MKP1 inhibits myocardial TNF‐alpha expression and improves cardiac function in endotoxemia
Bibliographic record
Abstract
The objective of this study was to investigate the role of mitogen‐activated protein kinase phosphatase‐1 (MKP1) pathway in myocardial tumor necrosis factor (TNF)‐alpha expression and cardiac function during endotoxemia. Experiments were carried out in a mouse model of endotoxemia and in cultured neonatal cardiomyocytes. Lipopolysaccharide (LPS) increased MKP1 expression in the heart and in cultured neonatal cardiomyocytes. LPS‐induced ERK1/2 and p38 phosphorylation in the myocardium was prolonged in MKP1 −/− mice. Myocardial TNF‐alpha mRNA and protein levels were enhanced in MKP1 −/− compared to WT mice in endotoxemia, leading to a further decrease in cardiac function. Inhibition of Rac1 and PAK1 by a dominant negative Rac1 adenovirus (Ad‐Rac1N17) and PAK1 siRNA, respectively blocked LPS‐induced MKP1 expression in cardiomyocytes. PAK1 siRNA also decreased p38 and c‐Jun N‐terminal kinase (JNK) activation, and TNF‐alpha expression induced by LPS. Furthermore, deficiency in either Rac1 or JNK1 decreased myocardial MKP1 expression in endotoxemic mice. In conclusion, LPS increases myocardial MKP1 expression via JNK1. MKP1 attenuates ERK1/2 and p38 activation, inhibits myocardial TNF‐alpha expression and improves cardiac function in endotoxemia. Thus, MKP1 represents an important negative feedback mechanism limiting pro‐inflammatory response in the heart during sepsis.
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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) | 0.001 | 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) | 0.001 | 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".