Endoplasmic Reticulum Stress Promotes iNOS/NO and Influences Inflammation in the Development of Doxorubicin-Induced Cardiomyopathy
Bibliographic record
Abstract
Doxorubicin (Dox) is known to cause heart failure in some cancer patients. Despite extensive studies over the past half century, the subcellular basis of Dox-induced cardiomyopathy (DIC) is still elusive. Earlier, we suggested that Dox causes a delayed activation of unfolded protein response (UPR) which may promote mitochondrial Bax activity leading to cardiomyocyte death. As a follow up, using NO donor, S-Nitroso-N-acetyl-d,l-penicillamine (SNAP), and/or NOS inhibitor, N(ω)-nitro-L-arginine methyl ester (L-NAME), we now show that endoplasmic reticulum (ER) stress promotes inflammation through iNOS/NO-induced TLR2 activation. In vivo Dox treatment increased mitochondrial iNOS to promote ER stress as there was an increase in Bip (Grp78) response, proapoptotic CHOP (DDIT3) and ER-mediated Caspase 12 activation. Increased iNOS activity is associated with an increase in TLR2 and TNF-α receptor associated factor 2 (TRAF2). These two together with NF-κB p105/50 expression and a synergistic support through ER stress, promote inflammatory response in the myocardium leading to cell death and ultimately fostering DIC conditions. In the presence of NOS inhibitor, such detrimental effects of Dox were inhibited, suggesting iNOS/NO as key mediators of Dox-induced inflammatory as well as apoptotic responses.
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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".