Ethosuximide reverses paclitaxel- and vincristine-induced painful peripheral neuropathy
Bibliographic record
Abstract
Paclitaxel (Taxol) is one of the most effective and frequently used chemotherapeutics for the treatment of solid tumours. However, paclitaxel produces peripheral neurotoxicity with patients reporting sensory abnormalities and neuropathic pain during and often persisting after paclitaxel therapy. The mechanisms underlying this dose-limiting side effect are currently unknown and there are no validated drugs for its prevention or control. Male Sprague-Dawley rats received four intraperitoneal (i.p.) injections on alternate days of 2 mg/kg paclitaxel. Behavioural assessment using von Frey filaments and acetone showed that such paclitaxel treatment induced a pronounced mechanical and cold allodynia/hyperalgesia. Thus these studies aim to test potential analgesics on established paclitaxel-induced pain. Paclitaxel-induced pain appears to be relatively resistant to opioid therapy i.p. 4 mg/kg morphine was ineffective and i.p. 8 mg/kg morphine only elicited up to a 50% reversal of mechanical allodynia/hyperalgesia. Interestingly, a maximally tolerated dose (i.p. 0.2 mg/kg) of the potent NMDA receptor antagonist MK-801 produced no significant reversal of the mechanical allodynia/hyperalgesia suggesting that NMDA receptors have little role in paclitaxel-induced pain. Ethosuximide (i.p. 450 mg/kg) an anti-epileptic and relatively selective T-type calcium channel blocker elicited a near complete reversal of mechanical allodynia/hyperalgesia. Repetitive dosing with ethosuximide (i.p. 100 or 300 mg/kg daily for 3 days) showed a dose-related consistent reversal of mechanical allodynia/hyperalgesia with no evidence of tolerance. Ethosuximide (i.p. 300 mg/kg) also reversed paclitaxel-induced cold allodynia and vincristine-induced mechanical allodynia/hyperalgesia. These data suggest that T-type calcium channels may play a role in chemotherapy-induced neuropathy and moreover identify ethosuximide as a new potential treatment for chemotherapy-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".