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Several studies have shown that epileptic seizures increase hippocampal neurogenesis in the adult. However, the mechanism underlying increased neurogenesis after seizures remains largely unknown. Neurogenesis occurs in the subgranular zone (SGZ) of the hippocampus in the adult brain, although an understanding of why it actively occurs in this region has remained elusive. A high level of vesicular zinc is localized in the presynaptic terminals of the SGZ. Previously, we demonstrated that a possible correlation may exist between synaptic zinc localization and high rates of neurogenesis in this area after hypoglycemia. Using a lithium-pilocarpine model, we tested our hypothesis that zinc plays a key role in modulating hippocampal neurogenesis after seizure. Then, we injected the zinc chelator, clioquinol (CQ, 30 mg/kg), into the intraperitoneal space to reduce brain zinc availability. Neuronal death was detected with Fluoro Jade-B and NeuN staining to determine whether CQ has neuroprotective effects after seizure. The total number of degenerating and live neurons was similar in vehicle and in CQ treated rats at 1 week after seizure. Neurogenesis was evaluated using BrdU, Ki67 and doublecortin (DCX) immunostaining 1 week after seizure. The number of BrdU, Ki67 and DCX positive cell was increased after seizure. However, the number of BrdU, Ki67 and DCX positive cells was significantly decreased by CQ treatment. Intracellular zinc chelator, N,N,N0,N-Tetrakis (2-pyridylmethyl) ethylenediamine (TPEN), also reduced seizure-induced neurogenesis in the hippocampus. The present study shows that zinc chelation does not prevent neurodegeneration but does reduce seizure-induced progenitor cell proliferation and neurogenesis. Therefore, this study suggests that zinc has an essential role for modulating hippocampal neurogenesis after seizure.
Pubmed ID: 23119054
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NEURON is a simulation environment for modeling individual neurons and networks of neurons. It provides tools for conveniently building, managing, and using models in a way that is numerically sound and computationally efficient. It is particularly well-suited to problems that are closely linked to experimental data, especially those that involve cells with complex anatomical and biophysical properties. NEURON has benefited from judicious revision and selective enhancement, guided by feedback from the growing number of neuroscientists who have used it to incorporate empirically-based modeling into their research strategies. NEURON's computational engine employs special algorithms that achieve high efficiency by exploiting the structure of the equations that describe neuronal properties. It has functions that are tailored for conveniently controlling simulations, and presenting the results of real neurophysiological problems graphically in ways that are quickly and intuitively grasped. Instead of forcing users to reformulate their conceptual models to fit the requirements of a general purpose simulator, NEURON is designed to let them deal directly with familiar neuroscience concepts. Consequently, users can think in terms of the biophysical properties of membrane and cytoplasm, the branched architecture of neurons, and the effects of synaptic communication between cells. * helps users focus on important biological issues rather than purely computational concerns * has a convenient user interface * has a user-extendable library of biophysical mechanisms * has many enhancements for efficient network modeling * offers customizable initialization and simulation flow control * is widely used in neuroscience research by experimentalists and theoreticians * is well-documented and actively supported * is free, open source, and runs on (almost) everything
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