Evidence map›Paper›PMID 36901939›Full record

ArticleInternational journal of molecular sciences2023

A Semi-Automatic Method for the Quantification of Astrocyte Number and Branching in Bulk Immunohistochemistry Images.

Sandra I Marques, Helena Carmo, Félix Carvalho, Susana I Sá, João Pedro Silva

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Article in International journal of molecular sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

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  7. Standardizing the lateral fluid percussion model of trauma in marmosets (Callithrix jacchus): regional vulnerability and inflammatory response.Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologicas · 2026
    Article
  8. Article
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  13. Digital pathology in tau research: A comparison of QuPath and HALO.Journal of neuropathology and experimental neurology · 2025
    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

5 authors.

Sandra I MarquesUCIBIO-Applied Molecular Biosciences Unit, Laboratory of Toxicology, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal.ORCID 0000-0001-8090-5720
Helena CarmoUCIBIO-Applied Molecular Biosciences Unit, Laboratory of Toxicology, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal.ORCID 0000-0002-6650-5285
Félix CarvalhoUCIBIO-Applied Molecular Biosciences Unit, Laboratory of Toxicology, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal.ORCID 0000-0003-3858-3494
Susana I SáUnit of Anatomy, Department of Biomedicine, Faculty of Medicine, University of Porto, Alameda Prof. Hernâni Monteiro, 4200-319 Porto, Portugal.ORCID 0000-0002-5078-980X
João Pedro SilvaUCIBIO-Applied Molecular Biosciences Unit, Laboratory of Toxicology, Faculty of Pharmacy, University of Porto, 4050-313 Porto, Portugal.ORCID 0000-0002-5656-0897

Funding

Fundação para a Ciência e Tecnologia 2020.09080.BDFundação para a Ciência e Tecnologia 2021.01789.CEECINDi4HB - Institute for Health and Bioeconomy LA/P/0140/2020Innovative Medicines Initiative 821528UCIBIO - Applied Molecular Biosciences Unit UIDB/04378/2020UCIBIO - Applied Molecular Biosciences Unit UIDP/04378/2020
6 · The paper itself

Abstract

Immunohistochemical staining of cell and molecular targets in brain samples is a powerful tool that can provide valuable information on neurological mechanisms. However, post-processing of photomicrographs acquired after 3,3'-Diaminobenzidine (DAB) staining is particularly challenging due to the complexity associated with the size, samples number, analyzed targets, image quality, and even the subjectivity inherent to the analysis by different users. Conventionally, this analysis relies on the manual quantification of distinct parameters (e.g., the number and size of cells and the number and length of cell branching) in a large set of images. These represent extremely time-consuming and complex tasks, defaulting the processing of high amounts of information. Here we describe an improved semi-automatic method to quantify glial fibrillary acidic protein (GFAP)-labelled astrocytes in immunohistochemistry images of rat brains, at magnifications as low as 20×. This method is a straightforward adaptation of the Young & Morrison method, using ImageJ's plugin Skeletonize, coupled with intuitive data processing in datasheet-based software. It allows swifter and more efficient post-processing of brain tissue samples, regarding astrocyte size and number quantification, the total area occupied, as well as astrocyte branching and branch length (indicators of astrocyte activation), thus contributing to better understand the possible inflammatory response developed by astrocytes.

Indexed as

AstrocytesBrainAnimalsGlial Fibrillary Acidic ProteinHeadImmunohistochemistryNeurogenesisRatsGlial Fibrillary Acidic Proteinglial fibrillary acidic protein (GFAP)image analysisimage post-processingskeletonize

Identifiers

PMID36901939
PMCPMC10003611

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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.