GDNF levels in the lower lip skin in a rat model of trigeminal neuropathic pain: Implications for nonpeptidergic fiber reinnervation and parasympathetic sprouting
Bibliographic record
Abstract
Trigeminal neuropathic pain is associated with trigeminal nerve damage. Significant remodeling of the peripheral nervous system may contribute to the pain; however, the changes and the factors that drive them have not been well described. In this study, a partial injury of the mental nerve of the rat, a purely sensory branch of the trigeminal nerve, resulted in prolonged mechanical allodynia in the lower lip skin persisting up to 4 months. Although nonpeptidergic, P2X3-immunoreactive (IR) C fibers displayed a transient decrease in density of innervation in the skin; they returned to sham levels by 4 weeks after lesioning. Ectopic sympathetic (as detected by anti-dopamine-β-hydroxylase antibodies) and parasympathetic (as detected by antibodies against the vesicular acetylcholine transporter) fibers in the upper dermis were apparent early on the following lesion (2 weeks), in close apposition with regenerating nonpeptidergic fibers. Meanwhile, the glial cell line-derived growth factor (GDNF) showed a quick upregulation in the skin after nerve lesioning, with levels peaking at 4 weeks. This suggests that an excess of GDNF in the skin drives the nonpeptidergic C-fiber regeneration and parasympathetic fiber sprouting in the upper dermis, and could be an important mechanism in trigeminal neuropathic pain. This article provides an in-depth description of the changes in nonpeptidergic fibers in the skin after nerve lesioning, and measures, for the first time, GDNF protein levels in the skin after a nerve lesion, providing strong evidence for the role of GDNF in modulating innervation of the nonpeptidergic and parasympathetic fibers in the skin after injury.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".