Evidence map›Paper›PMID 28745626›Full record

ArticleJournal of visualized experiments : JoVE2017

Quantifying Branching Density in Rat Mammary Gland Whole-mounts Using the Sholl Analysis Method.

Jason P Stanko, Suzanne E Fenton

Abstract readVideo-Audio Media
In one paragraph

Article in Journal of visualized experiments : JoVE, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Article
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  8. Whole mount preparation and analysis of rabbit mammary gland.Reproductive toxicology (Elmsford, N.Y.) · 2024
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  15. Review
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  19. Mutant SF3B1 promotes AKT- and NF-κB-driven mammary tumorigenesis.The Journal of clinical investigation · 2021
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  20. 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

2 authors.

Jason P StankoNational Toxicology Program Laboratory, Division of the National Toxicology Program, National Institute of Environmental Health Sciences.
Suzanne E FentonNational Toxicology Program Laboratory, Division of the National Toxicology Program, National Institute of Environmental Health Sciences; Suzanne.fenton@nih.gov.

Funding

Mammary Gland as a Sensitive End Point to Effects of Endocrine DisruptorsZIAES102785 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI FENTON, SUZANNE · 2010 to 2021
$38.1M
6 · The paper itself

Abstract

An increasing number of studies are utilizing the rodent mammary gland as an endpoint for assessing the developmental toxicity of a chemical exposure. The effects these exposures have on mammary gland development are typically evaluated using either basic dimensional measurements or by scoring morphological characteristics. However, the broad range of methods for interpreting developmental changes could lead to inconsistent translations across laboratories. A common method of assessment is needed so that proper interpretations can be formed from data being compared across studies. The present study describes the application of the Sholl analysis method to quantify mammary gland branching characteristics. The Sholl method was originally developed for use in quantifying neuronal dendritic patterns. By using ImageJ, an open-source image analysis software package, and a plugin developed for this analysis, the mammary gland branching density and the complexity of a mammary gland from a peripubertal female rat were determined. The methods described here will enable the use of the Sholl analysis as an effective tool for quantifying an important characteristic of mammary gland development.

Indexed as

AnimalsFemaleMammary Glands, AnimalRatsRats, Sprague-Dawley

Identifiers

PMID28745626
PMCPMC5612270

What OpenQuestion holds

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Registered trials

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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.