Involvement of a cytoplasmic-tail serine cluster in urotensin II receptor internalization
Bibliographic record
Abstract
Most G-protein-coupled receptors that undergo agonist-dependent internalization require the presence of specific cytoplasmic-tail residues to initiate interactions with proteins of the endocytic machinery. Here we show that the UT receptor (urotensin II receptor) undergoes internalization, and that specific serine residues of the receptor's cytoplasmic tail participate in this process. We first observed a time-dependent increase in internalization of the UT receptor expressed in COS-7 cells following binding of the agonist urotensin II. This sequestration was significantly reduced in the presence of sucrose, demonstrating that the agonist-activated UT receptor is internalized in part by clathrin-coated pits. Moreover, the sequestered receptor was co-localized in endocytic vesicles with beta-arrestin1 and beta-arrestin2. To assess whether specific regions of the receptor's cytoplasmic tail were involved in internalization, five UT receptor mutants were constructed. In four constructs the receptor's cytoplasmic tail was truncated at various positions (UTDelta367, UTDelta363, UTDelta350 and UTDelta336), and in the other four adjacent serine residues at positions 364-367 were replaced by Ala (Mut4S). Each mutant, except UTDelta367, demonstrated a significantly reduced internalization rate, thereby revealing the importance of specific serine residues within the cytoplasmic tail of the UT receptor for its ability to be internalized efficiently.
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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 | 0.000 |
| 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 | 0.000 |
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".