A computational model of cardiomyocyte metabolism predicts unique reperfusion protocols capable of reducing cell damage during ischemia/reperfusion.

If a coronary blood vessel is occluded and the neighboring cardiomyocytes deprived of oxygen, subsequent reperfusion of the ischemic tissue can lead to oxidative damage due to excessive generation of reactive oxygen species. Cardiomyocytes and their mitochondria are the main energy producers and consumers of the heart, and their metabolic changes during ischemia seem to be a key driver of reperfusion injury. Here, we hypothesized that tracking changes in cardiomyocyte metabolism, such as oxygen and ATP concentrations, would help in identifying points of metabolic failure during ischemia and reperfusion. To track some of these changes continuously from the onset of ischemia through reperfusion, we developed a system of differential equations representing the chemical reactions involved in the production and consumption of 67 molecular species. This model was validated and used to identify conditions present during periods of critical transition in ischemia and reperfusion that could lead to oxidative damage. These simulations identified a range of oxygen concentrations that lead to reverse mitochondrial electron transport at complex I of the respiratory chain and a spike in mitochondrial membrane potential, which are key suspects in the generation of reactive oxygen species at the onset of reperfusion. Our model predicts that a short initial reperfusion treatment with reduced oxygen content (5% of physiological levels) could reduce the cellular damage from both of these mechanisms. This model should serve as an open-source platform to test ideas for treatment of the ischemia reperfusion process by following the temporal evolution of molecular concentrations in the cardiomyocyte.

In vivo visualization of butterfly scale cell morphogenesis in Vanessa cardui.

During metamorphosis, the wings of a butterfly sprout hundreds of thousands of scales with intricate microstructures and nano-structures that determine the wings' optical appearance, wetting characteristics, thermodynamic properties, and aerodynamic behavior. Although the functional characteristics of scales are well known and prove desirable in various applications, the dynamic processes and temporal coordination required to sculpt the scales' many structural features remain poorly understood. Current knowledge of scale growth is primarily gained from ex vivo studies of fixed scale cells at discrete time points; to fully understand scale formation, it is critical to characterize the time-dependent morphological changes throughout their development. Here, we report the continuous, in vivo, label-free imaging of growing scale cells of Vanessa cardui using speckle-correlation reflection phase microscopy. By capturing time-resolved volumetric tissue data together with nanoscale surface height information, we establish a morphological timeline of wing scale formation and gain quantitative insights into the underlying processes involved in scale cell patterning and growth. We identify early differences in the patterning of cover and ground scales on the young wing and quantify geometrical parameters of growing scale features, which suggest that surface growth is critical to structure formation. Our quantitative, time-resolved in vivo imaging of butterfly scale development provides the foundation for decoding the processes and biomechanical principles involved in the formation of functional structures in biological materials.

Modeling oxygen requirements in ischemic cardiomyocytes.

Heart disease remains the leading cause of death globally. Although reperfusion following myocardial ischemia can prevent death by restoring nutrient flow, ischemia/reperfusion injury can cause significant heart damage. The mechanisms that drive ischemia/reperfusion injury are not well understood; currently, few methods can predict the state of the cardiac muscle cell and its metabolic conditions during ischemia. Here, we explored the energetic sustainability of cardiomyocytes, using a model for cellular metabolism to predict the levels of ATP following hypoxia. We modeled glycolytic metabolism with a system of coupled ordinary differential equations describing the individual metabolic reactions within the cardiomyocyte over time. Reduced oxygen levels and ATP consumption rates were simulated to characterize metabolite responses to ischemia. By tracking biochemical species within the cell, our model enables prediction of the cell's condition up to the moment of reperfusion. The simulations revealed a distinct transition between energetically sustainable and unsustainable ATP concentrations for various energetic demands. Our model illustrates how even low oxygen concentrations allow the cell to perform essential functions. We found that the oxygen level required for a sustainable level of ATP increases roughly linearly with the ATP consumption rate. An extracellular O2 concentration of ∼0.007 mm could supply basic energy needs in non-beating cardiomyocytes, suggesting that increased collateral circulation may provide an important source of oxygen to sustain the cardiomyocyte during extended ischemia. Our model provides a time-dependent framework for studying various intervention strategies to change the outcome of reperfusion.