Evidence map›Paper›PMID 40538075›Full record

ArticlePhysiological reports2025

Distinct morphometric features of cardiomyocytes isolated from mouse hypertrophy models: An ImageJ analysis combined with machine learning algorithms.

Hoang Duc Minh Pham, Marie-Thérèse Daher, Onnik Agbulut, Zhenlin Li, Ara Parlakian

Abstract read
In one paragraph

Article in Physiological reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
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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

5 authors.

Hoang Duc Minh PhamSorbonne Université, CNRS UMR8263, INSERM U1345, Development, Adaptation and Ageing, Institute of Biology Paris-Seine, Paris, France.
Marie-Thérèse DaherSorbonne Université, CNRS UMR8263, INSERM U1345, Development, Adaptation and Ageing, Institute of Biology Paris-Seine, Paris, France.
Onnik AgbulutSorbonne Université, CNRS UMR8263, INSERM U1345, Development, Adaptation and Ageing, Institute of Biology Paris-Seine, Paris, France.
Zhenlin LiSorbonne Université, CNRS UMR8263, INSERM U1345, Development, Adaptation and Ageing, Institute of Biology Paris-Seine, Paris, France.
Ara ParlakianSorbonne Université, CNRS UMR8263, INSERM U1345, Development, Adaptation and Ageing, Institute of Biology Paris-Seine, Paris, France.ORCID 0000-0002-0928-2185

Funding

Emergence Sorbonne University EMERG-28Fédération Française de Cardiologie (FFC) FFC2019Fondation de France (Foundation of France) 00086490Fondation de l'Avenir pour la Recherche Médicale Appliquée (Fondation de l'Avenir) AP-RM-23-028The French Muscular Dystrophy Association (AFM-Téléthon) 17689The French Muscular Dystrophy Association (AFM-Téléthon) 19353Vingroup Science and Technology Scholarship Cohort 2020
6 · The paper itself

Abstract

This study aims at defining a standardized workflow based on a customized ImageJ macro combined with a machine-learning algorithm to analyze morphometric features of isolated cardiomyocytes using high-resolution/high-content photomicrographs and to identify key and specific morphological features of cardiomyocytes isolated from various murine cardiac hypertrophy models. For that purpose, we set up and optimized a Langendorff based protocol for isolating cardiomyocytes from mouse hearts. This optimized protocol yielded in a significantly high number of formaldehyde-fixed cardiomyocytes, with more than 97% of rod shaped cells. Moreover, our method allowed for reliable gene expression analysis and conservation of cell integrity through multiple freeze-thaw cycles. Next, we successfully applied our analytical workflow on formaldehyde-fixed cardiomyocytes isolated from various murine cardiac hypertrophy models and defined distinct morphological features in Angiotensin II, Isoproterenol, and age-induced hypertrophy. Taken together, our study provides an effective and standardized workflow for high-throughput morphological and molecular characterization of isolated cardiomyocytes, and could constitute a robust and reliable analytical tool to distinguish healthy versus diseased states and assess the ability of a potential therapeutic agent or strategy to reverse the situation.

Indexed as

CardiomegalyImage Processing, Computer-AssistedMachine LearningMyocytes, CardiacAlgorithmsAnimalsDisease Models, AnimalIsoproterenolMaleMiceMice, Inbred C57BLIsoproterenolcardiac hypertrophycardiomyocyte isolationLangendorffmachine learningmorphological analysis

Identifiers

PMID40538075
PMCPMC12179408

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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.