Linked Life Data

16158301

Source:http://linkedlifedata.com/resource/pubmed/id/16158301

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
4
pubmed:dateCreated
2005-10-19
pubmed:abstractText
Use of classical microbiological methods to differentiate bacteria that cause gastroenteritis is cumbersome but usually very efficient. The high cost of reagents and the time required for such identifications, approximately four days, could have serious consequences, however, mainly when the patients are children, the elderly, or adults with low resistance. The search for new methods enabling rapid and reagentless differentiation of these microorganisms is, therefore, extremely relevant. In this work the main microorganisms responsible for gastroenteritis, Escherichia coli, Salmonella choleraesuis, and Shigella flexneri, were studied. For each microorganism sixty different dispersions were prepared in physiological solution. The Raman spectra of these dispersions were recorded using a diode laser operating in the near infrared region. Partial least-squares (PLS) discriminant analysis was used to differentiate among the bacteria by use of their respective Raman spectra. This approach enabled correct classification of 100% of the bacteria evaluated and unknown samples from the clinical environment, in less time ( approximately 10 h), by use of a low-cost, portable Raman spectrometer, which can be easily used in intensive care units and clinical environments.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Oct
pubmed:issn
1618-2642
pubmed:author
pubmed:issnType
Print
pubmed:volume
383
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
701-6
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2005
pubmed:articleTitle
Rapid differentiation among bacteria that cause gastroenteritis by use of low-resolution Raman spectroscopy and PLS discriminant analysis.
pubmed:affiliation
Instituto de Química, Universidade de Franca, C.P. 82, 14404-600 Franca, SP, Brazil. camello@unifran.br
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't