Evidence map›Paper›PMID 34879058›Full record

ArticlePLoS computational biology2021

Benchmarking of tools for axon length measurement in individually-labeled projection neurons.

Mario Rubio-Teves, Sergio Díez-Hermano, César Porrero, Abel Sánchez-Jiménez, Lucía Prensa, Francisco Clascá, María García-Amado, José Antonio Villacorta-Atienza

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.3field-weighted citation impact, top 49% 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

5 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
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  5. Defect ofInternational journal of molecular sciences · 2023
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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

8 authors at 2 institutions in 1 country.

Mario Rubio-TevesDepartment of Anatomy & Neuroscience, School of Medicine, Autónoma de Madrid University, Madrid, Spain.ORCID 0000-0002-1405-9885
Sergio Díez-HermanoDepartment of Biodiversity, ecology and evolution, Biomathematics Unit, Faculty of Biology, Complutense University of Madrid, Madrid, Spain.ORCID 0000-0003-3830-7297
César PorreroDepartment of Anatomy & Neuroscience, School of Medicine, Autónoma de Madrid University, Madrid, Spain.ORCID 0000-0002-2170-2453
Abel Sánchez-JiménezDepartment of Biodiversity, ecology and evolution, Biomathematics Unit, Faculty of Biology, Complutense University of Madrid, Madrid, Spain.ORCID 0000-0002-7978-3436
Lucía PrensaDepartment of Anatomy & Neuroscience, School of Medicine, Autónoma de Madrid University, Madrid, Spain.
Francisco ClascáDepartment of Anatomy & Neuroscience, School of Medicine, Autónoma de Madrid University, Madrid, Spain.ORCID 0000-0003-0718-1337
María García-AmadoDepartment of Anatomy & Neuroscience, School of Medicine, Autónoma de Madrid University, Madrid, Spain.
José Antonio Villacorta-AtienzaDepartment of Biodiversity, ecology and evolution, Biomathematics Unit, Faculty of Biology, Complutense University of Madrid, Madrid, Spain.ORCID 0000-0002-9220-1226
Universidad Autónoma de Madrid · ESUniversidad Complutense de Madrid · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Projection neurons are the commonest neuronal type in the mammalian forebrain and their individual characterization is a crucial step to understand how neural circuitry operates. These cells have an axon whose arborizations extend over long distances, branching in complex patterns and/or in multiple brain regions. Axon length is a principal estimate of the functional impact of the neuron, as it directly correlates with the number of synapses formed by the axon in its target regions; however, its measurement by direct 3D axonal tracing is a slow and labor-intensive method. On the contrary, axon length estimations have been recently proposed as an effective and accessible alternative, allowing a fast approach to the functional significance of the single neuron. Here, we analyze the accuracy and efficiency of the most used length estimation tools-design-based stereology by virtual planes or spheres, and mathematical correction of the 2D projected-axon length-in contrast with direct measurement, to quantify individual axon length. To this end, we computationally simulated each tool, applied them over a dataset of 951 3D-reconstructed axons (from NeuroMorpho.org), and compared the generated length values with their 3D reconstruction counterparts. The evaluated reliability of each axon length estimation method was then balanced with the required human effort, experience and know-how, and economic affordability. Subsequently, computational results were contrasted with measurements performed on actual brain tissue sections. We show that the plane-based stereological method balances acceptable errors (~5%) with robustness to biases, whereas the projection-based method, despite its accuracy, is prone to inherent biases when implemented in the laboratory. This work, therefore, aims to provide a constructive benchmark to help guide the selection of the most efficient method for measuring specific axonal morphologies according to the particular circumstances of the conducted research.

Indexed as

AnimalsAxonsComputational BiologyDatabases, FactualImaging, Three-DimensionalMiceNeuronsTomography

Identifiers

PMID34879058
PMCPMC8824366
OpenAlexW4225483595

What OpenQuestion holds

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LicenceCC BY
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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.