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      Brain Glucose Metabolism: Integration of Energetics with Function

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      Physiological Reviews

      American Physiological Society

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          Most cited references 678

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          An energy budget for signaling in the grey matter of the brain.

          Anatomic and physiologic data are used to analyze the energy expenditure on different components of excitatory signaling in the grey matter of rodent brain. Action potentials and postsynaptic effects of glutamate are predicted to consume much of the energy (47% and 34%, respectively), with the resting potential consuming a smaller amount (13%), and glutamate recycling using only 3%. Energy usage depends strongly on action potential rate--an increase in activity of 1 action potential/cortical neuron/s will raise oxygen consumption by 145 mL/100 g grey matter/h. The energy expended on signaling is a large fraction of the total energy used by the brain; this favors the use of energy efficient neural codes and wiring patterns. Our estimates of energy usage predict the use of distributed codes, with
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            Molecular anatomy of a trafficking organelle.

            Membrane traffic in eukaryotic cells involves transport of vesicles that bud from a donor compartment and fuse with an acceptor compartment. Common principles of budding and fusion have emerged, and many of the proteins involved in these events are now known. However, a detailed picture of an entire trafficking organelle is not yet available. Using synaptic vesicles as a model, we have now determined the protein and lipid composition; measured vesicle size, density, and mass; calculated the average protein and lipid mass per vesicle; and determined the copy number of more than a dozen major constituents. A model has been constructed that integrates all quantitative data and includes structural models of abundant proteins. Synaptic vesicles are dominated by proteins, possess a surprising diversity of trafficking proteins, and, with the exception of the V-ATPase that is present in only one to two copies, contain numerous copies of proteins essential for membrane traffic and neurotransmitter uptake.
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              Astrocyte-neuron lactate transport is required for long-term memory formation.

              We report that, in the rat hippocampus, learning leads to a significant increase in extracellular lactate levels that derive from glycogen, an energy reserve selectively localized in astrocytes. Astrocytic glycogen breakdown and lactate release are essential for long-term but not short-term memory formation, and for the maintenance of long-term potentiation (LTP) of synaptic strength elicited in vivo. Disrupting the expression of the astrocytic lactate transporters monocarboxylate transporter 4 (MCT4) or MCT1 causes amnesia, which, like LTP impairment, is rescued by L-lactate but not equicaloric glucose. Disrupting the expression of the neuronal lactate transporter MCT2 also leads to amnesia that is unaffected by either L-lactate or glucose, suggesting that lactate import into neurons is necessary for long-term memory. Glycogenolysis and astrocytic lactate transporters are also critical for the induction of molecular changes required for memory formation, including the induction of phospho-CREB, Arc, and phospho-cofilin. We conclude that astrocyte-neuron lactate transport is required for long-term memory formation. Copyright © 2011 Elsevier Inc. All rights reserved.
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                Author and article information

                Journal
                Physiological Reviews
                Physiological Reviews
                American Physiological Society
                0031-9333
                1522-1210
                January 2019
                January 2019
                : 99
                : 1
                : 949-1045
                Affiliations
                [1 ]Department of Neurology, University of Arkansas for Medical Sciences, Little Rock, Arkansas; and Department of Cell Biology and Physiology, University of New Mexico, Albuquerque, New Mexico
                Article
                10.1152/physrev.00062.2017
                © 2019

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