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Molecules ; 24(17)2019 Aug 29.
Artigo em Inglês | MEDLINE | ID: mdl-31470620

RESUMO

Non-alcoholic fatty liver disease is a highly prevalent condition worldwide that increases the risk to develop liver fibrosis, cirrhosis, and hepatocellular carcinoma. Thus, it is imperative to develop novel diagnostic tools that together with liver biopsy help to differentiate mild and advanced degrees of steatosis. Ex-vivo liver samples were collected from mice fed a methionine-choline deficient diet for two or eight weeks, and from a control group. The degree of hepatic steatosis was histologically evaluated, and fat content was assessed by Oil-Red O staining. On the other hand, fluorescence spectroscopy was used for the assessment of the steatosis progression. Fluorescence spectra were recorded at excitation wavelengths of 330, 365, 385, 405, and 415 nm by establishing surface contact of the fiber optic probe with the liver specimens. A multi-variate statistical approach based on principal component analysis followed by quadratic discriminant analysis was applied to spectral data to obtain classifiers able to distinguish mild and moderate stages of steatosis at the different excitation wavelengths. Receiver Operating Characteristic (ROC) curves were computed to compare classifier's performances for each one of the five excitation wavelengths and steatosis stages. Optimal sensitivity and specificity were calculated from the corresponding ROC curves using the Youden index. Intensity in the endogenous fluorescence spectra at the given wavelengths progressively increased according to the time of exposure to diet. The area under the curve of the spectra was able to discriminate control liver samples from those with steatosis and differentiate among the time of exposure to the diet for most of the used excitation wavelengths. High specificities and sensitivities were obtained for every case; however, fluorescence spectra obtained by exciting with 405 nm yielded the best results distinguishing between the mentioned classes with a total classification error of 1.5% and optimal sensitivities and specificities better than 98.6% and 99.3%, respectively.


Assuntos
Tecido Adiposo/diagnóstico por imagem , Deficiência de Colina/diagnóstico por imagem , Fígado/diagnóstico por imagem , Metionina/deficiência , Hepatopatia Gordurosa não Alcoólica/diagnóstico por imagem , Espectrometria de Fluorescência/métodos , Tecido Adiposo/química , Tecido Adiposo/patologia , Animais , Área Sob a Curva , Deficiência de Colina/metabolismo , Deficiência de Colina/patologia , Análise Discriminante , Modelos Animais de Doenças , Progressão da Doença , Humanos , Fígado/química , Fígado/patologia , Masculino , Camundongos , Camundongos Endogâmicos C57BL , Hepatopatia Gordurosa não Alcoólica/metabolismo , Hepatopatia Gordurosa não Alcoólica/patologia , Análise de Componente Principal , Curva ROC , Sensibilidade e Especificidade , Índice de Gravidade de Doença , Espectrometria de Fluorescência/normas
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