[<sup>125</sup>I]‐GR231118: a high affinity radioligand to investigate neuropeptide Y Y<sub>1</sub> and Y<sub>4</sub> receptors
Bibliographic record
Abstract
GR231118 (also known as 1229U91 and GW1229), a purported Y(1) antagonist and Y(4) agonist was radiolabelled using the chloramine T method. [(125)I]-GR231118 binding reached equilibrium within 10 min at room temperature and remained stable for at least 4 h. Saturation binding experiments showed that [(125)I]-GR231118 binds with very high affinity (K(d) of 0.09 - 0.24 nM) in transfected HEK293 cells with the rat Y(1) and Y(4) receptor cDNA and in rat brain membrane homogenates. No specific binding sites could be detected in HEK293 cells transfected with the rat Y(2) or Y(5) receptor cDNA demonstrating the absence of significant affinity of GR231118 for these two receptor classes. Competition binding experiments revealed that specific [(125)I]-GR231118 binding in rat brain homogenates is most similar to that observed in HEK293 cells transfected with the rat Y(1), but not rat Y(4), receptor cDNA. Autoradiographic studies demonstrated that [(125)I]-GR231118 binding sites were fully inhibited by the Y(1) antagonist BIBO3304 in most areas of the rat brain. Interestingly, high percentage of [(125)I]-GR231118/BIBO3304-insensitive binding sites were detected in few areas. These [(125)I]-GR231118/BIBO3304-insensitive binding sites likely represent labelling to the Y(4) receptor subtype. In summary, [(125)I]-GR231118 is a new radiolabelled probe to investigate the Y(1) and Y(4) receptors; its major advantage being its high affinity. Using highly selective Y(1) antagonists such as BIBO3304 or BIBP3226 it is possible to block the binding of [(125)I]-GR231118 to the Y(1) receptor allowing for the characterization and visualization of the purported Y(4) subtype. British Journal of Pharmacology (2000) 129, 37 - 46
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".