Search

In order to explore short-term facilitation of the Schaffer collateral to CA1 synapse in mouse hippocampal brain slices, we measured the time course of the decay of the peak amplitude of successive EPSCs during progressive MK-801-dependent block (PMDB) of NMDAR responses to paired (R1 and R2) stimuli. We made the unexpected observation that the R2 response exhibited a slower PMDB decay constant than that of the R1 response. This indicated that the facilitated R2 response engages release sites with NMDARs that are protected from opening and consequent MK-801 block during the basal R1 response. We then utilized conditions that affect synaptic glutamate distribution to dissect the components of the distinct PMDB decay constants of the first and second of paired pulses. While extra-synaptic NMDARs and glutamate transporters appear to play only minor roles in the differences of the PMDB decay constant, we showed important roles for the R1 response itself and for glutamate diffusion in determining the PMDB decay constant of R2. We used a simple computational model with realistic parameters that allowed us to predict the time course of R2 decay based on the R1 decay time course.

Paired pulse facilitation (PPF) is a form of short-term synaptic plasticity that results from an interaction of residual presynaptic Ca(2+) ([Ca(2+)](res)), number of release-competent vesicles, and the sensitivity of the vesicle release mechanisms to Ca(2+). While PPF is predominant at hippocampal Schaffer collateral-CA1 (SC-CA1) synapses, facilitation is greater in adult mice (designated Tkneo) that over express an isoform of the plasma membrane-targeted SNARE protein, SNAP-25a, which is normally predominantly expressed in juvenile animals. SNAP-25 is essential for action potential-dependent neuroexocytosis, yet the significance of the shift between the alternatively spliced variants SNAP-25a and SNAP-25b is not fully understood. This alteration of a key component of the protein machinery required for neurotransmitter release in Tkneo mice, therefore, provides a useful tool to further investigate presynaptic mechanisms that influence short-term plasticity. To explore this link between SNAP-25 and PPF, we simultaneously measured postsynaptic potentials and presynaptic [Ca(2+)](res) during paired-pulses in adult Tkneo, heterozygote null (HET), and wild type (WT) mice. We demonstrate that enhanced PPF is maintained at mature hippocampal synapses of Tkneo mice that predominantly express SNAP-25a, and that [Ca(2+)](res) kinetics are altered at synapses of Tkneo and HET mice, both of which exhibit reduced levels of total SNAP-25 expression. To evaluate the role of SNAP-25 in short-term plasticity and [Ca(2+)](res) regulation, we applied a vesicular release probability model for neurotransmission. Our results suggest that the isoform expression and total level of SNAP-25 affect both [Ca(2+)](res) dynamics and the ability of releasable vesicles to enter into a facilitated state.

Communication infrastructures are rapidly evolving to support 5G enabling lower latency, high reliability, and scalability of the network and of the service provisioning. An important element of the 5G vision is Multi-access Edge Computing (MEC), that leverages the availability of powerful and low-cost middle boxes, i.e., MEC nodes, statically deployed at suitable edges of the network to extend the centralized cloud backbone. At the same time, after almost a decade of research, Mobile CrowdSensing (MCS) has established the technology able to collect sensing data on the environment by using personal devices, usually smartphones, as powerful sensing-and-communication platforms. Even though, mutual benefits due to the integration of MEC and Mobile CrowdSensing (MCS) are still largely unexplored. In this paper, we address and analyze the potential of the synergic use of MCS and MEC by thoroughly assessing various strategies for the selection of both traditional Fixed MEC (FMEC) edges as well as human-enabled Mobile MEC (M2EC) edges to support the collection of mobile CrowdSensing data. Collected results quantitatively show the effectiveness of the proposed optimization strategies in elastically scaling the load at edge nodes according to runtime provisioning needs.