Egr-1 negatively regulates expression of the sodium?calcium exchanger-1 in cardiomyocytes in vitro and in vivo
Bibliographic record
Abstract
OBJECTIVE: Increased expression of the transcription factor early growth response gene-1 (Egr-1) accompanies catecholamine infusion. Catecholamine-treated, Egr-1-deficient (-/-) mice show exacerbated cardiac damage when compared to similarly treated wild-type (+/+) mice, suggesting that Egr-1 reduces heart damage. We sought to identify Egr-1-mediated cardiac sparing genes. METHODS: Microarray analyses identified increased sodium calcium exchanger-1 (NCX1) expression in catecholamine-treated -/- mice. Immunoblots assessed NCX1 expression in +/+, -/-, and transgenic mice overexpressing Egr-1 in heart and cardiac differentiated H9c2 cells harboring wild-type Egr-1 (wtEgr-1) or NAB-binding ablating mutations. Chromatin immunoprecipitation (ChIP) used anti-Egr-1 antibody coupled to amplification of purified Egr-1/associated DNA. RESULTS: Immunoblots revealed a two- to threefold increase in NCX1 in catecholamine-stimulated and naive -/- versus +/+ mice. In contrast, transgenic mice overexpressing Egr-1 in heart had 30% of normal NCX1 protein. Thus, the in vivo data indicate that Egr-1 negatively controls NCX1 expression. In vitro cardiac differentiated H9c2 cells overexpressing wtEgr-1 also showed 30% NCX1 expression. However, cells overexpressing NAB-ablating Egr-1 mutations showed four- to fivefold increased NCX1 expression. NCX1 promoter DNA was specifically amplified from Egr-1/associated DNA. Thus, the in vitro results indicate that Egr-1/NAB interactions are critical for NCX1 repression at the NCX1 promoter. CONCLUSIONS: NCX1 is responsible for calcium exit from cardiomyocytes, and continued overexpression is thought to be detrimental. We propose that one way Egr-1 action is cardiac sparing is by promoting a reduction in NCX1 expression.
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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) | 0.001 | 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".