How does exercise affect energy metabolism? An in silico approach for cardiac muscle.

We explored an in silico model of muscle energy metabolism and demonstrated its theoretical plausibility. Results indicate that energy metabolism triggered by activation can capture the muscle condition, rest, or exercise, and can respond accordingly adjusting the rates of their respiration and energy utilization for efficient use of the nutrients. Our study demonstrated during exercise higher respiratory activity causes a substantial increase in exergy release with an increase in exergy destruction, and entropy generation rate. The thermodynamic analysis showed that at the resting state when the exergy destruction rate was 0.66 W/kg and the respiratory metabolism energetic efficiency was 36% and exergetic efficiency was 32%; whereas, when the exergy destroyed was 1.24 W/kg, the energetic efficiency was 58% and exergetic efficiency was 50% during exercise. The efficiency results suggest the ability of the system to regulate itself in response to higher work demand and become more efficient in terms of converting energy coming from nutrients to useable energy when the circulating medium has sufficient energy precursor.

Astrocyte-neuron lactate shuttle may boost more ATP supply to the neuron under hypoxic conditions--in silico study supported by in vitro expression data.

BACKGROUND: Neuro-glial interactions are important for normal functioning of the brain as well as brain energy metabolism. There are two major working models--in the classical view, both neurons and astrocytes can utilize glucose as the energy source through oxidative metabolism, whereas in the astrocyte-neuron lactate shuttle hypothesis (ANLSH) it is the astrocyte which can consume glucose through anaerobic glycolysis to pyruvate and then to lactate, and this lactate is secreted to the extracellular space to be taken up by the neuron for further oxidative degradation. RESULTS: In this computational study, we have included hypoxia-induced genetic regulation of these enzymes and transporters, and analyzed whether the ANLSH model can provide an advantage to either cell type in terms of supplying the energy demand. We have based this module on our own experimental analysis of hypoxia-dependent regulation of transcription of key metabolic enzymes. Using this experimentation-supported in silico modeling, we show that under both normoxic and hypoxic conditions in a given time period ANLSH model does indeed provide the neuron with more ATP than in the classical view. CONCLUSIONS: Although the ANLSH is energetically more favorable for the neuron, it is not the case for the astrocyte in the long term. Considering the fact that astrocytes are more resilient to hypoxia, we would propose that there is likely a switch between the two models, based on the energy demand of the neuron, so as to maintain the survival of the neuron under hypoxic or glucose-and-oxygen-deprived conditions.