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Record W2116356198 · doi:10.1186/1742-2094-8-110

Wallerian degeneration: gaining perspective on inflammatory events after peripheral nerve injury

2011· review· en· W2116356198 on OpenAlexafffund
Andrew D. Gaudet, Phillip G. Popovich, Matt S. Ramer

Bibliographic record

VenueJournal of Neuroinflammation · 2011
Typereview
Languageen
FieldNeuroscience
TopicNerve injury and regeneration
Canadian institutionsInternational Collaboration On Repair DiscoveriesVancouver Coastal Health Research InstituteUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchNational Institutes of HealthMichael Smith Health Research BC
KeywordsWallerian degenerationAxonRegeneration (biology)MyelinPeripheral nerve injuryRemyelinationNerve injuryMedicineNeuroscienceNeuroregenerationPeripheral nervous systemSchwann cellMicrogliaCentral nervous systemInflammationPathologyBiologyImmunologyCell biology

Abstract

fetched live from OpenAlex

In this review, we first provide a brief historical perspective, discussing how peripheral nerve injury (PNI) may have caused World War I. We then consider the initiation, progression, and resolution of the cellular inflammatory response after PNI, before comparing the PNI inflammatory response with that induced by spinal cord injury (SCI).In contrast with central nervous system (CNS) axons, those in the periphery have the remarkable ability to regenerate after injury. Nevertheless, peripheral nervous system (PNS) axon regrowth is hampered by nerve gaps created by injury. In addition, the growth-supportive milieu of PNS axons is not sustained over time, precluding long-distance regeneration. Therefore, studying PNI could be instructive for both improving PNS regeneration and recovery after CNS injury. In addition to requiring a robust regenerative response from the injured neuron itself, successful axon regeneration is dependent on the coordinated efforts of non-neuronal cells which release extracellular matrix molecules, cytokines, and growth factors that support axon regrowth. The inflammatory response is initiated by axonal disintegration in the distal nerve stump: this causes blood-nerve barrier permeabilization and activates nearby Schwann cells and resident macrophages via receptors sensitive to tissue damage. Denervated Schwann cells respond to injury by shedding myelin, proliferating, phagocytosing debris, and releasing cytokines that recruit blood-borne monocytes/macrophages. Macrophages take over the bulk of phagocytosis within days of PNI, before exiting the nerve by the circulation once remyelination has occurred. The efficacy of the PNS inflammatory response (although transient) stands in stark contrast with that of the CNS, where the response of nearby cells is associated with inhibitory scar formation, quiescence, and degeneration/apoptosis. Rather than efficiently removing debris before resolving the inflammatory response as in other tissues, macrophages infiltrating the CNS exacerbate cell death and damage by releasing toxic pro-inflammatory mediators over an extended period of time. Future research will help determine how to manipulate PNS and CNS inflammatory responses in order to improve tissue repair and functional recovery.

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)0.001
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: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0010.001

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 head0.065
GPT teacher head0.334
Teacher spread0.269 · 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
GenreReview

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

Citations899
Published2011
Admission routes2
Has abstractyes

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