Indentificación de Fases de la Diabetes Espontánea de un Biomodelo Murino mediante Análisis Multidimensional de Datos
Biomodels used in the study of diabetes allow to evaluate genetic and environmental factors. Our aim was to characterize individuals of eSS, a genetically diabetic line of rats. We applied multivariate analysis, using the values obtained during the performance of oral glucose tolerance tests, presen...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Universidad de Costa Rica
2012-03-01
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| Series: | Revista de Matemática: Teoría y Aplicaciones |
| Online Access: | https://revistas.ucr.ac.cr/index.php/matematica/article/view/252 |
| _version_ | 1797726621940056064 |
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| author | Nora Moscoloni Silvana M. Montenegro Hugo D. Navone Juan Carlos Picena Stella M. Martínez M. Cristina Tarrés |
| author_facet | Nora Moscoloni Silvana M. Montenegro Hugo D. Navone Juan Carlos Picena Stella M. Martínez M. Cristina Tarrés |
| author_sort | Nora Moscoloni |
| collection | DOAJ |
| description | Biomodels used in the study of diabetes allow to evaluate genetic and environmental factors. Our aim was to characterize individuals of eSS, a genetically diabetic line of rats. We applied multivariate analysis, using the values obtained during the performance of oral glucose tolerance tests, presence of glucosuria, together with other physiological and environmental characteristics totalling 9 variables. Previously, an assignation of missing values of glucosuria was carried out through an artificial neural network classifier. To characterize individuals, principal componentes analysis was carried out. On describing data structure in a graphical representation of factorial coordinates, the first axe separated individuals according to glycemias, age and weight and the second opposed biomass in early ages to litter size. The cluster analysis defined a typology based on five classes. When these results were correlated with clinical classification, it was possible to separate eSS males from the youngest rats with low body weight, aglucosuric, with normal fasting glycemia but impaired glucose tolerance, up to diabetic individuals, older, with higher biomass and glucosuric. This methodology allows to identify stages in the progression of the diabetic syndrome |
| first_indexed | 2024-03-12T10:48:18Z |
| format | Article |
| id | doaj.art-2a4d6d5c408942478ba8f8a8daeecfee |
| institution | Directory Open Access Journal |
| issn | 2215-3373 |
| language | English |
| last_indexed | 2024-03-12T10:48:18Z |
| publishDate | 2012-03-01 |
| publisher | Universidad de Costa Rica |
| record_format | Article |
| series | Revista de Matemática: Teoría y Aplicaciones |
| spelling | doaj.art-2a4d6d5c408942478ba8f8a8daeecfee2023-09-02T07:13:02ZengUniversidad de Costa RicaRevista de Matemática: Teoría y Aplicaciones2215-33732012-03-01121-2738810.15517/rmta.v12i1-2.252237Indentificación de Fases de la Diabetes Espontánea de un Biomodelo Murino mediante Análisis Multidimensional de DatosNora Moscoloni0Silvana M. Montenegro1Hugo D. Navone2Juan Carlos Picena3Stella M. Martínez4M. Cristina Tarrés5Programa Interdisciplinario de Análisis de Datos (PIAD), IRICE (CONICET) / Universidad Nacional de RosarioPrograma Interdisciplinario de Análisis de Datos (PIAD), IRICE (CONICET) / Universidad Nacional de RosarioPrograma Interdisciplinario de Análisis de Datos (PIAD), IRICE (CONICET) / Universidad Nacional de RosarioPrograma Interdisciplinario de Análisis de Datos (PIAD), IRICE (CONICET) / Universidad Nacional de RosarioPrograma Interdisciplinario de Análisis de Datos (PIAD), IRICE (CONICET) / Universidad Nacional de RosarioPrograma Interdisciplinario de Análisis de Datos (PIAD), IRICE (CONICET) / Universidad Nacional de RosarioBiomodels used in the study of diabetes allow to evaluate genetic and environmental factors. Our aim was to characterize individuals of eSS, a genetically diabetic line of rats. We applied multivariate analysis, using the values obtained during the performance of oral glucose tolerance tests, presence of glucosuria, together with other physiological and environmental characteristics totalling 9 variables. Previously, an assignation of missing values of glucosuria was carried out through an artificial neural network classifier. To characterize individuals, principal componentes analysis was carried out. On describing data structure in a graphical representation of factorial coordinates, the first axe separated individuals according to glycemias, age and weight and the second opposed biomass in early ages to litter size. The cluster analysis defined a typology based on five classes. When these results were correlated with clinical classification, it was possible to separate eSS males from the youngest rats with low body weight, aglucosuric, with normal fasting glycemia but impaired glucose tolerance, up to diabetic individuals, older, with higher biomass and glucosuric. This methodology allows to identify stages in the progression of the diabetic syndromehttps://revistas.ucr.ac.cr/index.php/matematica/article/view/252 |
| spellingShingle | Nora Moscoloni Silvana M. Montenegro Hugo D. Navone Juan Carlos Picena Stella M. Martínez M. Cristina Tarrés Indentificación de Fases de la Diabetes Espontánea de un Biomodelo Murino mediante Análisis Multidimensional de Datos Revista de Matemática: Teoría y Aplicaciones |
| title | Indentificación de Fases de la Diabetes Espontánea de un Biomodelo Murino mediante Análisis Multidimensional de Datos |
| title_full | Indentificación de Fases de la Diabetes Espontánea de un Biomodelo Murino mediante Análisis Multidimensional de Datos |
| title_fullStr | Indentificación de Fases de la Diabetes Espontánea de un Biomodelo Murino mediante Análisis Multidimensional de Datos |
| title_full_unstemmed | Indentificación de Fases de la Diabetes Espontánea de un Biomodelo Murino mediante Análisis Multidimensional de Datos |
| title_short | Indentificación de Fases de la Diabetes Espontánea de un Biomodelo Murino mediante Análisis Multidimensional de Datos |
| title_sort | indentificacion de fases de la diabetes espontanea de un biomodelo murino mediante analisis multidimensional de datos |
| url | https://revistas.ucr.ac.cr/index.php/matematica/article/view/252 |
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