Effects of Δ <sup>9</sup> -Tetrahydrocannabinol, Cannabinol and Cannabidiol on the Immune System in Mice
Bibliographic record
Abstract
The effects of the cannabinoids delta 9-tetrahydrocannabinol (THC), cannabinol and cannabidiol on the primary humoral immune response, the secondary humoral immune response and the memory aspect of humoral immunity in response to sheep red blood cell (SRBC) immunization was investigated. Mice treated with THC (10 and 15 mg/kg) during the primary immunization period exhibited a suppression of the primary humoral immune response. Mice treated with THC during the secondary immunization period showed no measurable suppression of the secondary humoral immune response to the immunizing antigen. The memory aspect of humoral immunity was assessed when treatment with cannabinoids was carried out during the primary immunization period and the ability of mice to undergo a secondary immune response was evaluated; suppression of the secondary humoral immune response was evident with THC treatment (10 and 15 mg/kg). Cannabinol and cannabidiol (10 and 25 mg/kg) treated mice showed no impairment in the ability to undergo primary or secondary immune responses with any treatment protocol. In vivo investigations of the effects of cannabinoids on the thymus were also carried out. Thymus weight and thymus cell number were depressed in mice undergoing a primary humoral immune response when treated with THC (10 and 15 mg/kg) during this period. THC treatment, however, did not alter these parameters in mice not challenged with antigen. In both challenged and unchallenged animals, cannabinol and cannabidiol did not measurably alter the thymus.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".