Evidence map›Paper›PMID 40099847›Full record

ArticleRegenerative medicine

Open-source software to calculate the static sciatic index automatically.

Simão Laranjeira, Owein Guillemot-Legris, Gedion Girmahun, James B Phillips, Rebecca J Shipley

Abstract read
In one paragraph

Article in Regenerative medicine. 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
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1 · What the graph read from it

What it found

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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

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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

5 authors.

Simão LaranjeiraUCL Department of Mechanical Engineering, London, UK.
Owein Guillemot-LegrisDepartment of Pharmacology, UCL School of Pharmacy, London, UK.
Gedion GirmahunDepartment of Pharmacology, UCL School of Pharmacy, London, UK.
James B PhillipsDepartment of Pharmacology, UCL School of Pharmacy, London, UK.
Rebecca J ShipleyUCL Department of Mechanical Engineering, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe static sciatic index is commonly used in rat models of nerve crush injury to quantify functional recovery from new therapies under evaluation. However, it is challenging to standardize these measurements across different investigations, and the process is labor intensive. MATERIAL/

methodsA new machine learning method was previously developed that performs these measurements automatically and consistently. Here, the approach is tested using two data sets that use different experimental setups, and end-user requirements are evaluated.

resultsThe model's outputs presented a nerve regeneration profile comparable to the manual measurements and outperformed the latter by having a much tighter standard deviation (± 5- ± 10 compared to ± 10 - ± 50).

conclusionAn inexpensive automatic tool that can perform functional analysis for nerve repair research was developed and tested. The software is available open source to facilitate its dissemination and use in quantifying recovery from peripheral nerve crush injury.

Indexed as

Nerve RegenerationPeripheral Nerve InjuriesSciatic NerveSoftwareAnimalsMachine LearningRatsRecovery of FunctionregenerationRepairtechnology platformstissue engineeringtools and services

Identifiers

PMID40099847
PMCPMC11951718

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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.