Nuclear Factor-κB–Mediated Cell Survival Involves Transcriptional Silencing of the Mitochondrial Death Gene BNIP3 in Ventricular Myocytes
Bibliographic record
Abstract
BACKGROUND: A survival role for the transcription factor nuclear factor-kappaB (NF-kappaB) in ventricular myocytes has been reported; however, the underlying mechanism is undefined. In this report we provide new mechanistic evidence that survival signals conferred by NF-kappaB impinge on the hypoxia-inducible death factor BNIP3. METHODS AND RESULTS: Activation of the NF-kappaB signaling pathway by IKKbeta in ventricular myocytes suppressed mitochondrial permeability transition pore (PTP) opening and cell death provoked by BNIP3. Expression of IKKbeta or p65 NF-kappaB suppressed basal and hypoxia-inducible BNIP3 gene activity. Deletion analysis of the BNIP3 promoter revealed the NF-kappaB elements to be crucial for inhibiting basal and inducible BNIP3 gene activity. Cells derived from p65(-/-)-deficient mice or ventricular myocytes rendered defective for NF-kappaB signaling with a nonphosphorylative IkappaB exhibited increased basal BNIP3 gene expression, mitochondrial PTP, and cell death. Genetic or functional ablation of the BNIP3 gene in NF-kappaB-defective myocytes rescued them from mitochondrial defects and cell death. CONCLUSIONS: The data provide new compelling evidence that NF-kappaB suppresses mitochondrial defects and cell death of ventricular myocytes through a mechanism that transcriptionally silences the death gene BNIP3. Collectively, our data provide new mechanistic insight into the mode by which NF-kappaB suppresses cell death and identify BNIP3 as a key transcriptional target for NF-kappaB-regulated expression in ventricular myocytes.
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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) | 0.001 | 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".