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Record W3037630421 · doi:10.2196/18706

Closing the Gap Between Mammalian and Invertebrate Peripheral Nerve Injury: Protocol for a Novel Nerve Repair

2020· article· en· W3037630421 on OpenAlexvenueno aff
Maxwell O. Vest, Addison Guida, Cory Colombini, Kristina Cordes, Diana Peña, Marwa Maki, Michael Briones, Sabrina Antonio, Carmen Hollifield, Elli Tian, Lucas James, Christian Borashan, Johnnie Woodson, John Rovig, Hanaa Shihadeh, Alexander Karabachev, John Brosious, Ashley L. Pistorio

Bibliographic record

VenueJMIR Research Protocols · 2020
Typearticle
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsnot available
Fundersnot available
KeywordsAxonWallerian degenerationNeuroscienceSciatic nerveElectrophysiologyCompound muscle action potentialPeripheral nerve injuryAxotomyMedicineMyelinBiologyAnatomyCentral nervous system

Abstract

fetched live from OpenAlex

BACKGROUND: Outcomes after peripheral nerve injuries are poor despite current nerve repair techniques. Currently, there is no conclusive evidence that mammalian axons are capable of spontaneous fusion after transection. Notably, certain invertebrate species are able to auto-fuse after transection. Although mammalian axonal auto-fusion has not been observed experimentally, no mammalian study to date has demonstrated regenerating axolemmal membranes contacting intact distal segment axolemmal membranes to determine whether mammalian peripheral nerve axons have the intrinsic mechanisms necessary to auto-fuse after transection. OBJECTIVE: This study aims to assess fusion competence between regenerating axons and intact distal segment axons by enhancing axon regeneration, delaying Wallerian degeneration, limiting the immune response, and preventing myelin obstruction. METHODS: This study will use a rat sciatic nerve model to evaluate the effects of a novel peripheral nerve repair protocol on behavioral, electrophysiologic, and morphologic parameters. This protocol consists of a variety of preoperative, intraoperative, and postoperative interventions. Fusion will be assessed with electrophysiological conduction of action potentials across the repaired transection site. Axon-axon contact will be assessed with transmission electron microscopy. Behavioral recovery will be analyzed with the sciatic functional index. A total of 36 rats will be used for this study. The experimental group will use 24 rats and the negative control group will use 12 rats. For both the experimental and negative control groups, there will be both a behavior group and another group that will undergo electrophysiological and morphological analysis. The primary end point will be the presence or absence of action potentials across the lesion site. Secondary end points will include behavioral recovery with the sciatic functional index and morphological analysis of axon-axon contact between regenerating axons and intact distal segment axons. RESULTS: The author is in the process of grant funding and institutional review board approval as of March 2020. The final follow-up will be completed by December 2021. CONCLUSIONS: In this study, the efficacy of the proposed novel peripheral nerve repair protocol will be evaluated using behavioral and electrophysiologic parameters. The author believes this study will provide information regarding whether spontaneous axon fusion is possible in mammals under the proper conditions. This information could potentially be translated to clinical trials if successful to improve outcomes after peripheral nerve injury. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/18706.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Protocol · Consensus signal: none
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.460
GPT teacher head0.530
Teacher spread0.070 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreProtocol

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2020
Admission routes1
Has abstractyes

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