Abnormal Reinnervation of Denervated Areas Following Nerve Injury Facilitates Neuropathic Pain
Bibliographic record
Abstract
An injury to peripheral nerves leads to skin denervation, which often is followed by increased pain sensitivity of the denervated areas and the development of neuropathic pain. Changes in innervation patterns during the reinnervation process of the denervated skin could contribute to the development of neuropathic pain. Here, we examined the changes in the innervation pattern during reinnervation and correlated them with the symptoms of neuropathic pain. Using a multispectral labeling technique-PainBow, which we developed, we characterized dorsal root ganglion (DRG) neurons innervating distinct areas of the rats' paw. We then used spared nerve injury, causing partial denervation of the paw, and examined the changes in innervation patterns of the denervated areas during the development of allodynia and hyperalgesia. We found that, differently from normal conditions, during the development of neuropathic pain, these areas were mainly innervated by large, non-nociceptive neurons. Moreover, we found that the development of neuropathic pain is correlated with an overall decrease in the number of DRG neurons innervating these areas. Importantly, treatment with ouabain facilitated reinnervation and alleviated neuropathic pain. Our results suggest that local changes in peripheral innervation following denervation contribute to neuropathic pain development. The reversal of these changes decreases neuropathic pain.
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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 | 0.001 | 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 | 0.000 |
| 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".