Human Skeletal Muscle Niche Formation and Analysis with Spatial RNA Sequencing.

Ben Clock, Michael Hicks

Abstract read

In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2025. 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

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.

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

2 authors.

Ben ClockPhysiology and Biophysics, University of California Irvine, Irvine, CA, USA.

Michael HicksPhysiology and Biophysics, University of California Irvine, Irvine, CA, USA. mrhicks1@hs.uci.edu.

Funding

Modulating the Stem Cell Niche Set Point to Improve Skeletal Muscle RegenerationR01AR084027 · NIAMS · UNIVERSITY OF CALIFORNIA-IRVINE · PI Michael Ryan Hicks · 2024 to 2026

$1.2M

MAXIMUS: MAXimizing Training in MUScle ResearchT32AR083870 · NIAMS · UNIVERSITY OF CALIFORNIA-IRVINE · PI TAHSEEN MOZAFFAR, Sergio Armando Villalta · 2024 to 2026

$577k

NIAMS NIH HHS R01 AR084027NIAMS NIH HHS T32 AR083870

6 · The paper itself

Abstract

Formation of the human skeletal muscle can be achieved through xenotransplant of human stem or progenitor cells into mice. Human cells, such as those derived from human pluripotent stem cells (hPSCs), are dissociated from in vitro culture conditions and injected into immune-compromised mice where human cells must form new myofibers and retain or replace the mouse muscle stem cell pool. Efforts to better understand niche interactions will lead to improved regenerative potential that could ameliorate a broad range of muscle diseases. Spatial RNA sequencing of xenografted tissues allows for precise transcriptomic profiling of human muscle stem and progenitor cells in relation to myofibers and their niche throughout the myogenic differentiation process. Herein, we describe the procedures of obtaining high yields of human xenografted transplants and compare the use of various spatial RNA sequencing platforms to uncover stem cell niche formation.

Indexed as

Muscle, SkeletalSequence Analysis, RNAStem Cell NicheAnimalsCell DifferentiationGene Expression ProfilingHumansMiceMuscle DevelopmentPluripotent Stem CellsEngraftmentNiche formationSkeletal muscleSpatial transcriptomicsStem cell

Identifiers

PMID40183842

DOI10.1007/7651_2025_619

PMCPMC13020548

What OpenQuestion holds

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Registered trials

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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.