Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
1
pubmed:dateCreated
2011-1-10
pubmed:abstractText
Subclinical mastitis (SM) is a major concern in the dairy industry because it causes economic losses and can lead to clinical mastitis. The mechanisms of the onset and progression of SM are not fully understood, and a new procedure for the detection and appropriate prediction of SM leading to clinical mastitis is necessary for dairy cow management. Inflammatory cytokines such as interleukin (IL)-6 are known to be present in inflamed mammary glands at the onset of mastitis, and IL-6 concentrations correlate with the levels of inflammation. In this study, the detection of IL-6 was examined for the evaluation for the future prediction of SM in 77 quarter milk samples from 20 cows. IL-6 concentrations in quarter milk were measured by sandwich ELISA, and the data were compared with milk somatic cell count (SCC) levels to diagnose SM. Average IL-6 concentration was significantly higher in SM quarter milk (207·0 ± 441·6 pg/ml) than in healthy control quarter milk (12·6 ± 33·4 pg/ml, P<0·01). Results of the cross-tabulation table show that SM prediction accuracy based on IL-6 concentration was almost equal or superior to SM prediction accuracy based on SCC. The detection of IL-6 in milk indicated SM earlier than did the detection of elevated SCC. Thus, the detection of IL-6 in milk could be a future prediction marker for SM.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Feb
pubmed:issn
1469-7629
pubmed:author
pubmed:issnType
Electronic
pubmed:volume
78
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
118-21
pubmed:meshHeading
pubmed:year
2011
pubmed:articleTitle
Interleukin-6 in quarter milk as a further prediction marker for bovine subclinical mastitis.
pubmed:affiliation
Food Microbiology and Food Safety, School of Veterinary Medicine, Rakuno Gakuen University, 582, Midorimachi, Bunkyodai, Ebetsu-shi, Hokkaido 069-8501, Japan.
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't