Agonist‐dependent cannabinoid receptor signalling in human trabecular meshwork cells
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Trabecular meshwork (TM) is an ocular tissue involved in the regulation of aqueous humour outflow and intraocular pressure (IOP). CB1 receptors (CB1) are present in TM and cannabinoid administration decreases IOP. CB1 signalling was investigated in a cell line derived from human TM (hTM). EXPERIMENTAL APPROACH: CB1 signalling was investigated using ratiometric Ca2+ imaging, western blotting and infrared In-Cell Western analysis. KEY RESULTS: WIN55212-2, a synthetic aminoalkylindole cannabinoid receptor agonist (10-100 microM) increased intracellular Ca2+ in hTM cells. WIN55,212-2-mediated Ca2+ increases were blocked by AM251, a CB1 antagonist, but were unaffected by the CB2 antagonist, AM630. The WIN55,212-2-mediated increase in [Ca2+]i was pertussis toxin (PTX)-insensitive, therefore, independent of Gi/o coupling, but was attenuated by a dominant negative Galpha(q/11) subunit, implicating a Gq/11 signalling pathway. The increase in [Ca2+]i was dependent upon PLC activation and mobilization of intracellular Ca2+ stores. A PTX-sensitive increase in extracellular signal-regulated kinase (ERK1/2) phosphorylation was also observed in response to WIN55,212-2, indicative of a Gi/o signalling pathway. CB1-Gq/11 coupling to activate PLC-dependent increases in Ca2+ appeared to be specific to WIN55,212-2 and were not observed with other CB1 agonists, including CP55,940 and methanandamide. CP55940 produced PTX-sensitive increases in [Ca2+]i at concentrations>or=15 microM, and PTX-sensitive increases in ERK1/2 phosphorylation. CONCLUSIONS AND IMPLICATIONS: This study demonstrates that endogenous CB1 couples to both Gq/11 and Gi/o in hTM cells in an agonist-dependent manner. Cannabinoid activation of multiple CB1 signalling pathways in TM tissue could lead to differential changes in aqueous humour outflow and IOP.
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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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".