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Cited by 366

The DOI matches its Crossref record; 41 of the 41 references it cites were found in a registry or an index.

The Dynamic Control of Kiss-And-Run and Vesicular Reuse Probed with Single Nanoparticles

Open access
Zhang, Qi, Li, Yulong, Tsien, Richard W.·2009·Science

Abstract

Vesicular secretion of neurotransmitter is essential for neuronal communication. Kiss-and-run is a mode of membrane fusion and retrieval without the full collapse of the vesicle into the plasma membrane and de novo regeneration. The importance of kiss-and-run during efficient neurotransmission has remained in doubt. We developed an approach for loading individual synaptic vesicles with single quantum dots. Their size and pH-dependent photoluminescence change allowed us to distinguish kiss-and-run from full-collapse fusion and to track single vesicles through multiple rounds of kiss-and-run and reuse, without perturbing vesicle cycling. Kiss-and-run dominated at the beginning of stimulus trains, reflecting the preference of vesicles with high release probability. Its incidence was increased by rapid firing, a response appropriate to shape the kinetics of neurotransmission during a wide range of firing patterns.

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Crossref · 10.1126/science.1167373

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Metadata

Authors
Zhang, Q., Li, Y., & Tsien, R. W.
Venue
Science
Published
2009-03-13
Volume
323
Issue
5920
Pages
1448-1453
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W2006766519
Cited by
366
References
41
FWCI
18.05
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: The Dynamic Control of Kiss-And-Run and Vesicular Reuse Probed with Single Nanoparticles. https://app.cochat.ai/papers/10.1126/science.1167373
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Zhang, Q., Li, Y., & Tsien, R. W. (2009). The Dynamic Control of Kiss-And-Run and Vesicular Reuse Probed with Single Nanoparticles. Science. https://doi.org/10.1126/science.1167373

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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.