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The paper presents a methodology for using computational neurogenetic modelling (CNGM) to bring new original insights into how genes influence the dynamics of brain neural networks. CNGM is a novel computational approach to brain neural network modelling that integrates dynamic gene networks with artificial neural network model (ANN). Interaction of genes in neurons affects the dynamics of the whole ANN model through neuronal parameters, which are no longer constant but change as a function of gene expression. Through optimization of interactions within the internal gene regulatory network (GRN), initial gene/protein expression values and ANN parameters, particular target states of the neural network behaviour can be achieved, and statistics about gene interactions can be extracted. In such a way, we have obtained an abstract GRN that contains predictions about particular gene interactions in neurons for subunit genes of AMPA, GABA_A and NMDA neuro-receptors. The extent of sequence conservation for 20 subunit proteins of all these receptors was analysed using standard bioinformatics multiple alignment procedures. We have observed abundance of conserved residues but the most interesting observation has been the consistent conservation of phenylalanine (F at position 269) and leucine (L at position 353) in all 20 proteins with no mutations. We hypothesise that these regions can be the basis for mutual interactions. Existing knowledge on evolutionary linkage of their protein families and analysis at molecular level indicate that the expression of these individual subunits should be coordinated, which provides the biological justification for our optimized GRN.

In the brain, endoplasmic reticulum (ER) stress results in synaptic dysfunction and eventually leads to neurodegeneration. Allomyrina dichotoma larvae are a Chinese ethnomedicine and are widely used in East Asia. In the present study, we investigated the ability of ethanol extract of A. dichotoma larvae (ADE) to improve synaptic structure and function by activating unfolded protein response (UPR) under ER stress in animal and neuron culture models. ER stress was induced in obese mice fed a high fat diet (HFD) or by treating dissociated cultures of rat embryonic (E19) hippocampal neurons with tunicamycin (TM). Western blot and real-time or conventional RT-PCR were performed to analyze the expressions of ER stress marker proteins. In dissociated hippocampal cultures, immunocytochemistry was performed for synaptic proteins, and cultures were stained with styryl dye FM1-43 to assess presynaptic activities. In HFD-fed obese mice, ADE efficiently reduced the expressions of ER stress markers, such as, xbp-1, chop, atf4, erdi4, and eIf2a, and those of the ER chaperone/foldases Bip/grp78, Ero-1l, and PDI. Unconventionally spliced xbp-1s mRNA was not detected. In primary rat hippocampal cultures under ER stress, ADE significantly lowered the nuclear expression of CHOP, inhibited the downregulations of postsynaptic proteins, such as, GluN2A, GluN2B, and PSD-95, and maintained the pool size of recycling presynaptic vesicles. The study shows that ADE potently suppressed the induction of ER stress and maintained the structure and function of hippocampal neurons, and suggests that ADE is a potentially valuable food supplement and preventive therapeutic for ER stress-related nervous disorders.

The term synaptic plasticity describes the ability of excitatory synapses to undergo activity-driven long-lasting changes in the efficacy of basal synaptic transmission. This change may be expressed as a long-term potentiation (LTP) or as a long-term depression (LTD). Metaplasticity is a higher-order form of synaptic plasticity that regulates the expression of both LTP and LTD through processes that are initiated by cellular activity that precedes a later bout of plasticity-inducing synaptic activity. Activation by prior synaptic activity and later expression as a facilitation or inhibition of activity-dependent synaptic plasticity are fundamental properties of metaplasticity. The intracellular mechanisms which support metaplasticity appear to be closely linked to those of synaptic plasticity, hence there are significant technical challenges to overcome in order to elucidate those mechanisms specific to metaplasticity. This review will examine the progress in the characterization of metaplasticity over the last decade or so with a focus on findings gained using electrophysiological techniques. It will look at the techniques applied, the brain regions investigated and the knowledge gained from the application of a wide range of protocols designed to examine the influence of varied forms of prior synaptic activity on later, activity-induced, synaptic plasticity.