Evidence map›Paper›PMID 37799294›Full record

ArticleArchives of microbiology & immunology2023

Automated Image Analysis Pipeline Development to Monitor Disease Progression in Muscular Dystrophy Using Cell Profiler.

Alexandra Brown, Brooklyn Morris, John Karanja Kamau, Abdullah A Alshudukhi, Abdulrahman Jama, Hongmei Ren

Open access · diamondAbstract read
In one paragraph

Article in Archives of microbiology & immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 42% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
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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

6 authors at 2 institutions in 2 countries.

Alexandra BrownDepartment of Biochemistry and Molecular Biology, Wright State University, Dayton, OH, USA.
Brooklyn MorrisDepartment of Biochemistry and Molecular Biology, Wright State University, Dayton, OH, USA.
John Karanja KamauDepartment of Biochemistry and Molecular Biology, Wright State University, Dayton, OH, USA.
Abdullah A AlshudukhiDepartment of Biochemistry and Molecular Biology, Wright State University, Dayton, OH, USA.
Abdulrahman JamaDepartment of Biochemistry and Molecular Biology, Wright State University, Dayton, OH, USA.
Hongmei RenDepartment of Biochemistry and Molecular Biology, Wright State University, Dayton, OH, USA.
Wright State University · USQassim University · SA

Funding

The Role of Lipin1 in Myofiber Stability and IntegrityR01AR077574 · NIAMS · WRIGHT STATE UNIVERSITY · PI REN, HONGMEI · 2021 to 2025
$1.8M
NIAMS NIH HHS R01 AR077574
6 · The paper itself

Abstract

Muscular dystrophies are inherited disorders that are characterized by progressive muscle degeneration. These disorders are caused by mutations in the genes encoding structural elements within the muscle, which leads to increased vulnerability to mechanical stress and sarcolemma damage. Although myofibers have the capacity to regenerate, the newly formed myofibers still harbor genetic mutation, which induces continuous cycles of muscle fiber death and regeneration. This repeated cycling is accompanied by an inflammatory response which eventually provokes excessive fibrotic deposition. The histopathological changes in skeletal muscle tissue are central to the disease pathogenesis. Analysis of muscle histopathology is the gold standard for monitoring muscle health and disease progression. However, manual, or semi-manual quantification methods, are not only immensely tedious but can be subjective. Here, we present four image analysis pipelines built in CellProfiler which enable users without a background in computer vision or programming to quantitatively analyze biological images. These image analysis pipelines are designed to quantify skeletal muscle histopathological staining for membrane damage, the abundance and size distribution of regenerating muscle fibers, inflammation via quantification of CD68+ M1 macrophages, and collagen deposition. Additionally, we discuss methods to address common errors associated with the quantification of microscopy images. These automated tools can not only improve workflow efficiency but can provide a better understanding of the histopathological progression of muscular dystrophy.

Indexed as

Automated Histopathology AnalysisCellProfilerEvan’s Blue DyeFibrosisMuscle RegenerationMuscular Dystrophy

Identifiers

PMID37799294
PMCPMC10552673
OpenAlexW4386403401

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.