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Find video protocols related to scientific articles indexed in Pubmed.
Characterization of Carnobacterium maltaromaticum LMA 28 for its positive technological role in soft cheese making.
Food Microbiol.
PUBLISHED: 05-03-2013
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Carnobacterium maltaromaticum is a lactic acid bacterium isolated from soft cheese. The objective of this work was to study its potential positive impact when used in cheese technology. Phenotypic and genotypic characterization of six strains of C. maltaromaticum showed that they belong to different phylogenetic groups. Although these strains lacked the ability to coagulate milk quickly, they were acidotolerant. They did not affect the coagulation capacity of starter lactic acid bacteria, Lactococcus lactis and Streptococcus thermophilus, used in dairy industry. The impact of C. maltaromaticum LMA 28 on bacterial flora of cheese revealed a significant decrease of Psychrobacter sp. concentration, which might be responsible for cheese aging phenomena. An experimental plan was carried out to unravel the mechanism of inhibition of Psychrobacter sp. and Listeria monocytogenes and possible interaction between various factors (cell concentration, NaCl, pH and incubation time). Cellular concentration of C. maltaromaticum LMA 28 was found to be the main factor involved in the inhibition of Psychrobacter sp. and L. monocytogenes.
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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.

Video X seems to be unrelated to Abstract Y...

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.