Multivariate analysis for animal selection in experimental research
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0066-782X2015000200002&lng=en&nrm=iso&tlng=en http://hdl.handle.net/11449/127344 |
Resumo: | Background: Several researchers seek methods for the selection of homogeneous groups of animals in experimental studies, a fact justified because homogeneity is an indispensable prerequisite for casualization of treatments. The lack of robust methods that comply with statistical and biological principles is the reason why researchers use empirical or subjective methods, influencing their results. Objective: To develop a multivariate statistical model for the selection of a homogeneous group of animals for experimental research and to elaborate a computational package to use it. Methods: The set of echocardiographic data of 115 male Wistar rats with supravalvular aortic stenosis (AoS) was used as an example of model development. Initially, the data were standardized, and became dimensionless. Then, the variance matrix of the set was submitted to principal components analysis (PCA), aiming at reducing the parametric space and at retaining the relevant variability. That technique established a new Cartesian system into which the animals were allocated, and finally the confidence region (ellipsoid) was built for the profile of the animals’ homogeneous responses. The animals located inside the ellipsoid were considered as belonging to the homogeneous batch; those outside the ellipsoid were considered spurious. Results: The PCA established eight descriptive axes that represented the accumulated variance of the data set in 88.71%. The allocation of the animals in the new system and the construction of the confidence region revealed six spurious animals as compared to the homogeneous batch of 109 animals. Conclusion: The biometric criterion presented proved to be effective, because it considers the animal as a whole, analyzing jointly all parameters measured, in addition to having a small discard rate. |
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Multivariate analysis for animal selection in experimental researchAnálise multivariada na seleção de animais em pesquisas experimentaisMultivariate AnalysisAnimalsEpidemiologyExperimentalAortic valve stenosisAnálise multivariadaAnimaisEpidemiologia ExperimentalEstenose da válvula aórticaBackground: Several researchers seek methods for the selection of homogeneous groups of animals in experimental studies, a fact justified because homogeneity is an indispensable prerequisite for casualization of treatments. The lack of robust methods that comply with statistical and biological principles is the reason why researchers use empirical or subjective methods, influencing their results. Objective: To develop a multivariate statistical model for the selection of a homogeneous group of animals for experimental research and to elaborate a computational package to use it. Methods: The set of echocardiographic data of 115 male Wistar rats with supravalvular aortic stenosis (AoS) was used as an example of model development. Initially, the data were standardized, and became dimensionless. Then, the variance matrix of the set was submitted to principal components analysis (PCA), aiming at reducing the parametric space and at retaining the relevant variability. That technique established a new Cartesian system into which the animals were allocated, and finally the confidence region (ellipsoid) was built for the profile of the animals’ homogeneous responses. The animals located inside the ellipsoid were considered as belonging to the homogeneous batch; those outside the ellipsoid were considered spurious. Results: The PCA established eight descriptive axes that represented the accumulated variance of the data set in 88.71%. The allocation of the animals in the new system and the construction of the confidence region revealed six spurious animals as compared to the homogeneous batch of 109 animals. Conclusion: The biometric criterion presented proved to be effective, because it considers the animal as a whole, analyzing jointly all parameters measured, in addition to having a small discard rate.Fundamento: Muitos pesquisadores buscam métodos para a seleção de grupos homogêneos de animais em pesquisas experimentais, fato que se justifica por ser a homogeneidade pré-requisito indispensável à casualização de tratamentos. A ausência de métodos robustos, que atendam a princípios estatísticos e biológicos, faz com que os pesquisadores utilizem métodos empíricos ou subjetivos, influenciando seus resultados. Objetivo: Desenvolver modelo estatístico multivariado para a seleção de grupo homogêneo de animais para pesquisas experimentais e elaborar pacote computacional que o operacionalize. Métodos: O conjunto de dados ecocardiográficos de 115 ratos Wistar, machos, com estenose aórtica (EAo) supravalvular foi utilizado para exemplificar o desenvolvimento do modelo. Inicialmente, os dados foram padronizados, tornando-se adimensionais. Em sequência, submeteu-se a matriz de variabilidade do conjunto à análise de componentes principais (ACP) buscando-se reduzir o espaço paramétrico e conservar a variabilidade relevante. Essa técnica estabeleceu um novo sistema cartesiano em que os animais foram alocados e, finalmente, construiu-se a região de confiança (elipsoide) para o perfil de respostas homogêneas dos animais. Os que se situaram no interior do elipsoide foram considerados pertencentes ao grupo homogêneo; caso contrário, espúrios ao grupo. Resultados: A ACP estabeleceu oito eixos descritores que representaram a variabilidade acumulada dos dados em 88,71%. A alocação dos animais no novo sistema e a construção da região de confiança revelou a presença de seis espúrios ao lote homogêneo formado por 109 animais. Conclusão: O critério biométrico proposto mostra-se eficiente, pois considera o animal como um todo, analisando conjuntamente todos os parâmetros mensurados, além de apresentar pequena frequência de descartes.