Evidence map›Paper›PMID 31949214›Full record

ArticleScientific reports2020

Microendoscopy detects altered muscular contractile dynamics in a mouse model of amyotrophic lateral sclerosis.

Xuefeng Chen, Gabriel N Sanchez, Mark J Schnitzer, Scott L Delp

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.4field-weighted citation impact, top 34% of its field
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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. ACS chemical neuroscience · 2021
    Article
  5. 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

4 authors at 2 institutions in 1 country.

Xuefeng ChenDepartment of Mechanical Engineering, Stanford University, Stanford, CA, 94305, USA.
Gabriel N SanchezDepartment of Bioengineering, Stanford University, Stanford, CA, 94305, USA.
Mark J SchnitzerDepartment of Biology, Stanford University, Stanford, CA, 94305, USA. schnitzer@stanford.edu.
Scott L DelpDepartment of Mechanical Engineering, Stanford University, Stanford, CA, 94305, USA. delp@stanford.edu.
Stanford University · USCellecta (United States) · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Amyotrophic lateral sclerosis (ALS) is a fatal disease involving motor neuron degeneration. Effective diagnosis of ALS and quantitative monitoring of its progression are crucial to the success of clinical trials. Second harmonic generation (SHG) microendoscopy is an emerging technology for imaging single motor unit contractions. To assess the potential value of microendoscopy for diagnosing and tracking ALS, we monitored motor unit dynamics in a B6.SOD1G93A mouse model of ALS for several weeks. Prior to overt symptoms, muscle twitch rise and relaxation time constants both increased, consistent with a loss of fast-fatigable motor units. These effects became more pronounced with disease progression, consistent with the death of fast fatigue-resistant motor units and superior survival of slow motor units. From these measurements we constructed a physiological metric that reflects the changing distributions of measured motor unit time constants and effectively diagnoses mice before symptomatic onset and tracks disease state. These results indicate that SHG microendoscopy provides a means for developing a quantitative, physiologic characterization of ALS progression.

Indexed as

EndoscopyMuscle ContractionAmyotrophic Lateral SclerosisAnimalsCell CountDisease Models, AnimalFemaleMiceMotor Neurons

Identifiers

PMID31949214
PMCPMC6965652
OpenAlexW3003089511

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.