Studies of peripheral sensory nerves in paclitaxel-induced painful peripheral neuropathy: Evidence for mitochondrial dysfunction
Bibliographic record
Abstract
Paclitaxel chemotherapy frequently induces neuropathic pain during and often persisting after therapy. The mechanisms responsible for this pain are unknown. Using a rat model of paclitaxel-induced painful peripheral neuropathy, we have performed studies to search for peripheral nerve pathology. Paclitaxel-induced mechano-allodynia and mechano-hyperalgesia were evident after a short delay, peaked at day 27 and finally resolved on day 155. Paclitaxel- and vehicle-treated rats were perfused on days 7, 27 and 160. Portions of saphenous nerves were processed for electron microscopy. There was no evidence of paclitaxel-induced degeneration or regeneration as myelin structure was normal and the number/density of myelinated axons and C-fibres was unaltered by paclitaxel treatment at any time point. In addition, the prevalence of ATF3-positive dorsal root ganglia cells was normal in paclitaxel-treated animals. With one exception, at day 160 in myelinated axons, total microtubule densities were also unaffected by paclitaxel both in C-fibres and myelinated axons. C-fibres were significantly swollen following paclitaxel at days 7 and 27 compared to vehicle. The most striking finding was significant increases in the prevalence of atypical (swollen and vacuolated) mitochondria in both C-fibres (1.6- to 2.3-fold) and myelinated axons (2.4- to 2.6-fold) of paclitaxel-treated nerves at days 7 and 27. Comparable to the pain behaviour, these mitochondrial changes had resolved by day 160. Our data do not support a causal role for axonal degeneration or dysfunction of axonal microtubules in paclitaxel-induced pain. Instead, our data suggest that a paclitaxel-induced abnormality in axonal mitochondria of sensory nerves contributes to paclitaxel-induced 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) | 0.000 | 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) | 0.002 | 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".