Altered responsiveness of serotonin receptor subtypes following long-term cannabinoid treatment
Bibliographic record
Abstract
This study examined the effects of long-term cannabinoid administration on the responsivity of 5-HT1A and 5-HT2A receptors, which have been implicated in depression. Animals received 12 d administration of the potent cannabinoid receptor agonist HU-210 (100 microg/kg), following which they were monitored on their behavioural, physiological and hormonal responses to a single challenge of a 5-HT1A and 5-HT2A receptor agonist, 8-OH-DPAT (0.3 mg/kg) and DOI (1 mg/kg) respectively. Chronic HU-210 treatment lead to a significant enhancement of DOI-induced wet-dog shakes, but a reduction of DOI-induced back muscle contractions. DOI-induced corticosterone release was unaffected by HU-210 treatment. The hyperthermic response to DOI appeared to be potentiated by long-term HU-210 treatment, as 50% of these subjects died from an apparent serotonin syndrome with core temperatures exceeding 43 degrees C. The 8-OH-DPAT-induced hypothermic response and elevation of corticosterone were both significantly attenuated by long- term HU-210 treatment. These data imply that chronic cannabinoid treatment may up-regulate 5-HT2A receptor activity while concurrently down-regulating 5-HT1A receptor activity, a finding similar to that sometimes observed in depression. This may partially explain the association between excessive cannabis consumption and the induction of affective disease.
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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) | 0.001 | 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".