Distinct Pathways Regulate Proapoptotic Nix and BNip3 in Cardiac Stress
Bibliographic record
Abstract
Up-regulation of myocardial Nix and BNip3 is associated with apoptosis in cardiac hypertrophy and ischemia, respectively. To identify mechanisms of gene regulation for these critical cardiac apoptosis effectors, the determinants of Nix and BNip3 promoter activation were elucidated by luciferase reporter gene expression in neonatal rat cardiac myocytes. BNip3 transcription was increased by hypoxia but not by phenylephrine (10 microM), angiotensin II (100 nM), or isoproterenol (10 microM). In contrast, Nix transcription was increased by phenylephrine but not by isoproterenol, angiotensin II, or hypoxia. Since phenylephrine stimulates cardiomyocyte hypertrophy via protein kinase C (PKC), the effects of phorbol myristate acetate (PMA, 10 nM for 24 h) and adenoviral PKC expression were assessed. PMA and PKC alpha, but not PKC epsilon or dominant negative PKC alpha, increased Nix transcription. Multiple Nix promoter GC boxes bound transcription factor Sp-1, and basal and PMA- or PKC alpha-stimulated Nix promoter activity was suppressed by mithramycin inhibition of Sp1-DNA interactions. In vivo determinants of Nix expression were evaluated in Nix promoter-luciferase (NixP) transgenic mice that underwent ischemia-reperfusion (1 h/24 h), transverse aortic coarctation (TAC), or cross-breeding with the G(q) overexpression model of hypertrophy. Luciferase activity increased in G alpha(q)-NixP hearts 3.2 +/- 0.4-fold and in TAC hearts 2.8 +/- 0.4-fold but did not increase with infarction-reperfusion. NixP activity was proportional to the extent of TAC hypertrophy and was inhibited by mithramycin. These studies revealed distinct mechanisms of transcriptional regulation for cardiac Nix and BNip3. BNip3 is hypoxia-inducible, whereas Nix expression was induced by G alpha(q)-mediated hypertrophic stimuli. PKC alpha, a G(q) effector, transduced Nix transcriptional induction via Sp1.
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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".