Receptor‐mediated effects of Δ<sup>9</sup>‐tetrahydrocannabinol and cannabidiol on the inflammatory response of alveolar macrophages
Bibliographic record
Abstract
Abstract Δ 9 ‐Tetrahydrocannabinol (Δ 9 ‐THC) and cannabidiol (CBD) are cannabinoids found in Cannabis sativa . While research supports cannabinoids reduce inflammation, the consensus surrounding receptor(s)‐mediated effects has yet to be established. Here, we investigated the receptor‐mediated properties of Δ 9 ‐THC and CBD on alveolar macrophages, an important pulmonary immune cell in direct contact with cannabinoids inhaled by cannabis smokers. MH‐S cells, a mouse alveolar macrophage cell line, were exposed to Δ 9 ‐THC and CBD, with and without lipopolysaccharide (LPS). Outcomes included RNA‐sequencing and cytokine analysis. Δ 9 ‐THC and CBD alone did not affect the basal transcriptional response of MH‐S cells. In response to LPS, Δ 9 ‐THC and CBD significantly reduced the expression of numerous proinflammatory cytokines including tumor necrosis factor‐alpha, interleukin (IL)‐1β and IL‐6, an effect that was dependent on CB 2 . The anti‐inflammatory effects of CBD but not Δ 9 ‐THC were mediated through a reduction in signaling through nuclear factor‐kappa B and extracellular signal‑regulated protein kinase 1/2. These results suggest that CBD and Δ 9 ‐THC have potent immunomodulatory properties in alveolar macrophages, a cell type important in immune homeostasis in the lungs. Further investigation into the effects of cannabinoids on lung immune cells could lead to the identification of therapies that may ameliorate conditions characterized by inflammation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".