dc.creatorFaria A.V.
dc.creatorMacedo Jr. F.C.
dc.creatorMarsaioli A.J.
dc.creatorFerreira M.M.C.
dc.creatorCendes F.
dc.date2011
dc.date2015-06-30T20:25:49Z
dc.date2015-11-26T14:49:24Z
dc.date2015-06-30T20:25:49Z
dc.date2015-11-26T14:49:24Z
dc.date.accessioned2018-03-28T22:00:25Z
dc.date.available2018-03-28T22:00:25Z
dc.identifier
dc.identifierBrazilian Journal Of Medical And Biological Research. , v. 44, n. 2, p. 149 - 164, 2011.
dc.identifier0100879X
dc.identifier10.1590/S0100-879X2010007500146
dc.identifierhttp://www.scopus.com/inward/record.url?eid=2-s2.0-79951488475&partnerID=40&md5=d5c44b6d9146bf967c3f2dbbe767f5d6
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/107894
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/107894
dc.identifier2-s2.0-79951488475
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1253895
dc.descriptionHigh resolution proton nuclear magnetic resonance spectroscopy ( 1H MRS) can be used to detect biochemical changes in vitro caused by distinct pathologies. It can reveal distinct metabolic profiles of brain tumors although the accurate analysis and classification of different spectra remains a challenge. In this study, the pattern recognition method partial least squares discriminant analysis (PLS-DA) was used to classify 11.7 T 1H MRS spectra of brain tissue extracts from patients with brain tumors into four classes (high-grade neuroglial, low-grade neuroglial, non-neuroglial, and metastasis) and a group of control brain tissue. PLS-DA revealed 9 metabolites as the most important in group differentiation: γ-aminobutyric acid, acetoacetate, alanine, creatine, glutamate/glutamine, glycine, myo-inositol, N-acetylaspartate, and choline compounds. Leave-one-out crossvalidation showed that PLS-DA was efficient in group characterization. The metabolic patterns detected can be explained on the basis of previous multimodal studies of tumor metabolism and are consistent with neoplastic cell abnormalities possibly related to high turnover, resistance to apoptosis, osmotic stress and tumor tendency to use alternative energetic pathways such as glycolysis and ketogenesis.
dc.description44
dc.description2
dc.description149
dc.description164
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dc.languageen
dc.publisher
dc.relationBrazilian Journal of Medical and Biological Research
dc.rightsaberto
dc.sourceScopus
dc.titleClassification Of Brain Tumor Extracts By High Resolution 1h Mrs Using Partial Least Squares Discriminant Analysis
dc.typeArtículos de revistas


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