Evidence map›Paper›PMID 42765433›Full record

ArticlePhysiological reports2026

A semi-automated pipeline for quantitation of Pax7+, myonuclei, and cross-sectional area by fiber type.

Helia G Megowan, Madeline Luu, Adam Shuaib, Kaitlyn B Augienello, Adam C Fries, Jake Searcy, Hans C Dreyer

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Physiological reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

7 authors.

Helia G MegowanDepartment of Human Physiology, University of Oregon, Eugene, Oregon, USA.
Madeline LuuDepartment of Computer Science, University of Oregon, Eugene, Oregon, USA.
Adam ShuaibDepartment of Neuroscience, University of Oregon, Eugene, Oregon, USA.
Kaitlyn B AugienelloDepartment of Human Physiology, University of Oregon, Eugene, Oregon, USA.
Adam C FriesGenomics & Cell Characterization Core Facility, University of Oregon, Eugene, Oregon, USA.
Jake SearcyDepartment of Data Science, University of Oregon, Eugene, Oregon, USA.
Hans C DreyerDepartment of Human Physiology, University of Oregon, Eugene, Oregon, USA.ORCID https://orcid.org/0000-0003-2555-5240

Funding

Wu Tsai Human Performance Alliance
6 · The paper itself

Abstract

Manual analysis of skeletal muscle cross-sections is time-consuming and subject to error and user bias. To overcome these limitations, we developed and validated a semi-automated, quantitative, and reproducible image-analysis pipeline specifically tailored to quantify Pax7+ satellite cells, myonuclei, and cross-sectional area by fiber type. The workflow combines Fiji/ImageJ-based image preprocessing with CellProfiler, Cellpose, and a custom Python script to process and analyze immunohistological images of muscle tissue cross-sections. Outcomes include Pax7+ satellite cells and myonuclei quantified per fiber by fiber type, along with cross-sectional area, perimeter, and fiber type classification. This semi-automated approach provides a robust and efficient platform for high-throughput analysis of muscle tissue cross-sections from large datasets.

Indexed as

Cell NucleusImage Processing, Computer-AssistedMuscle Fibers, SkeletalPAX7 Transcription FactorSatellite Cells, Skeletal MuscleAnimalsMicePax7 protein, mousePAX7 Transcription Factorautomated analysisCellProfilermuscle stem cellsskeletal muscle

Identifiers

PMID42765433
PMCPMC13591552

What Socratic holds

Textmetadata
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 Socratic graph.