Discovery of new antagonists aimed at discriminating <scp>UII</scp> and <scp>URP</scp>‐mediated biological activities: insight into <scp>UII</scp> and <scp>URP</scp> receptor activation
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Recent evidence suggested that urotensin II (UII) and its paralog peptide UII-related peptide (URP) might exert common but also divergent physiological actions. Unfortunately, none of the existing antagonists were designed to discriminate specific UII- or URP-associated actions, and our understanding, on how these two endogenous peptides can trigger different, but also common responses, is limited. EXPERIMENTAL APPROACH: Ex vivo rat and monkey aortic ring contraction as well as dissociation kinetics studies using transfected CHO cells expressing the human urotensin (UT) receptors were used in this study. KEY RESULTS: Ex vivo rat and monkey aortic ring contraction studies revealed the propensity of [Pep(4)]URP to decrease the maximal response of human UII (hUII) without any significant change in potency, whereas no effect was noticeable on the URP-induced vasoconstriction. Dissociation experiments demonstrated the ability of [Pep(4)]URP to increase the dissociation rate of hUII, but not URP. Surprisingly, URP, an equipotent UII paralog, was also able to accelerate the dissociation rate of membrane-bound (125)I-hUII, whereas hUII had no noticeable effect on URP dissociation kinetics. Further experiments suggested that an interaction between the glutamic residue at position 1 of hUII and the UT receptor seems to be critical to induce conformational changes associated with agonistic activation. Finally, we demonstrated that the N-terminal domain of the rat UII isoform was able to act as a specific antagonist of the URP-associated actions. CONCLUSION: Such compounds, that is [Pep(4)]URP and rUII(1-7), should prove to be useful as new pharmacological tools to decipher the specific role of UII and URP in vitro but also in vivo.
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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 | 0.000 |
| 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 | 0.001 |
| 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".