Biochemical Characterization of β2-Adrenergic Receptor Dimers and Oligomers
Bibliographic record
Abstract
G Protein-coupled receptor dimerization/oligomerization has been well established during the last several years. Studies have demonstrated the existence of dimers/digomers both in vitro and in living cells. However, a thorough characterization of the biochemical nature of receptor dimers and oligomers as well as their occurrence at the cell surface has not been properly addressed. In this study, we show that both beta2-adrenergic receptor (beta2AR) dimers and oligomers exist at the plasma membrane and that the detection of such species, following receptor solubilization and resolution by denaturing polyacrylamide gel electrophoresis (SDS-PAGE), does not result from the formation of spurious disulfide bonds during cell lysis. Moreover, our results indicate that the biochemical nature of beta2AR dimers is different from that of the oligomers. Although both complexes are partially resistant to SDS denaturation, disulfide bonding is absolutely required for the stability of beta2AR oligomers but not dimers in SDS-PAGE. Indeed, dimeric species can be detected even in the presence of high concentrations of reducing and alkylating agents. Although the different biochemical nature of the dimers and oligomers may be indicative of distinct biological roles in cells, additional studies will be required to further elucidate the biosynthesis and function of these receptor forms.
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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 | 0.001 | 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) | 0.001 | 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".