Evidence map›Paper›PMID 38526119›Full record

ArticleJournal of visualized experiments : JoVE2024

Stimulated Single Fiber Electromyography (SFEMG) for Assessing Neuromuscular Junction Transmission in Rodent Models.

Arsh Ketabforoush, Meifang Wang, W David Arnold

Abstract readVideo-Audio Media
In one paragraph

Article in Journal of visualized experiments : JoVE, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

3 authors.

Arsh KetabforoushNextGen Precision Health, University of Missouri.
Meifang WangNextGen Precision Health, University of Missouri.
W David ArnoldNextGen Precision Health, University of Missouri; Department of Physical Medicine and Rehabilitation, University of Missouri; Department of Neurology, University of Missouri; Department of Medical Pharmacology and Physiology, University of Missouri; wdavidarnold@health.missouri.edu.

Funding

Neuronal mechanisms involved in aging and ADR01AG067758 · NIA · OHIO UNIVERSITY ATHENS · PI ARNOLD, WILLIAM DAVID, CLARK, BRIAN C · 2021 to 2025
$4.1M
Neural mechanisms of age-related weaknessR01AG078129 · NIA · OHIO UNIVERSITY ATHENS · PI William David Arnold, Brian C Clark · 2023 to 2026
$2.5M
NIA NIH HHS R01 AG067758NIA NIH HHS R01 AG078129
6 · The paper itself

Abstract

As the final connection between the nervous system and muscle, transmission at the neuromuscular junction (NMJ) is crucial for normal motor function. Single fiber electromyography (SFEMG) is a clinically relevant and sensitive technique that measures single muscle fiber action potential responses during voluntary contractions or nerve stimulations to assess NMJ transmission. The assessment and quantification of NMJ transmission involves two parameters: jitter and blocking. Jitter refers to the variability in timing (latency) between consecutive single-fiber action potentials (SFAPs). Blocking signifies the failure of NMJ transmission to initiate an SFAP response. Although SFEMG is a well-established and sensitive test in clinical settings, its application in preclinical research has been relatively infrequent. This report outlines the steps and criteria employed in performing stimulated SFEMG to quantify jitter and blocking in rodent models. This technique can be used in preclinical and clinical studies to gain insights into NMJ function in the context of health, aging, and disease.

Indexed as

Muscle Fibers, SkeletalRodentiaAnimalsElectromyographyNeuromuscular JunctionSynaptic Transmission

Identifiers

PMID38526119
PMCPMC13197892

What OpenQuestion holds

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Registered trials

None linked

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.