Chaotic fluctuations in mitochondrial function under oxidative stress. SOD2 concentrations of 0.0216733 mM

• Autores: Kembro, Jackelyn Melissa; Cortassa, Sonia; Lloyd, David; Sollot, Steven; Aon, Miguel
• Año de publicación: 2018
• Idioma: inglés
• Tipo de recurso: conjunto de datos
• Materia: Animal Physiology - Systems; Molecular Biology; Superoxide dismutase activity; Respiration; Oxidative stress effect; Oxidative stress enzymes
• Institución: Universidad Nacional de Córdoba

Fil: Kembro, Jackelyn Melissa. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina.
Fil: Kembro, Jackelyn Melissa. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones Biológicas y Tecnológicas; Argentina.
Fil: Cortassa, Sonia. National Institutes of Health. NIH · NIA Intramural Research Program; Estados Unidos.
Fil: Lloyd, David. Cardiff University. School of Biosciences 1; Inglaterra.
Fil: Sollot, Steven. Johns Hopkins University. Laboratory of Cardiovascular Science; Estados Unidos.
Fil: Aon, Miguel. Johns Hopkins University. Laboratory of Cardiovascular Science; Estados Unidos.
Numerical integration of the ME-R model equations was performed with MatCont 2.4 in MATLAB 7.1, until steady-state solutions were obtained (i.e., when the magnitude of each time derivative was -10). Time series with duration of at least 6e6 ms were constructed by numerical integration of model equations. To allow transient states to vanish, the system was computed during a time lapse of 2 e8 ms. The solutions were then evaluated with the function deval.m in MATLAB R2017a to obtain a time series with constant sampling frequency at 1ms. All studies were performed using the parameter setting optimized in our previous work (Kembro et al. 2013. Biophys J 104(2):332-343; Kembro et al., 2014. Front Physiol 5:257), with ADPm = 0.01mM, i.e. consistent with energized mitochondria under state 4 respiration. The two .txt file represents the time reference and the time series of variables output of the model, in order from left to right column:1) Mitochondrial Ca+;2) Mitochondrial ADP; 3) Membrane potential; 4)Mitocondrial NADH; 5) Mitochondrial H+; 6) Mitochondrial Phosfate, Pi; 7) Isocitrate; 8) a-ketoglutarate; 9) Succinyl CoA; 10) Succinate; 11) Fumarate; 12) Malate; 13) Oxaloacetate; 14) NADPH; 15) Mitochondrial superoxide; 16) Extramitochondrial superoxide; 17) Mitochondrial hydrogen peroxide; 18) Extramitochondrial hydrogen peroxide; 19) Mitochondrial GSH; 20) Extramitochondrial GSH; 21)Mitochondrial GSSG; 22) Mitochondrial TrxSH2; 23) ExtramitochondrialTrxSH; 24)Mitochondrial PSSGm; 25) Extramitochondrial PSSG
Fil: Kembro, Jackelyn Melissa. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas, Físicas y Naturales; Argentina.
Fil: Kembro, Jackelyn Melissa. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Investigaciones Biológicas y Tecnológicas; Argentina.
Fil: Cortassa, Sonia. National Institutes of Health. NIH · NIA Intramural Research Program; Estados Unidos.
Fil: Lloyd, David. Cardiff University. School of Biosciences 1; Inglaterra.
Fil: Sollot, Steven. Johns Hopkins University. Laboratory of Cardiovascular Science; Estados Unidos.
Fil: Aon, Miguel. Johns Hopkins University. Laboratory of Cardiovascular Science; Estados Unidos.