Pharmacological and Molecular Biological (RT-PCR) Characterization of Functional TP Prostanoid Receptors in Immortalized Human Non-Pigmented Ciliary Epithelial Cells
Bibliographic record
Abstract
Immortalized human non-pigmented ciliary epithelial (NPE) cells (ODM-2) were shown to express the mRNA for the prostanoid TPalpha but not the TPbeta receptor using reverse transcription-polymerase chain reaction (RT-PCR). These TPalpha receptors were coupled to phospholipase C (PLC) and, thus, promoted phosphoinositide (PI) turnover. TP receptor agonists yielded the following potencies (EC50S) in the PI turnover assays: I-BOP = 8.2 +/- 1.1 nM; carbocyclic TA2 = 87.5 +/- 25.3 nM; U-44069 = 1.16 +/- 0.32 microM; U-46619 = 1.2 +/- 0.2 microM (n = 4-17). Agonists selective for other prostanoid receptor subtypes (e.g., fluprostenol and sulprostone) were inactive. The agonist effects of U-44619 and I-BOP were potently blocked, in an apparent non-competitive manner (ki = 53.9 +/- 12 nM; pA2s = 7.6-7.8; pKbs = 7.38), by the TP receptor-selective antagonist, SQ29,548, but were unaffected by other prostanoid receptor antagonists (e.g., AH6809, AL-8810). The PLC inhibitor (U73122) inhibited U-46619-induced PI turnover (IC50 = 4.3 +/- 0.6 microM). The functional potencies of the compounds stimulating or inhibiting the TP receptor-mediated PI turnover in the NPE cells correlated well with the TP receptor binding affinities of these compounds at human platelet TP receptors (r = 0.98). These studies have shown the presence of the mRNA for and the expression of functional TPalpha receptors coupled to PLC in human NPE cells. The TPalpha receptors on NPE cells may be responsible for inhibiting aqueous humor production and may help explain the intraocular pressure-lowering effects of certain TP agonists.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".