Evidence map›Paper›PMID 37358301›Full record

ArticleJournal of visualized experiments : JoVE2023

Decellularization-Based Quantification of Skeletal Muscle Fatty Infiltration.

Jacob C Parson, Nicole K Biltz, Gretchen A Meyer

Open access · greenAbstract readVideo-Audio Media
In one paragraph

Article in Journal of visualized experiments : JoVE, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact, top 75% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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 at 1 institution in 1 country.

Jacob C ParsonProgram in Physical Therapy, Washington University in St. Louis.
Nicole K BiltzProgram in Physical Therapy, Washington University in St. Louis.
Gretchen A MeyerProgram in Physical Therapy, Washington University in St. Louis; Departments of Neurology, Orthopaedic Surgery and Biomedical Engineering, Washington University in St. Louis; meyerg@wustl.edu.
Washington University in St. Louis · US

Funding

Promoting Muscle Regeneration through Adipose SignalingR01AR075773 · NIAMS · WASHINGTON UNIVERSITY · PI MEYER, GRETCHEN A · 2019 to 2023
$1.7M
NIAMS NIH HHS R01 AR075773
6 · The paper itself

Abstract

Fatty infiltration is the accumulation of adipocytes between myofibers in skeletal muscle and is a prominent feature of many myopathies, metabolic disorders, and dystrophies. Clinically in human populations, fatty infiltration is assessed using noninvasive methods, including computed tomography (CT), magnetic resonance imaging (MRI), and ultrasound (US). Although some studies have used CT or MRI to quantify fatty infiltration in mouse muscle, costs and insufficient spatial resolution remain challenging. Other small animal methods utilize histology to visualize individual adipocytes; however, this methodology suffers from sampling bias in heterogeneous pathology. This protocol describes the methodology to qualitatively view and quantitatively measure fatty infiltration comprehensively throughout intact mouse muscle and at the level of individual adipocytes using decellularization. The protocol is not limited to specific muscles or specific species and can be extended to human biopsy. Additionally, gross qualitative and quantitative assessments can be made with standard laboratory equipment for little cost, making this procedure more accessible across research laboratories.

Indexed as

Muscle, SkeletalMuscular DiseasesAdipocytesAnimalsHumansMagnetic Resonance ImagingMiceTomography, X-Ray Computed

Identifiers

PMID37358301
PMCPMC10837739
OpenAlexW4379979464

What OpenQuestion holds

Textmetadata
LicenceTDM
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.