Evidence map›Paper›PMID 33564025›Full record

ArticleScientific reports2021

Distinguishing synaptic vesicle precursor navigation of microtubule ends with a single rate constant model.

M W Gramlich, S Balseiro-Gómez, S M Ali Tabei, M Parkes, S Yogev

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. rTg(TauFrontiers in synaptic neuroscience · 2022
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

M W GramlichDepartment of Physics, Auburn University, Auburn, AL, USA. mwg0016@auburn.edu.
S Balseiro-GómezDepartments of Neuroscience and Cell Biology, Yale School of Medicine, New Haven, CT, USA.
S M Ali TabeiDepartment of Physics, University of Northern Iowa, Cedar Falls, IA, USA.
M ParkesDepartment of Physics, Auburn University, Auburn, AL, USA.
S YogevDepartments of Neuroscience and Cell Biology, Yale School of Medicine, New Haven, CT, USA.

Funding

Local regulation of neuronal microtubules and synaptic cargoR01NS114400 · NINDS · YALE UNIVERSITY · PI YOGEV, SHAUL · 2020 to 2024
$2.0M
NINDS NIH HHS R01 NS114400
6 · The paper itself

Abstract

Axonal motor driven cargo utilizes the microtubule cytoskeleton in order to direct cargo, such as synaptic vesicle precursors (SVP), to where they are needed. This transport requires vesicles to travel up to microns in distance. It has recently been observed that finite microtubule lengths can act as roadblocks inhibiting SVP and increasing the time required for transport. SVPs reach the end of a microtubule and pause until they can navigate to a neighboring microtubule in order to continue transport. The mechanism(s) by which axonal SVPs navigate the end of a microtubule in order to continue mobility is unknown. In this manuscript we model experimentally observed vesicle pausing at microtubule ends in C. elegans. We show that a single rate-constant model reproduces the time SVPs pause at MT-ends. This model is based on the time an SVP must detach from its current microtubule and re-attach to a neighboring microtubule. We show that vesicle pause times are different for anterograde and retrograde motion, suggesting that vesicles utilize different proteins at plus and minus end sites. Last, we show that vesicles do not likely utilize a tug-of-war like mechanism and reverse direction in order to navigate microtubule ends.

Indexed as

Models, NeurologicalAnimalsCaenorhabditis elegansMicrotubulesSynaptic Vesicles

Identifiers

PMID33564025
PMCPMC7873188

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.