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Universidade Estadual Paulista Instituto de Ciências Biológicas Departamento de BioestatísticaUniversidade Estadual Paulista Faculdade de Medicina de Botucatu Departamento de Clínica MédicaUniversidade Estadual Paulista Instituto de Ciências Biológicas Departamento de BioestatísticaUniversidade Estadual Paulista Faculdade de Medicina de Botucatu Departamento de Clínica MédicaSociedade Brasileira de Cardiologia - SBCUniversidade Estadual Paulista (Unesp)Pinto, Renan Mercuri [UNESP]Campos, Dijon Henrique Salomé de [UNESP]Tomasi, Loreta Casquel [UNESP]Cicogna, Antonio Carlos [UNESP]Okoshi, Katashi [UNESP]Padovani, Carlos Roberto [UNESP]2015-08-26T19:19:15Z2015-08-26T19:19:15Z2015-02-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article97-103application/pdfhttp://www.scielo.br/scielo.php?script=sci_arttext&pid=S0066-782X2015000200002&lng=en&nrm=iso&tlng=enArquivos Brasileiros de Cardiologia, v. 104, n. 2, p. 97-103, 2015.0066-782Xhttp://hdl.handle.net/11449/12734410.5935/abc.20140219S0066-782X2015000200002S0066-782X2015000200002.pdf941897010356413787278970805222891590971576309420SciELOreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengArquivos Brasileiros de Cardiologia1.318info:eu-repo/semantics/openAccess2024-08-14T17:22:48Zoai:repositorio.unesp.br:11449/127344Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-14T17:22:48Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Multivariate analysis for animal selection in experimental research Análise multivariada na seleção de animais em pesquisas experimentais |
title |
Multivariate analysis for animal selection in experimental research |
spellingShingle |
Multivariate analysis for animal selection in experimental research Pinto, Renan Mercuri [UNESP] Multivariate Analysis Animals Epidemiology Experimental Aortic valve stenosis Análise multivariada Animais Epidemiologia Experimental Estenose da válvula aórtica |
title_short |
Multivariate analysis for animal selection in experimental research |
title_full |
Multivariate analysis for animal selection in experimental research |
title_fullStr |
Multivariate analysis for animal selection in experimental research |
title_full_unstemmed |
Multivariate analysis for animal selection in experimental research |
title_sort |
Multivariate analysis for animal selection in experimental research |
author |
Pinto, Renan Mercuri [UNESP] |
author_facet |
Pinto, Renan Mercuri [UNESP] Campos, Dijon Henrique Salomé de [UNESP] Tomasi, Loreta Casquel [UNESP] Cicogna, Antonio Carlos [UNESP] Okoshi, Katashi [UNESP] Padovani, Carlos Roberto [UNESP] |
author_role |
author |
author2 |
Campos, Dijon Henrique Salomé de [UNESP] Tomasi, Loreta Casquel [UNESP] Cicogna, Antonio Carlos [UNESP] Okoshi, Katashi [UNESP] Padovani, Carlos Roberto [UNESP] |
author2_role |
author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Pinto, Renan Mercuri [UNESP] Campos, Dijon Henrique Salomé de [UNESP] Tomasi, Loreta Casquel [UNESP] Cicogna, Antonio Carlos [UNESP] Okoshi, Katashi [UNESP] Padovani, Carlos Roberto [UNESP] |
dc.subject.por.fl_str_mv |
Multivariate Analysis Animals Epidemiology Experimental Aortic valve stenosis Análise multivariada Animais Epidemiologia Experimental Estenose da válvula aórtica |
topic |
Multivariate Analysis Animals Epidemiology Experimental Aortic valve stenosis Análise multivariada Animais Epidemiologia Experimental Estenose da válvula aórtica |
description |
Background: Several researchers seek methods for the selection of homogeneous groups of animals in experimental studies, a fact justified because homogeneity is an indispensable prerequisite for casualization of treatments. The lack of robust methods that comply with statistical and biological principles is the reason why researchers use empirical or subjective methods, influencing their results. Objective: To develop a multivariate statistical model for the selection of a homogeneous group of animals for experimental research and to elaborate a computational package to use it. Methods: The set of echocardiographic data of 115 male Wistar rats with supravalvular aortic stenosis (AoS) was used as an example of model development. Initially, the data were standardized, and became dimensionless. Then, the variance matrix of the set was submitted to principal components analysis (PCA), aiming at reducing the parametric space and at retaining the relevant variability. That technique established a new Cartesian system into which the animals were allocated, and finally the confidence region (ellipsoid) was built for the profile of the animals’ homogeneous responses. The animals located inside the ellipsoid were considered as belonging to the homogeneous batch; those outside the ellipsoid were considered spurious. Results: The PCA established eight descriptive axes that represented the accumulated variance of the data set in 88.71%. The allocation of the animals in the new system and the construction of the confidence region revealed six spurious animals as compared to the homogeneous batch of 109 animals. Conclusion: The biometric criterion presented proved to be effective, because it considers the animal as a whole, analyzing jointly all parameters measured, in addition to having a small discard rate. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-08-26T19:19:15Z 2015-08-26T19:19:15Z 2015-02-01 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0066-782X2015000200002&lng=en&nrm=iso&tlng=en Arquivos Brasileiros de Cardiologia, v. 104, n. 2, p. 97-103, 2015. 0066-782X http://hdl.handle.net/11449/127344 10.5935/abc.20140219 S0066-782X2015000200002 S0066-782X2015000200002.pdf 9418970103564137 8727897080522289 1590971576309420 |
url |
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0066-782X2015000200002&lng=en&nrm=iso&tlng=en http://hdl.handle.net/11449/127344 |
identifier_str_mv |
Arquivos Brasileiros de Cardiologia, v. 104, n. 2, p. 97-103, 2015. 0066-782X 10.5935/abc.20140219 S0066-782X2015000200002 S0066-782X2015000200002.pdf 9418970103564137 8727897080522289 1590971576309420 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Arquivos Brasileiros de Cardiologia 1.318 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
97-103 application/pdf |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Cardiologia - SBC |
publisher.none.fl_str_mv |
Sociedade Brasileira de Cardiologia - SBC |
dc.source.none.fl_str_mv |
SciELO reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128132831510528 |