Cannabinoids Alleviate the LPS-Induced Cytokine Storm via Attenuating NLRP3 Inflammasome Signaling and TYK2-Mediated STAT3 Signaling Pathways In Vitro
Bibliographic record
Abstract
because of their several pharmaceutical properties. Current evidence suggests a crucial role of cannabinoids as potent anti-inflammatory agents for the treatment of chronic inflammatory diseases; however, the mechanisms remain largely unclear. Cytokine storm, a dysregulated severe inflammatory response by our immune system, is involved in the pathogenesis of numerous chronic inflammatory disorders, including coronavirus disease 2019 (COVID-19), which results in the accumulation of pro-inflammatory cytokines. Therefore, we hypothesized that CBD and THC reduce the levels of pro-inflammatory cytokines by inhibiting key inflammatory signaling pathways. The nucleotide-binding and oligomerization domain (NOD)-like receptor family pyrin domain-containing 3 (NLRP3) inflammasome signaling has been implicated in a variety of chronic inflammatory diseases, which results in the release of pyroptotic cytokines, interleukin-1β (IL-1β) and IL-18. Likewise, the activation of the signal transducer and activator of transcription-3 (STAT3) causes increased expression of pro-inflammatory cytokines. We studied the effects of CBD and THC on lipopolysaccharide (LPS)-induced inflammatory response in human THP-1 macrophages and primary human bronchial epithelial cells (HBECs). Our results revealed that CBD and, for the first time, THC significantly inhibited NLRP3 inflammasome activation following LPS + ATP stimulation, leading to a reduction in the levels of IL-1β in THP-1 macrophages and HBECs. CBD attenuated the phosphorylation of nuclear factor-κB (NF-κB), and both cannabinoids inhibited the generation of oxidative stress post-LPS. Our multiplex ELISA data revealed that CBD and THC significantly diminished the levels of IL-6, IL-8, and tumor necrosis factor-α (TNF-α) after LPS treatment in THP-1 macrophages and HBECs. In addition, the phosphorylation of STAT3 was significantly downregulated by CBD and THC in THP-1 macrophages and HBECs, which was in turn attributed to the reduced phosphorylation of tyrosine kinase-2 (TYK2) by CBD and THC after LPS stimulation in these cells. Overall, CBD and THC were found to be effective in alleviating the LPS-induced cytokine storm in human macrophages and primary HBECs, at least via modulation of NLRP3 inflammasome and STAT3 signaling pathways. The encouraging results from this study warrant further investigation of these cannabinoids in vivo.
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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) | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".