Inhaled Cannabis Suppresses Chemotherapy-Induced Neuropathic Nociception by Decoupling the Raphe Nucleus: A Functional Imaging Study in Rats
Bibliographic record
Abstract
Efficacy of inhaled cannabis for treating pain is controversial. Effective treatment for chemotherapy-induced neuropathy represents an unmet medical need. We hypothesized that cannabis reduces neuropathic pain by reducing functional coupling in the raphe nuclei. We assessed the impact of inhalation of vaporized cannabis plant (containing 10.3% Δ9-tetrahydrocannabinol/0.05% cannabidiol) or placebo cannabis on brain resting-state blood oxygen level–dependent functional connectivity and pain behavior induced by paclitaxel in rats. Rats received paclitaxel to produce chemotherapy-induced peripheral neuropathy or its vehicle. Behavioral and imaging experiments were performed after neuropathy was established and stable. Images were registered to, and analyzed using, a 3D magnetic resonance imaging rat atlas providing site-specific data on more than 168 different brain areas. Prior to vaporization, paclitaxel produced cold allodynia. Inhaled vaporized cannabis increased cold withdrawal latencies relative to prevaporization or placebo cannabis, consistent with Δ9-tetrahydrocannabinol-induced antinociception. In paclitaxel-treated rats, the midbrain serotonergic system, comprising the dorsal and median raphe, showed hyperconnectivity to cortical, brainstem, and hippocampal areas, consistent with nociceptive processing. Inhalation of vaporized cannabis uncoupled paclitaxel-induced hyperconnectivity patterns. No such changes in connectivity or cold responsiveness were observed following placebo cannabis vaporization. Inhaled vaporized cannabis plant uncoupled brain resting-state connectivity in the raphe nuclei, normalizing paclitaxel-induced hyperconnectivity to levels observed in vehicle-treated rats. Inhaled vaporized cannabis produced antinociception in both paclitaxel- and vehicle-treated rats. Our study elucidates neural circuitry implicated in the therapeutic effects of Δ9-tetrahydrocannabinol and supports a role for functional imaging studies in animals in guiding indications for future clinical trials.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".