A Dynamic Model of Interactions of Ca^(2+), Calmodulin, and Catalytic Subunits of Ca^(2+)/Calmodulin-Dependent Protein Kinase II

During the acquisition of memories, influx of Ca^(2+) into the postsynaptic spine through the pores of activated N-methyl-D-aspartate-type glutamate receptors triggers processes that change the strength of excitatory synapses. The pattern of Ca^(2+) influx during the first few seconds of activity is interpreted within the Ca^(2+)-dependent signaling network such that synaptic strength is eventually either potentiated or depressed. Many of the critical signaling enzymes that control synaptic plasticity, including Ca^(2+)/calmodulin-dependent protein kinase II (CaMKII), are regulated by calmodulin, a small protein that can bind up to 4 Ca^(2+) ions. As a first step toward clarifying how the Ca^(2+)-signaling network decides between potentiation or depression, we have created a kinetic model of the interactions of Ca^(2+), calmodulin, and CaMKII that represents our best understanding of the dynamics of these interactions under conditions that resemble those in a postsynaptic spine. We constrained parameters of the model from data in the literature, or from our own measurements, and then predicted time courses of activation and autophosphorylation of CaMKII under a variety of conditions. Simulations showed that species of calmodulin with fewer than four bound Ca^(2+) play a significant role in activation of CaMKII in the physiological regime, supporting the notion that processing ofCa^(2+) signals in a spine involves competition among target enzymes for binding to unsaturated species of CaM in an environment in which the concentration of Ca^(2+) is fluctuating rapidly. Indeed, we showed that dependence of activation on the frequency of Ca^(2+) transients arises from the kinetics of interaction of fluctuating Ca^(2+) with calmodulin/CaMKII complexes. We used parameter sensitivity analysis to identify which parameters will be most beneficial to measure more carefully to improve the accuracy of predictions. This model provides a quantitative base from which to build more complex dynamic models of postsynaptic signal transduction during learning

Investigation on Mechanical, Tribological and Microstructural properties of Al-Mg-Si-T6/SiC/Muscovite-hybrid metal-matrix composites for high strength applications

The wide range of aluminium variants (alloys and composites) has made it an important material for aviation, automotive components, auto-transmission locomotive section units, S.C.U.B.A. tanks, ship, vessels, submarines fabrication and design etc. regardless of the fact that the aluminium alloys were being utilized in myriads of sectors owing to its exceptional superior and versatile functional characteristics, the property such as wear-resistant ought to be enhanced in order to further prolong diverse spectrum of applications. An aluminium alloy having lower hardness and tensile strength has been incorporated with silicon carbide that drastically strengthens the properties. This study involves fabrication of aluminium silicon carbide with muscovite/hydrated aluminium potassium silicate/aluminosilicate in stir casting method to obtain a hybrid metal matrix composite. Maintaining a constant amount of aluminium and silicon carbide, muscovite or hydrated aluminium potassium silicate is varied to obtain three distinctive compositions of (Al/SiC/muscovite) composites. The mechanical characteristics like tensile-strength, flexural-strength, toughness, hardness, scratch adhesion, percent-porosity and density were studied. The dispersion of muscovite and silicon carbide particles were observed by viewing the microstructure photographs obtained using optical microscopy and Scanning Electron Microscope (SEM). EDAX analysis affirms the presence of reinforcing constituents in Al–Mg–Si–T6 alloy matrix. A drum type wear apparatus was utilized to evaluate the percentage of wear-loss in different compositions using different loads and it was found that the wear-loss decreases linearly as the muscovite percentage was increased

Genetic deletion of fibroblast growth factor 14 recapitulates phenotypic alterations underlying cognitive impairment associated with schizophrenia

Cognitive processing is highly dependent on the functional integrity of gamma-amino-butyric acid (GABA) interneurons in the brain. These cells regulate excitability and synaptic plasticity of principal neurons balancing the excitatory/inhibitory tone of cortical networks. Reduced function of parvalbumin (PV) interneurons and disruption of GABAergic synapses in the cortical circuitry result in desynchronized network activity associated with cognitive impairment across many psychiatric disorders, including schizophrenia. However, the mechanisms underlying these complex phenotypes are still poorly understood. Here we show that in animal models, genetic deletion of fibroblast growth factor 14 (Fgf14), a regulator of neuronal excitability and synaptic transmission, leads to loss of PV interneurons in the CA1 hippocampal region, a critical area for cognitive function. Strikingly, this cellular phenotype associates with decreased expression of glutamic acid decarboxylase 67 (GAD67) and vesicular GABA transporter (VGAT) and also coincides with disrupted CA1 inhibitory circuitry, reduced in vivo gamma frequency oscillations and impaired working memory. Bioinformatics analysis of schizophrenia transcriptomics revealed functional co-clustering of FGF14 and genes enriched within the GABAergic pathway along with correlatively decreased expression of FGF14, PVALB, GAD67 and VGAT in the disease context. These results indicate that Fgf14(-/-) mice recapitulate salient molecular, cellular, functional and behavioral features associated with human cognitive impairment, and FGF14 loss of function might be associated with the biology of complex brain disorders such as schizophrenia