these isolates were analyzed by all three methods. The dominant genera in Norway and Finland were the gram-positive bacteria and , whereas the gram-negative bacterium was the dominant genus in Sweden. Using 16S rDNA sequencing, MALDI-TOF MS and MIDI MIS analysis, 83, 79 and 75 %, respectively, of the isolates were identified and assigned to order or higher taxonomic levels. In this study, the MALDI-TOF MS combining with the MALDI Biotyper 2.0 classification tool was demonstrated to be a fast and reliable alternative for identifying the airborne bacterial isolates. These studies have increased knowledge about the airborne bacterial background in outdoor air, which can be useful for evaluating and improving the operational performance of biological detectors in various environments. To our knowledge, this is the first time that 16S rDNA sequencing, MALDI-TOF MS and MIDI MIS analysis technologies have been compared for their efficiency in identifying airborne bacteria.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7087874 | PMC |
http://dx.doi.org/10.1007/s10453-015-9363-9 | DOI Listing |
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