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我们能从囊泡释放事件的累积数量中学到什么。

What We Can Learn From Cumulative Numbers of Vesicular Release Events.

作者信息

Miki Takafumi

机构信息

Graduate School of Brain Science, Doshisha University, Kyoto, Japan.

出版信息

Front Cell Neurosci. 2019 Jun 21;13:257. doi: 10.3389/fncel.2019.00257. eCollection 2019.

Abstract

Following action potential invasion in presynaptic terminals, synaptic vesicles are released in a stochastic manner at release sites (docking sites). Since neurotransmission occurs at frequencies up to 1 kHz, the mechanisms underlying consecutive vesicle releases at a docking site during high frequency bursts is a key factor for understanding the role and strength of the synapse. Particularly new vesicle recruitment at the docking site during neuronal activity is thought to be crucial for short-term plasticity. However current studies have not reached a unified docking site model for central synapses. Here I review newly developed analyses that can provide insight into docking site models. Quantal analysis using counts of vesicular release events provide a wealth of information not only to monitor the number of docking sites, but also to distinguish among docking site models. The stochastic properties of cumulative release number during bursts allow us to estimate the total number of releasable vesicles and to deduce the features of vesicle recruitment at docking sites and the change of release probability during bursts. This analytical method may contribute to a comprehensive understanding of release/replenishment mechanisms at a docking site.

摘要

在突触前终末动作电位传入后,突触小泡在释放位点(停靠位点)以随机方式释放。由于神经传递的频率高达1kHz,高频爆发期间停靠位点连续小泡释放的潜在机制是理解突触作用和强度的关键因素。特别是在神经元活动期间停靠位点上新的小泡募集被认为对短期可塑性至关重要。然而,目前的研究尚未达成关于中枢突触的统一停靠位点模型。在此,我回顾了新开发的分析方法,这些方法能够为停靠位点模型提供见解。使用小泡释放事件计数的量子分析不仅提供了大量信息以监测停靠位点的数量,还能区分不同的停靠位点模型。爆发期间累积释放数量的随机特性使我们能够估计可释放小泡的总数,并推断停靠位点上小泡募集的特征以及爆发期间释放概率的变化。这种分析方法可能有助于全面理解停靠位点的释放/补充机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ee1/6598442/0f74bcd93070/fncel-13-00257-g001.jpg

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