Glucocorticoid receptor and protein/RNA synthesis-dependent mechanisms underlie the control of synaptic plasticity by stress

Learning and memory are exquisitely sensitive to behavioral stress, but the underlying mechanisms are still poorly understood. Because activity-dependent persistent changes in synaptic strength are believed to mediate memory processes in brain areas such as the hippocampus we have examined the means by which stress affects synaptic plasticity in the CA1 region of the hippocampus of anesthetized rats, Inescapable behavioral stress (placement on an elevated platform for 30 min) switched the direction of plasticity, favoring low frequency stimulation-induced decreases in synaptic transmission (long-term depression, LTD), and opposing the induction of long-term potentiation by high frequency stimulation, We have discovered that glucocorticoid receptor activation mediates these effects of stress on LTD and longterm potentiation in a protein synthesis-dependent manner because they were prevented by the glucocorticoid receptor antagonist RU 38486 and the protein synthesis inhibitor emetine. Consistent with this, the ability of exogenously applied corticosterone in non-stressed rats to mimic the effects of stress on synaptic plasticity was also blocked by these agents, The enablement of low frequency stimulation-induced LTD by both stress and exogenous corticosterone was also blocked by the transcription inhibitor actinomycin D, Thus, naturally occurring synaptic plasticity is liable to be reversed in stressful situations via glucocorticoid receptor activation and mechanisms dependent on the synthesis of new protein and RNA, This indicates that the modulation of hippocampus-mediated learning by acute inescapable stress requires glucocorticoid receptor-dependent initiation of transcription and translation.

Coupling between NMDA receptor and acid-sensing ion channel contributes to ischemic neuronal death

Acid-sensing ion channels (ASICs) composed of ASIC1a subunit exhibit a high Ca2+ permeability and play important roles in synaptic plasticity and acid-induced cell death. Here, we show that ischemia enhances ASIC currents through the phosphorylation at Ser478 and Ser479 of ASIC1a, leading to exacerbated ischemic cell death. The phosphorylation is catalyzed by Ca2+/calmodulin-dependent protein kinase II (CaMKII) activity, as a result of activation of NR2B-containing N-methyl-D-aspartate subtype of glutamate receptors (NMDARs) during ischemia. Furthermore, NR2B-specific antagonist, CaMKII inhibitor, or overexpression of mutated form of ASIC1a with Ser478 or Ser479 replaced by alanine (ASICla-S478A, ASIC1a-S479A) in cultured hippocampal neurons prevented ischemia-induced enhancement of ASIC currents, cytoplasmic Ca2+ elevation, as well as neuronal death. Thus, NMDAR-CaMKII cascade is functionally coupled to ASICs and contributes to acidotoxicity during ischemia. Specific blockade of NMDAR/CaMKII-ASIC coupling may reduce neuronal death after ischemia and other pathological conditions involving excessive glutamate release and acidosis.

N-methyl-D-aspartate receptor-dependent long-term potentiation in CA1 region affects synaptic expression of glutamate receptor subunits and associated proteins in the whole hippocampus

Long term potentiation in hippocampus, evoked by high-frequency stimulation, is mediated by two major glutamate receptor subtypes, alpha-amino-3-hydroxyl-5-methyl-4-isoxazole propionate receptors and N-methyl-D-aspartate receptors. Receptor subunit compos

Glycine receptor activation regulates short-term plasticity in CA1 area of hippocampal slices of rats

Functional glycine receptors (GlyRs) are enriched in the hippocampus, but their roles in synaptic transmission are unclear. In this study, we examined the effect of GlyR activation on paired-pulse stimulation of the whole-cell postsynaptic currents (PSCs)

Glycine uptake regulates hippocampal network activity via glycine receptor-mediated tonic inhibition

Functional glycine receptors (GlyRs) are enriched in the hippocampus, but their role in hippocampal function remains unclear. Since the concentration of ambient glycine is determined by the presence of powerful glycine transporter (GlyT), we blocked the r

Phase noise analysis of a mechanical autonomous impact oscillator with a MEMS resonator

In this paper, phase noise analysis of a mechanical autonomous impact oscillator with a MEMS resonator is performed. Since the circuit considered belongs to the class of hybrid systems, methods based on the variational model for the evaluation of either phase noise or steady state solutions cannot be directly applied. As a matter of fact, the monodromy matrix is not defined at impact events in these systems. By introducing saltation matrices, this limit is overcome and the aforementioned methods are extended. In particular, the unified theory developed by Demir is used to analyze the phase noise after evaluating the asymptotically stable periodic solution of the system by resorting to the shooting method. Numerical results are presented to show how noise sources affect the phase noise performances. © 2011 IEEE.

Improved jet noise modeling using a new time-scale.

To calculate the noise emanating from a turbulent flow using an acoustic analogy knowledge concerning the unsteady characteristics of the turbulence is required. Specifically, the form of the turbulent correlation tensor together with various time and length-scales are needed. However, if a Reynolds Averaged Navier-Stores calculation is used as the starting point then one can only obtain steady characteristics of the flow and it is necessary to model the unsteady behavior in some way. While there has been considerable attention given to the correct way to model the form of the correlation tensor less attention has been given to the underlying physics that dictate the proper choice of time-scale. In this paper the authors recognize that there are several time dependent processes occurring within a turbulent flow and propose a new way of obtaining the time-scale. Isothermal single-stream flow jets with Mach numbers 0.75 and 0.90 have been chosen for the present study. The Mani-Gliebe-Balsa-Khavaran method has been used for prediction of noise at different angles, and there is good agreement between the noise predictions and observations. Furthermore, the new time-scale has an inherent frequency dependency that arises naturally from the underlying physics, thus avoiding supplementary mathematical enhancements needed in previous modeling.