Consequences of the ablation of nonpeptidergic afferents in an animal model of trigeminal neuropathic pain
Bibliographic record
Abstract
Damage to peripheral nerves causes significant remodeling of peripheral innervation and can lead to neuropathic pain. Most nociceptive primary afferents are unmyelinated (C fibers) and subdivided into peptidergic and nonpeptidergic fibers. Previous studies have found nerve injury in the trigeminal system to induce changes in small-diameter primary afferent innervation and cause significant autonomic sprouting into the upper dermis of the lower-lip skin of the rat. In this study, we used the ribosomal toxin, saporin, conjugated to the lectin IB4 to specifically ablate the nonpeptidergic nociceptive C fibers, to see if loss of these fibers was enough to induce autonomic fiber sprouting. IB4-saporin treatment led to specific and permanent ablation of the IB4-positive, P2X(3)-immunoreactive fibers and led to sprouting of parasympathetic fibers into the upper dermis, but not of sympathetic fibers. These changes were associated with significant increase in glial-derived nerve growth factor levels in the lower-lip skin. While IB4-saporin treatment had no effect on evoked mechanical thresholds when von Frey hairs were applied to the lower-lip skin, ablation of nonpeptidergic fibers in a chronic constriction injury model caused significant sympathetic and parasympathetic fiber sprouting, and led to an exacerbated pain response. This was an unexpected finding, as it has been suggested that nonpeptidergic fibers play a major role in mechanical pain, and suggests that these fibers play a complex role in the development of neuropathic pain.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".