Urine concentrating defect in prostaglandin EP<sub>1</sub>-deficient mice
Bibliographic record
Abstract
We investigated the role of the prostaglandin E(2) (PGE(2)) EP(1) receptor in modulating urine concentration as it is expressed along the renal collecting duct where arginine-vasopressin (AVP) exerts its anti-diuretic activity, and in the paraventricular and supraoptic nuclei of the hypothalamus where AVP is synthesized. The urine osmolality of EP(1)-null mice (EP(1)(-/-)) failed to match levels achieved by wild-type (WT) counterparts upon water deprivation (WD) for 24 h. This difference was reflected by higher plasma osmolality in WD EP(1)(-/-) mice. Along the collecting duct, the induction and subapical to plasma membrane translocation of the aquaporin-2 water channel in WD EP(1)(-/-) mice appeared equivalent to that of WD WT mice as determined by quantitative RT-PCR and immunohistochemistry. However, medullary interstitial osmolalities dropped significantly in EP(1)(-/-) mice following WD. Furthermore, urinary AVP levels of WD EP(1)(-/-) mice were significantly lower than those of WD WT mice. This deficit could be traced back to a blunted induction of hypothalamic AVP mRNA expression in WD EP(1)(-/-) mice as determined by quantitative RT-PCR. Administration of the AVP mimetic [deamino-Cys(1),D-Arg(8)]-vasopressin restored a significant proportion of the urine concentrating ability of WD EP(1)(-/-) mice. When mice were water loaded to suppress endogenous AVP production, urine osmolalities increased equally for WT and EP(1)(-/-) mice. These data suggest that PGE(2) modulates urine concentration by acting at EP(1) receptors, not in the collecting duct, but within the hypothalamus to promote AVP synthesis in response to acute WD.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".