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Proceedings Paper

Method of empirical dependences in estimation and prediction of activity of creatine kinase isoenzymes in cerebral ischemia
Author(s): Tatiana F. Sergeeva; Albina N. Moshkova; Elena I. Erlykina; Elena M. Khvatova
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Paper Abstract

Creatine kinase is a key enzyme of energy metabolism in the brain. There are known cytoplasmic and mitochondrial creatine kinase isoenzymes. Mitochondrial creatine kinase exists as a mixture of two oligomeric forms – dimer and octamer. The aim of investigation was to study catalytic properties of cytoplasmic and mitochondrial creatine kinase and using of the method of empirical dependences for the possible prediction of the activity of these enzymes in cerebral ischemia. Ischemia was revealed to be accompanied with the changes of the activity of creatine kinase isoenzymes and oligomeric state of mitochondrial isoform. There were made the models of multiple regression that permit to study the activity of creatine kinase system in cerebral ischemia using a calculating method. Therefore, the mathematical method of empirical dependences can be applied for estimation and prediction of the functional state of the brain by the activity of creatine kinase isoenzymes in cerebral ischemia.

Paper Details

Date Published: 21 April 2016
PDF: 6 pages
Proc. SPIE 9917, Saratov Fall Meeting 2015: Third International Symposium on Optics and Biophotonics and Seventh Finnish-Russian Photonics and Laser Symposium (PALS), 99171U (21 April 2016); doi: 10.1117/12.2229863
Show Author Affiliations
Tatiana F. Sergeeva, Nizhny Novgorod State Medical Academy (Russian Federation)
Albina N. Moshkova, Nizhny Novgorod State Technical Univ. (Russian Federation)
Elena I. Erlykina, Nizhny Novgorod State Medical Academy (Russian Federation)
Elena M. Khvatova, Nizhny Novgorod State Medical Academy (Russian Federation)


Published in SPIE Proceedings Vol. 9917:
Saratov Fall Meeting 2015: Third International Symposium on Optics and Biophotonics and Seventh Finnish-Russian Photonics and Laser Symposium (PALS)
Elina A. Genina; Valery V. Tuchin; Vladimir L. Derbov; Dmitry E. Postnov; Igor V. Meglinski; Kirill V. Larin; Alexander Borisovich Pravdin, Editor(s)

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