Peroxynitrite Is a Major Contributor to Cytokine-Induced Myocardial Contractile Failure
Bibliographic record
Abstract
Proinflammatory cytokines depress myocardial contractile function by enhancing the expression of inducible NO synthase (iNOS), yet the mechanism of iNOS-mediated myocardial injury is not clear. As the reaction of NO with superoxide to form peroxynitrite markedly enhances the toxicity of NO, we hypothesized that peroxynitrite itself is responsible for cytokine-induced cardiac depression. Isolated working rat hearts were perfused for 120 minutes with buffer containing interleukin-1 beta, interferon-gamma, and tumor necrosis factor-alpha. Cardiac mechanical function and myocardial iNOS, xanthine oxidoreductase (XOR), and NAD(P)H oxidase activities (sources of superoxide) were measured during the perfusion. Cytokines induced a marked decline in myocardial contractile function accompanied by enhanced activity of myocardial XOR, NADH oxidase, and iNOS. Cardiac NO content, myocardial superoxide production, and perfusate nitrotyrosine and dityrosine levels, markers of peroxynitrite, were increased in cytokine-treated hearts. The peroxynitrite decomposition catalyst FeTPPS (5,10,15, 20-tetrakis-[4-sulfonatophenyl]-porphyrinato-iron[III]), the NO synthase inhibitor N(G)-nitro-L-arginine, and the superoxide scavenger tiron each inhibited the decline in myocardial function and decreased perfusate nitrotyrosine levels. Proinflammatory cytokines stimulate the concerted enhancement in superoxide and NO-generating activities in the heart, thereby enhancing peroxynitrite generation, which causes myocardial contractile failure.
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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".