Abstract 17470: NF-κB Activation Down Stream of Tuber Sclerosis Complex -mTOR Signaling pathway is Suppressed in Doxorubicin-Induced Cardiotoxicity
Bibliographic record
Abstract
The signaling networks that coordinate cell survival and cell death are poorly defined in the heart. The mammalian target of rapamycin (mTOR) is a highly conserved serine threonine kinase centrally involved in vital processes including growth, proliferation, and gene transcription. However, mTOR's role in regulating cell survival under normal or disease conditions has not been undetermined. Previously we established a cytoprotective role for the cellular factor NF-κB in ventricular myocytes. Notably, we demonstrated that NF-κB activation was necessary and sufficient for basal cell survival and suppressing mitochondrial perturbations during hypoxic injury. Herein, we provide new compelling evidence that activation of IKK-NF-κB signaling pathway down-stream of mTOR suppresses mitochondrial perturbations and cell death during metabolic stress imposed by nutrient deprivation or hypoxia. In contrast to wild type cells, constitutive activation of mTOR in tuber sclerosis complex (TSC) 2 -/- cells displayed marked increased mTOR targets p-P70S6, p-4EBP-1 and S6 protein. Interestingly, a significant increase in nuclear NF-κB activity and NF-κB gene transcription was also observed in TSC 2 -/- cells. Interestingly, in in vivo and in vitro models of Doxorubicin (Dox) -induced cardiotoxicity we observed a marked reduction in mTOR and NF-κB activity. However, basal NF-κB activity and cell viability were significantly reduced upon mTOR inactivation following metabolic stress or hypoxia. Moreover, basal Bnip3 gene transcription and cell death were significantly increased in cells treated with DOX and defective for mTOR activity. IKKβ- mediated activation of NF-κB restored mTOR activity and suppressed cell death induced by Bnip3 in DOX treated cells. To our knowledge our data provide the first direct evidence that operationally links mTOR and cell survival via IKKβ-NF-κB mediated repression of Bnip3.
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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) | 0.003 | 0.001 |
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".