Evidence map›Paper›PMID 36995591›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2023

Analyses of Mesenchymal Progenitors in Skeletal Muscle by Fluorescence-Activated Cell Sorting and Tissue Clearing.

Madoka Ikemoto-Uezumi, Tamaki Kurosawa, Keitaro Minato, Akiyoshi Uezumi

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 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 91% 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

4 authors at 1 institution in 1 country.

Madoka Ikemoto-UezumiMuscle Aging and Regenerative Medicine, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan.
Tamaki KurosawaMuscle Aging and Regenerative Medicine, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan.
Keitaro MinatoMuscle Aging and Regenerative Medicine, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan.
Akiyoshi UezumiMuscle Aging and Regenerative Medicine, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan. uezumi@tmig.or.jp.
Tokyo Metropolitan Institute of Gerontology · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mesenchymal progenitors, which are resident progenitor populations residing in skeletal muscle interstitial space, contribute to pathogeneses such as fat infiltration, fibrosis, and heterotopic ossification. In addition to their pathological roles, mesenchymal progenitors have also been shown to play important roles for successful muscle regeneration and homeostatic muscle maintenance. Therefore, detailed and accurate analyses of these progenitors are essential for the research on muscle diseases and health. Here, we describe a method for purification of mesenchymal progenitors based on the expression of PDGFRα, which is a specific and well-established marker for mesenchymal progenitors, using fluorescence-activated cell sorting (FACS). Purified cells can be used in several downstream experiments including cell culture, cell transplantation, and gene expression analysis. We also describe the method for whole-mount 3-dimensional imaging of mesenchymal progenitors by utilizing tissue clearing. The methods described herein provide a powerful platform for studying mesenchymal progenitors in skeletal muscle.

Indexed as

Muscle, SkeletalOssification, HeterotopicCell DifferentiationCell SeparationFlow CytometryHumansCell isolationFACSMesenchymal progenitorsSkeletal muscleTissue clearing

Identifiers

PMID36995591
OpenAlexW4361302146

What OpenQuestion holds

Textmetadata
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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.