ArticleMethods in molecular biology (Clifton, N.J.)2023
Quantification of Muscle Satellite Stem Cell Divisions by High-Content Analysis.
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. Cited by 2 papers.
What it found
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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.
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.
Who cites it
2 citing papers in PubMed.
- Wnt7a is required for regeneration of dystrophic skeletal muscle.Skeletal muscle · 2024Article
- Wnt7a is Required for Regeneration of Dystrophic Skeletal Muscle.bioRxiv : the preprint server for biology · 2024Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
High-content screening is commonly performed on 2D cultured cells, which is high throughput but has low biological relevance. In contrast, single myofiber culture assay preserves the satellite cell niche between the basal lamina and sarcolemma and consequently has high biological relevance but is low throughput. We describe here a high-content screening method that utilizes single myofiber culture that addresses the caveats of both techniques. Our method utilizes the transgenic reporter allele Myf5-Cre:R26R-eYFP to differentiate stem and committed cells within a dividing couplet that can be quantified by high-content throughput immunodetection and bioinformatic analysis.
Indexed as
Identifiers
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Registered trials
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.