2-Arachidonoyl-glycerol- and arachidonic acid-stimulated neutrophils release antimicrobial effectors against<i>E. coli, S. aureus</i>, HSV-1, and RSV
Bibliographic record
Abstract
The endocannabinoid 2-AG is highly susceptible to its hydrolysis into AA, which activates neutrophils through de novo LTB(4) biosynthesis, independently of CB activation. In this study, we show that 2-AG and AA stimulate neutrophils to release antimicrobial effectors. Supernatants of neutrophils activated with nanomolar concentrations of 2-AG and AA indeed inhibited the infectivity of HSV-1 and RSV. Additionally, the supernatants of 2-AG- and AA-stimulated neutrophils strongly impaired the growth of Escherichia coli and Staphylococcus aureus. This correlated with the release of a large amount (micrograms) of α-defensins, as well as a limited amount (nanograms) of LL-37. All the effects of AA and 2-AG mentioned above were prevented by inhibiting LTB(4) biosynthesis or by blocking BLT(1). Importantly, neither CB(2) receptor agonists nor antagonists could mimic nor prevent the effects of 2-AG, respectively. In fact, qPCR data show that contaminating eosinophils express ∼100-fold more CB(2) receptor mRNA than purified neutrophils, suggesting that CB(2) receptor expression by human neutrophils is limited and that contaminating eosinophils are likely responsible for the previously documented CB(2) expression by freshly isolated human neutrophils. The rapid conversion of 2-AG to AA and their subsequent metabolism into LTB(4) promote 2-AG and AA as multifunctional activators of neutrophils, mainly exerting their effects by activating the BLT(1). Considering that nanomolar concentrations of AA or 2-AG were sufficient to impair viral infectivity, this suggests potential physiological roles for 2-AG and AA as regulators of host defense in vivo.
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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) | 0.001 | 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 | 0.001 |
| 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".