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Find video protocols related to scientific articles indexed in Pubmed.
Identification of clinical Pasteurella isolates by MALDI-TOF -- a comparison with VITEK 2 and conventional microbiological methods.
Diagn. Microbiol. Infect. Dis.
PUBLISHED: 01-17-2013
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The aim of this study was to compare the performance of four methods that are widely used in the clinical microbiology laboratory for identification of Pasteurella species. The 4 methods evaluated were VITEK2, VITEK MS (BioMerieux), and Bruker Biotyper MS (Bruker) as well as traditional biochemical tests. Sequencing of the sodA gene was used as the reference method. Sixty-five isolates of Pasteurella spp. from 65 patients were analyzed. One Pasteurella multocida isolate from American Type Culture Collection (Manassas, VA, USA) was used as a reference. Traditional biochemical tests accurately identified 62/66 (94%) isolates. Both Bruker and Vitek matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) identified 59/66 (89%) strains, but VITEK2 could only identify 32/66 (48.5%) isolates correctly. The mean time to identification using biochemical tests was 20 hours; VITEK2 took 6 hours and MALDI-TOF approximately 10 minutes. In conclusion, MALDI-TOF is a quick method, which accurately identified most isolates of Pasteurella to the species level. Thus, MALDI-TOF constitutes a valuable diagnostic tool in the clinical laboratory.
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What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

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We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

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In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.