Endocannabinoid hydrolysis inhibition unmasks that unsaturated fatty acids induce a robust biosynthesis of 2‐arachidonoyl‐glycerol and its congeners in human myeloid leukocytes
Bibliographic record
Abstract
The endocannabinoid (eCB) 2-arachidonoyl-gycerol (2-AG) modulates immune responses by activating cannabinoid receptors or through its multiple metabolites, notably eicosanoids. Thus, 2-AG hydrolysis inhibition might represent an interesting anti-inflammatory strategy that would simultaneously increase the levels of 2-AG and decrease those of eicosanoids. Accordingly, 2-AG hydrolysis inhibition increased 2-AG half-life in neutrophils. Under such setting, neutrophils, eosinophils, and monocytes synthesized large amounts of 2-AG and other monoacylglycerols (MAGs) in response to arachidonic acid (AA) and other unsaturated fatty acids (UFAs). Arachidonic acid and UFAs were ~1000-fold more potent than G protein-coupled receptor (GPCR) agonists. Triascin C and thimerosal, which, respectively, inhibit fatty acyl-CoA synthases and acyl-CoA transferases, prevented the UFA-induced MAG biosynthesis, implying glycerolipid remodeling. 2-AG and other MAG biosynthesis was preceded by that of the corresponding lysophosphatidic acid (LPA). However, we could not directly implicate LPA dephosphorylation in MAG biosynthesis. While GPCR agonists poorly induced 2-AG biosynthesis, they inhibited that induced by AA by 25%-50%, suggesting that 2-AG biosynthesis is decreased when leukocytes are surrounded by a pro-inflammatory entourage. Our data strongly indicate that human leukocytes use AA and UFAs to biosynthesize biologically significant concentrations of 2-AG and other MAGs and that hijacking the immune system with 2-AG hydrolysis inhibitors might diminish inflammation in humans.
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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 | 0.001 |
| 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".