To understand the mechanisms involved in the control and regulation of mitochondrial reactive oxygen species (ROS) levels, a two-compartment computational mitochondrial energetic-redox (ME-R) model accounting for energetic, redox, and ROS metabolisms is presented. The ME-R model incorporates four main redox couples (NADH/NAD(+), NADPH/NADP(+), GSH/GSSG, Trx(SH)(2)/TrxSS). Scavenging systems-glutathione, thioredoxin, superoxide dismutase, catalase-are distributed in mitochondrial matrix and extra-matrix compartments, and transport between compartments of ROS species (superoxide: O(2)(⋅-), hydrogen peroxide: H(2)O(2)), and GSH is also taken into account. Model simulations are compared with experimental data obtained from isolated heart mitochondria. The ME-R model is able to simulate: i), the shape and order of magnitude of H(2)O(2) emission and dose-response kinetics observed after treatment with inhibitors of the GSH or Trx scavenging systems and ii), steady and transient behavior of ΔΨ(m) and NADH after single or repetitive pulses of substrate- or uncoupler-elicited energetic-redox transitions. The dynamics of the redox environment in both compartments is analyzed with the model following substrate addition. The ME-R model represents a useful computational tool for exploring ROS dynamics, the role of compartmentation in the modulation of the redox environment, and how redox regulation participates in the control of mitochondrial function.
Living systems exhibit non-randomly organized biochemical, physiological, and behavioral processes that follow distinctive patterns. In particular, animal behavior displays both fractal dynamics and periodic rhythms yet the relationship between these two dynamic regimens remain unexplored. Herein we studied locomotor time series of visually isolated Japanese quails sampled every 0.5 s during 6.5 days (>106 data points). These high-resolution, week-long, time series enabled simultaneous evaluation of ultradian rhythms as well as fractal organization according to six different analytical methods that included Power Spectrum, Enright, Empirical Mode Decomposition, Wavelet, and Detrended Fluctuation analyses. Time series analyses showed that all birds exhibit circadian rhythms. Although interindividual differences were detected, animals presented ultradian behavioral rhythms of 12, 8, 6, 4.8, 4 h and/or lower and, irrespective of visual isolation, synchronization between these ultradian rhythms was observed. Moreover, all birds presented similar overall fractal dynamics (for scales ∼30 s to >4.4 h). This is the first demonstration that avian behavior presents fractal organization that predominates at shorter time scales and coexists with synchronized ultradian rhythms. This chronobiological pattern is advantageous for keeping the organism’s endogenous rhythms in phase with internal and environmental periodicities, notably the feeding, light-dark and sleep-wake cycles.
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