[beta]1 adrenergic receptor ([beta]1AR)‐epidermal growth factor receptor (EGFR) interaction regulates ERK cellular activity
Bibliographic record
Abstract
Recently, we showed that β1AR stimulation mediates transactivation of the EGFR and induces ERK activation in a βarrestin‐dependent manner to confer cardioprotection. However, ERK activation is associated with increased cardiac growth and hypertrophy, frequently a detrimental process in the failing heart. Therefore, we hypothesized that the β1AR and EGFR form a βarrestin‐dependent signaling complex in which ERK may be differentially targeted within the cell. Here, via (A) confocal microscopy, (B) immunoprecipitation and (C) FRET‐based assays, we show the physical association between β1AR and EGFR in a HEK 293 cell‐based system that is regulated by agonist stimulation. The interaction between β1AR and EGFR and the stimulation‐induced recruitment of βarrestin to the receptor complex is dependent on G protein receptor‐coupled kinase (GRK) phosphorylation sites in the C‐terminal tail of β1AR. While both β1AR stimulation and EGF ligand induce EGFR activation, EGF ligand causes translocation of activated ERK to the nucleus, whereas β1AR‐activated ERK is restricted to the cytoplasm. These data reveal a new signaling paradigm in which a β 1 AR‐EGFR‐βarrestin complex acts to retain activated ERK in the cytoplasm, resulting in differential intracellular targeting of ERK signaling. Supported by the Heart and Stroke Foundation of Canada and the National Institutes of Health.
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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 | 0.001 |
| 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".