Glial perspectives of metabolic states during cerebral hypoxia--calcium regulation and metabolic energy

Cooperation between astrocytes and neurons is a unique interaction between two highly specialized cell types of the brain. Therefore, lack of nutrient supply during ischemia requires tight coordination of metabolism between astrocytes and neurons to keep the brain functions intact. To understand the impact of energy limitation on astrocytes, the functions of astrocytes have to be considered: (i) supplementation of neuronal cells, (ii) modulation of the extracellular milieu, mainly of the glutamate level, and (iii) elimination of reactive oxygen species (ROS). In cultured astrocytes and neurons inhibition of oxidative phosphorylation, using rotenone, was tested. Interestingly, this had only a negligible effect on Ca2+ homeostasis in astrocytes, even in combination with a severe glutamate stress. In contrast, in neurons glutamate in the presence of rotenone induced Ca2+ deregulation. Ca2+ homeostasis is very critical for cell survival. A massive and prolonged Ca2+ rise will lead to deregulation of many processes in such a way that the cells affected can hardly survive. Ca2+ homeostasis depends on the energy-consuming processes, which maintain the steep gradient between intracellular and extracellular Ca2+ concentration. Deprivation of oxygen and glucose during ischemia leads to a depletion of ATP in the brain, due to inhibited glycolytic and mitochondrial activity, whereas energy-consuming processes like ion pumps drain the ATP pools. On the other hand, specific mechanisms can protect brain structures against the massive insult of ischemia. Glycogen, stored in astrocytes, can maintain both neurons and astrocytes alive during short limitation of oxygen and glucose. Moreover, astrocytes can fuel ATP generation by providing lactate for neurons.     

Circadian rhythms and the regulation of metabolic tissue function and energy homeostasis

Circadian oscillators play an indispensable role in the coordination of physiological processes with the cyclic changes in the physical environment. A significant number of recent clinical and molecular studies suggest that circadian biology may play an important role in the regulation of adipose and other metabolic tissue functions. In this discussion, we present the hypothesis that circadian dysfunction may be involved in the pathogenesis of obesity, type 2 diabetes, and the metabolic syndrome.     

An overview of structure,function, and regulation of pyruvate kinases

In the last step of glycolysis Pyruvate kinase catalyzes the irreversible conversion of ADP and phosphoenolpyruvate to ATP and pyruvic acid, both crucial for cellular metabolism. Thus pyruvate kinase plays a key role in controlling the metabolic flux and ATP production. The hallmark of the activity of different pyruvate kinases is their tight modulation by a variety of mechanisms including the use of a large number of physiological allosteric effectors in addition to their homotropic regulation by phosphoenolpyruvate. Binding of effectors signals precise and orchestrated movements in selected areas of the protein structure that alter the catalytic action of these evolutionarily conserved enzymes with remarkably conserved architecture and sequences. While the diverse nature of the allosteric effectors has been discussed in the literature, the structural basis of their regulatory effects is still not well understood because of the lack of data representing conformations in various activation states. Results of recent studies on pyruvate kinases of different families suggest that members of evolutionarily related families follow somewhat conserved allosteric strategies but evolutionarily distant members adopt different strategies. Here we review the structure and allosteric properties of pyruvate kinases of different families for which structural data are available.     

An overview of energy efficiency techniques in cluster computing systems

Two major constraints demand more consideration for energy efficiency in cluster computing: (a) operational costs, and (b) system reliability. Increasing energy efficiency in cluster systems will reduce energy consumption, excess heat, lower operational costs, and improve system reliability. Based on the energy-power relationship, and the fact that energy consumption can be reduced with strategic power management, we focus in this survey on the characteristic of two main power management technologies: (a) static power management (SPM) systems that utilize low-power components to save the energy, and (b) dynamic power management (DPM) systems that utilize software and power-scalable components to optimize the energy consumption. We present the current state of the art in both of the SPM and DPM techniques, citing representative examples. The survey is concluded with a brief discussion and some assumptions about the possible future directions that could be explored to improve the energy efficiency in cluster computing.     

Thioredoxin and metabolic regulation

The regulatory function of thioredoxin, discovered in studies on carbon dioxide assimilation in photosynthesis, was extended to enzymes of related biosynthetic reactions of chloroplasts early on. More recently, thioredoxin was found to perform a range of regulatory functions—from the germination of seeds to the division and development of animal cells. The renaissance in knowledge relating to its activity suggests that thioredoxin will, on the hand, emerge as a principal regulator of fundamental processes in the major forms of life and, on the other, find application in technology and medicine.     

The adipocyte: a model for integration of endocrine and metabolic signaling in energy metabolism regulation

The ability to ensure continuous availability of energy despite highly variable supplies in the environment is a major determinant of the survival of all species. In higher organisms, including mammals, the capacity to efficiently store excess energy as triglycerides in adipocytes, from which stored energy could be rapidly released for use at other sites, was developed. To orchestrate the processes of energy storage and release, highly integrated systems operating on several physiological levels have evolved. The adipocyte is no longer considered a passive bystander, because fat cells actively secrete many members of the cytokine family, such as leptin, tumor necrosis factor-alpha, and interleukin-6, among other cytokine signals, which influence peripheral fuel storage, mobilization, and combustion, as well as energy homeostasis. The existence of a network of adipose tissue signaling pathways, arranged in a hierarchical fashion, constitutes a metabolic repertoire that enables the organism to adapt to a wide range of different metabolic challenges, such as starvation, stress, infection, and short periods of gross energy excess.     

An EMG-driven model applied for predicting metabolic energy consumption during movement

The relationship between mechanical work and metabolic energy cost during movement is not yet clear. Many studies demonstrated the utility of forward-dynamic musculoskeletal models combined with experimental data to address such question. The aim of this study was to evaluate the applicability of a muscle energy expenditure model at whole body level, using an EMG-driven approach.Four participants performed a 5-min squat exercise on unilateral leg press at two different frequencies and two load levels. Data collected were kinematics, EMG, forces and moments under the foot and gas-exchange data. This same task was simulated using a musculoskeletal model, which took EMG and kinematics as inputs and gave muscle forces and muscle energetics as outputs. Model parameters were taken from literature, but maximal isometric muscle force was optimized in order to match predicted joint moments with measured ones. Energy rates predicted by the model were compared with energy consumption measured by the gas-exchange data.Model results on metabolic energy consumption were close to the values obtained through indirect calorimetry. At the higher frequency level, the model underestimated measured energy consumption. This underestimation can be explained with an increase in energy consumption of the non-muscular mass with movement velocity.In conclusion, results obtained in comparing model predictions with experimental data were promising. More research is needed to evaluate this way of computing mechanical and metabolic work.