Evidence map›Paper›PMID 41683617›Full record

ArticleInternational journal of molecular sciences2026

MitoTex (Mitochondria Texture Analysis User Interface): Open-Source Framework for Textural Characterization and Classification of Mitochondrial Structures.

Amulya Kaianathbhatta, Malak Al Daraawi, Natasha N Kunchur, Rayhane Mejlaoui, Zoya Versey, Edana Cassol, Leila B Mostaço-Guidolin

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2026. 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

7 authors.

Amulya KaianathbhattaDepartment of Systems and Computer Engineering, Carleton University, Ottawa, ON K1S 5B6, Canada.
Malak Al DaraawiTissue Engineering and Applied Materials (TEAM) Hub, Ottawa, ON K1S 5B6, Canada.ORCID 0009-0005-8135-4832
Natasha N KunchurDepartment of Systems and Computer Engineering, Carleton University, Ottawa, ON K1S 5B6, Canada.ORCID 0009-0001-4967-5768
Rayhane MejlaouiTissue Engineering and Applied Materials (TEAM) Hub, Ottawa, ON K1S 5B6, Canada.
Zoya VerseyTissue Engineering and Applied Materials (TEAM) Hub, Ottawa, ON K1S 5B6, Canada.
Edana CassolTissue Engineering and Applied Materials (TEAM) Hub, Ottawa, ON K1S 5B6, Canada.
Leila B Mostaço-GuidolinDepartment of Systems and Computer Engineering, Carleton University, Ottawa, ON K1S 5B6, Canada.ORCID 0000-0002-3751-2494

Funding

Asthma Canada, the Canadian Allergy, Asthma and Immunology Foundation 02357-000Canadian Institutes of Health Research - Institute of Circulatory and Respiratory Health 202309PJT-507074-MPI-CEGA-259041Canadian Institutes of Health Research - Institute of Circulatory and Respiratory Health 202311FBDDiscovery Grant of Canada RGPIN-2019-0621Natural Sciences and Engineering Research Council of Canada RGPIN-2021-04185
6 · The paper itself

Abstract

Mitochondria are essential organelles involved in metabolism, energy production, and cell signaling. Assessing mitochondrial morphology is key to tracking cell metabolic activity and function. Quantifying these structural changes may also provide critical insights into disease pathogenesis and therapeutic responses. This work details the development and validation of a novel, quantitative image analysis pipeline for the characterization and classification of dynamic mitochondrial morphologies. Utilizing high-resolution confocal microscopy, the pipeline integrates first-order statistics (FOS) and a comprehensive suite of gray-level texture analyses, including gray level co-occurrence matrix (GLCM), gray level run length matrix (GLRLM), gray level dependence matrix (GLDM), gray level size zone matrix (GLSZM), and neighboring gray tone difference matrix (NGTDM) with machine learning approaches. The method's efficacy in objectively differentiating key mitochondrial structures-fibers, puncta, and rods-which are critical indicators of cellular metabolic and activation states is demonstrated. Our open-source pipeline provides robust quantitative metrics for characterizing mitochondrial variation.

Indexed as

Image Processing, Computer-AssistedMitochondriaSoftwareAnimalsHumansMachine LearningMicroscopy, Confocalmachine learningmicroscopymitochondriatexture analysis

Identifiers

PMID41683617
PMCPMC12897202

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.