New AKT-dependent mechanisms of anti-COVID-19 action of high-CBD Cannabis sativa extracts
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.
Bibliographic record
Abstract
COVID-19 is caused by the SARS-CoV-2 virus, which enters target cells via interactions with ACE2 and TMPRSS2. Here, we show AKT serine/threonine kinase-dependent epigenetic control of ACE2 and TMPRSS2 expression by high-cannabidiol (CBD) cannabis extracts and their individual components. CBD alone and extracts #1, #5, #7, and #129 downregulated ACE2 and TMPRSS2 in lung fibroblast WI-38 cells through AKT-mediated inhibition. miR-200c-3p and let-7a-5p were two contributing miRNAs in CBD-mediated suppression of ACE2 and TMPRSS2. CBD and terpene PTWT2.2 profoundly inhibited ACE2 and TMPRSS2 expression, both individually and in combination. Extracts #1, #5, #7, and #169 suppressed COX2 expression and remarkably attenuated TNFα/IFNγ-triggered induction of proinflammatory factors IL-6 and IL-8 by AKT pathway. The most abundant molecules present in extracts #1 and #7 modulated the expression of COX2, IL-6, and IL-8 both individually and in combination. These results reveal that high-CBD cannabis extracts attenuated ACE2 and TMPRSS2 expression and the induction of inflammatory mediators COX2, IL-6, and IL-8 via the AKT pathway, highlighting their potential anti-COVID-19 features.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.002 | 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 it