Characterization of a Rabbit Kidney Prostaglandin F2α Receptor Exhibiting Gi-restricted Signaling That Inhibits Water Absorption in the Collecting Duct
Bibliographic record
Abstract
PGF(2alpha) is the most abundant prostaglandin detected in urine; however, its renal effects are poorly characterized. The present study cloned a PGF-prostanoid receptor (FP) from the rabbit kidney and determined the functional consequences of its activation. Nuclease protection assay showed that FP mRNA expression predominates in rabbit ovary and kidney. In situ hybridization revealed that renal FP expression predominates in the cortical collecting duct (CCD). Although FP receptor activation failed to increase intracellular Ca(2+), it potently inhibited vasopressin-stimulated osmotic water permeability (L(p), 10(-7) cm/(atm.s)) in in vitro microperfused rabbit CCDs. Inhibition of L(p) by the FP selective agonist latanoprost was additive to inhibition of vasopressin action by the EP selective agonist sulprostone. Inhibition of L(p) by latanoprost was completely blocked by pertussis toxin, consistent with a G(i)-coupled mechanism. Heterologous transfection of the rabbit FPr into HEK293 cells also showed that latanoprost inhibited cAMP generation via a pertussis toxin-sensitive mechanism but did not increase cell Ca(2+). These studies demonstrate a functional FP receptor on the basolateral membrane of rabbit CCDs. In contrast to the Ca(2+) signal transduced by other FP receptors, this renal FP receptor signals via a PT-sensitive mechanism that is not coupled to cell Ca(2+).
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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 | 0.001 |
| 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) | 0.001 | 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".