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Record W45469515 · doi:10.1093/jnen/60.5.411

Delayed peripheral Nerve Degeneration, Regeneration, and pain in Mice Lacking Inducible Nitric Oxide Synthase

2001· article· en· W45469515 on OpenAlexaff
Dan Levy, Paul Kubes, Douglas W. Zochodne

Bibliographic record

VenueJournal of Neuropathology & Experimental Neurology · 2001
Typearticle
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsUniversity of Calgary
FundersMedical Research Council
KeywordsWallerian degenerationNitric oxide synthaseReinnervationNeuropathic painPeripheral nerve injuryAxonNitric oxideNerve injuryRegeneration (biology)MedicineDegeneration (medical)Crush injuryPathologyAnatomySciatic nerveEndocrinologyChemistryAnesthesiaBiologyCell biologySurgery

Abstract

fetched live from OpenAlex

Inducible nitric oxide synthase (iNOS) may be a critical factor in the repair of injured tissues. In mice lacking iNOS we observed abnormalities in how the peripheral nerve responds to each of 3 fundamental types of injury: chronic constriction partial nerve injury (a model of neuropathic pain), nerve crush, and nerve transection. In each type of injury, mice lacking iNOS had evidence of a regenerative delay, preceded by slowing of myelinated fiber Wallerian degeneration (WD). In wild-type mice, iNOS immunoreactivity and the presence and upregulation of its mRNA were demonstrated distal to injury, but neither was observed in the knockout mice. Slowed WD was suggested by the abnormal persistence of apparent myelinated fiber profiles distal to the injury zones in mice lacking iNOS compared to wild-type controls. In mice lacking iNOS there were fewer regenerating myelinated fibers, smaller caliber regenerating fibers, and slowed reinnervation of muscle endplates distal to the injury zone. Slowed degeneration was also associated with normal initiation but delayed expression of neuropathic pain. Our findings highlight important relationships among nitric oxide, WD, neuropathic pain, and axon regeneration.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.351
Threshold uncertainty score0.832

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.020
GPT teacher head0.282
Teacher spread0.262 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations109
Published2001
Admission routes1
Has abstractyes

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