Protective effect of the RGS2‐eIF2Bε binding domain (RGS2 <sup>eb</sup> ) in cardiac hypertrophy
Bibliographic record
Abstract
Regulator of G protein signalling 2 (RGS2) is known to play a protective role in maladaptive cardiac hypertrophy and heart failure via its ability to inhibit Gq and Gs mediated GPCR signalling. Recently, we have demonstrated that RGS2 can also inhibit protein translation, which would be expected to attenuate cell growth. This novel, G protein‐independent inhibitory effect has been mapped to a 37 a.a. domain ( RGS2 eb ) within RGS2 that binds to eukaryotic initiation factor 2B (eIF2B). When expressed on its own in neonatal rat cardiomyocytes, RGS2 eb attenuates both protein synthesis and hypertrophy induced by Gq and Gs activating agents. The objective of this study is to further elucidate the cardioprotective role of RGS2 eb by determining whether mice with targeted cardiac expression of RGS2 eb show resistance to the development of hypertrophy in comparison to wild‐type (WT) controls. Cardiac hypertrophy was induced by one month of transverse aortic constriction (TAC). RGS2 eb transgenic mice were found to have a significantly lower left ventricle/body weight ratio compared to WT TAC mice. In addition, the expression of hypertrophy markers, such as alpha natriuretic peptide (ANP), was decreased in RGS2 eb TAC mice compared to WT TAC animals. These results suggest that RGS2 eb , via its inhibition of protein synthesis, may be decreasing the severity of cardiac hypertrophy and aiding in the maintenance of cardiac function.
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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) | 0.002 | 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".