Abstract 15960: Activation of TRAF2-NF-κB Signaling suppresses Mitochondrial Perturbations in Doxorubicin Cardiotoxicity
Bibliographic record
Abstract
Doxorubicin (dox) is a highly effective anti-tumour agent, however, its use is limited by its protracted and cardiotoxic effects that manifest as heart failure. The canonical NFκB signaling pathway has been suggested to play a critical survival role in cardiac myocytes. Herein, we demonstrate that, impaired TRAF2 signaling disrupts NFκB activation in hearts of mice treated with dox (20mg/kg) or ventricular myocytes treated with dox (10μM). This was accompanied by severe ultrastructural defects including vacuolization, mitochondrial perturbations including mPTP, loss of [[Unable to Display Character: ∆]]Ψm and ROS production. Further we investigated role of TRAF2 on IKKβ- NFκB signaling in ventricular myocytes. Interestingly, TRAF2 mediated K-63 poly-ubiquitination of Receptor Interacting Protein 1 (RIP1) which recruits Tak-1 complex and activates IKKβ -NF-κB signaling was impaired in cells treated with dox. This coincided with a marked increase in expression and mitochondrial targeting of the Bcl-2 death protein Bnip3. Interestingly, expression of wild type TRAF2 but not the ring finger domain mutant defective for ubiquitination, restored TAK1-IKKβ-NF-κB signaling and suppressed Bnip3 gene activation in cells treated with dox. Concordant with TRAF2’s ability to suppress Bnip3, was accompanied by reduction in dox induced mPTP, ROS and cell death. Hence, our findings reveal a novel signaling pathway that functionally couples TRAF2 mediated NF-κB signaling to mitochondrial function and survival of cardiac 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) | 0.001 | 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) | 0.006 | 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".