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Cannabinoids Alleviate the LPS-Induced Cytokine Storm via Attenuating NLRP3 Inflammasome Signalling and TYK2-Mediated STAT3 Signalling Pathways <em>In Vitro</em>

2022· preprint· en· W4226439324 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePreprints.org · 2022
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammasome and immune disorders
Canadian institutionsUniversity of Lethbridge
FundersMitacs
KeywordsInflammasomeCytokineProinflammatory cytokineSignal transductionPharmacologyInflammationImmunologyBiologyChemistryCell biology

Abstract

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Cannabinoids, mainly cannabidiol (CBD) and Δ9-tetrahydrocannabinol (THC), are the most studied group of compounds obtained from Cannabis sativa 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 signalling pathways. The nucleotide-binding and oligomerization domain (NOD)-like receptor family pyrin domain-containing 3 (NLRP3) inflammasome signalling 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 signalling pathways. The encouraging results from this study warrant further investigation of these cannabinoids in vivo.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.037
GPT teacher head0.268
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it