Delayed reinnervation by nonpeptidergic nociceptive afferents of the glabrous skin of the rat hindpaw in a neuropathic pain model
Bibliographic record
Abstract
Painful peripheral neuropathies have been associated with a reorganization of skin innervation. However, the detailed changes in skin innervation by the different afferent fiber types following a neuropathic nerve injury have never been characterized in an animal model of neuropathic pain. Our objective was to thoroughly characterize such changes in the thick skin of the foot in a well-established rat model of neuropathic pain, namely, the chronic constriction injury (CCI) of the sciatic nerve. We used the immunofluorescence detection of calcitonin gene-related peptide (CGRP), purinergic receptor P2X3, and NF200 as markers of peptidergic nociceptive fibers, nonpeptidergic nociceptive C fibers, and myelinated afferents, respectively. We observed that CCI-operated animals developed significant mechanical allodynia and hyperalgesia as well as thermal hyperalgesia. At 3 days following nerve injury, all CCI-operated animals had a significant decrease in the density of fibers immunoreactive (IR) for CGRP, P2X3, and NF200 within the upper dermis. A recovery of CGRP-IR fibers occurred within 4 weeks of nerve injury and sprouting above control levels was observed at 16 weeks. However, the myelinated (NF200-IR) fibers never recovered to control levels within a period of 16 weeks following nerve injury. Interestingly, the P2X3-IR fibers took considerably more time to recover than the CGRP-IR fibers following the initial loss. A loss in P2X3-IR fibers persisted to 16 weeks and recovered to levels above that of control at 1.5 years following nerve injury. Further studies are required to clarify the relevance of these innervation changes for neuropathic pain generation and maintenance.
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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 | 0.002 | 0.000 |
| 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 | 0.001 |
| 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".