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(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Statistical physics approach to quantifying differences in myelinated nerve fibers

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Autor(es):
Comin, Cesar H. [1] ; Santos, Joao R. [2, 3] ; Corradini, Dario [2, 3] ; Morrison, Will [2, 3] ; Curme, Chester [2, 3] ; Rosene, Douglas L. [4] ; Gabrielli, Andrea [5, 6] ; Costa, Luciano da F. [1] ; Stanley, H. Eugene [2, 3]
Número total de Autores: 9
Afiliação do(s) autor(es):
[1] Univ Sao Paulo, Inst Phys Sao Carlos, BR-13560970 Sao Carlos, SP - Brazil
[2] Boston Univ, Dept Phys, Boston, MA 02215 - USA
[3] Boston Univ, Ctr Polymer Studies, Boston, MA 02215 - USA
[4] Boston Univ, Dept Anat & Neurobiol, Sch Med, Boston, MA 02118 - USA
[5] Univ Roma La Sapienza, UOS Sapienza, Dipartimento Fis, ISC, CNR, I-00185 Rome - Italy
[6] IMT Alti Studi Lucca, I-55100 Lucca - Italy
Número total de Afiliações: 6
Tipo de documento: Artigo Científico
Fonte: SCIENTIFIC REPORTS; v. 4, MAR 28 2014.
Citações Web of Science: 0
Resumo

We present a new method to quantify differences in myelinated nerve fibers. These differences range from morphologic characteristics of individual fibers to differences in macroscopic properties of collections of fibers. Our method uses statistical physics tools to improve on traditional measures, such as fiber size and packing density. As a case study, we analyze cross-sectional electron micrographs from the fornix of young and old rhesus monkeys using a semi-automatic detection algorithm to identify and characterize myelinated axons. We then apply a feature selection approach to identify the features that best distinguish between the young and old age groups, achieving a maximum accuracy of 94% when assigning samples to their age groups. This analysis shows that the best discrimination is obtained using the combination of two features: the fraction of occupied axon area and the effective local density. The latter is a modified calculation of axon density, which reflects how closely axons are packed. Our feature analysis approach can be applied to characterize differences that result from biological processes such as aging, damage from trauma or disease or developmental differences, as well as differences between anatomical regions such as the fornix and the cingulum bundle or corpus callosum. (AU)

Processo FAPESP: 11/22639-8 - Estudo da relação estrutura-dinâmica em redes modulares
Beneficiário:Cesar Henrique Comin
Linha de fomento: Bolsas no Brasil - Doutorado
Processo FAPESP: 11/50761-2 - Modelos e métodos de e-Science para ciências da vida e agrárias
Beneficiário:Roberto Marcondes Cesar Junior
Linha de fomento: Auxílio à Pesquisa - Temático