A farnesyltransferase inhibitor attenuated β-adrenergic receptor downregulation in rat skeletal muscle
Bibliographic record
Abstract
Farnesylation represents an essential posttranslational modification of several well-defined proteins implicated in the homologous desensitization of the beta-adrenergic receptor (beta-ADR). The following study examined the effect of a novel farnesyltransferase inhibitor, BMS-191563, on agonist-mediated beta-ADR downregulation in skeletal muscle. Female Sprague-Dawley rats were treated for 12 days with the beta2-adrenergic agonist clenbuterol (4 mg/kg) with or without the concurrent administration of BMS-191563 (2 mg x kg(-1) x day(-1)). Clenbuterol promoted gastrocnemius muscle hypertrophy, whereas the soleus muscle was unaffected. Total beta-ADR density was decreased by 45 and 40% in the soleus and medial gastrocnemius (MG), respectively, after clenbuterol treatment. BMS-191563 treatment did not prevent clenbuterol-stimulated MG hypertrophy, but markedly attenuated beta-ADR downregulation in both muscle types. This latter effect in the soleus muscle was not associated with the inhibition of Ras farnesylation. Likewise, in rat cardiac fibroblasts, isoproterenol-mediated decrease of total beta-ADR density was abrogated by the prior treatment with BMS-191563. Collectively, these data demonstrate that the mechanism(s) implicated in agonist-mediated beta-ADR downregulation was sensitive to BMS-191563, thereby suggesting the involvement of farnesylated proteins.
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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 | 0.000 |
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".