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通过对安培电流尖峰进行建模来揭示囊泡胞吐释放事件背后的物理化学和生物学过程的本质。

Unraveling the nature of physicochemical and biological processes underlying vesicular exocytotic release events through modeling of amperometric current spikes.

作者信息

Oleinick Alexander, Svir Irina, Amatore Christian

机构信息

Chimie Physique et Chimie du Vivant, Département de Chimie, Ecole Normale Supérieure, PSL Université, Sorbonne Université, CNRS, Paris, France.

State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, People's Republic of China.

出版信息

QRB Discov. 2025 Jul 24;6:e21. doi: 10.1017/qrd.2025.10010. eCollection 2025.

Abstract

This work offers a comprehensive approach to understanding the phenomena underlying vesicular exocytosis, a process involved in vital functions of living organisms such as neuronal and neuroendocrine signaling. The kinetics of release of most neuromediators that modulate these functions in various ways can be efficiently monitored using single-cell amperometry (SCA). Indeed, SCA at ultramicro- or nanoelectrodes provides the necessary temporal, flux, and nanoscale resolution to accurately report on the shape and intensity of single exocytotic spikes. Rather than characterizing amperometric spikes using standard descriptive parameters (e.g., amplitude and half-width), however, this study summarizes a modeling approach based on the underlying biology and physical chemistry of single exocytotic events. This approach provides deeper insights into intravesicular phenomena that control vesicular release dynamics. The ensuing model's intrinsic parsimony makes it computationally efficient and friendly, enabling the processing of large amperometric traces to gain statistically significant insights.

摘要

这项工作提供了一种全面的方法来理解囊泡胞吐作用背后的现象,囊泡胞吐作用是一种涉及生物体重要功能(如神经元和神经内分泌信号传导)的过程。使用单细胞安培法(SCA)可以有效地监测以各种方式调节这些功能的大多数神经介质的释放动力学。实际上,超微电极或纳米电极上的SCA提供了必要的时间、通量和纳米级分辨率,以准确报告单个胞吐尖峰的形状和强度。然而,本研究并非使用标准描述参数(如幅度和半高宽)来表征安培尖峰,而是总结了一种基于单个胞吐事件的基础生物学和物理化学的建模方法。这种方法能更深入地了解控制囊泡释放动力学的囊泡内现象。由此产生的模型具有内在的简洁性,使其在计算上高效且友好,能够处理大量的安培曲线以获得具有统计学意义的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8415/12418276/d8c8d562ae64/S2633289225100100_fig1.jpg

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