JNK1/c-fos inhibits cardiomyocyte TNF- expression via a negative crosstalk with ERK and p38 MAPK in endotoxaemia
Bibliographic record
Abstract
AIMS: Myocardial tumour necrosis factor-alpha (TNF-alpha) production plays an important role in cardiac dysfunction during sepsis. The aim of this study was to investigate the role of c-Jun NH2-terminal kinases (JNK) signalling in cardiomyocyte TNF-alpha expression during lipopolysaccharide (LPS) stimulation and myocardial function in endotoxaemic mice. METHODS AND RESULTS: In cultured neonatal mouse cardiomyocytes, deficiency of JNK1 or selective inhibition of JNK1 signalling by over-expression of a dominant negative mutant of JNK1 enhanced LPS-induced TNF-alpha expression, which was associated with elevations in phosphorylation of extracellular signal-regulated kinase (ERK)1/2 and p38 mitogen-activated protein kinase (MAPK). At the organ level, LPS-induced TNF-alpha expression was significantly increased in JNK1(-/-) compared with wild-type hearts. JNK1 activation by LPS also induced immediate c-fos expression in cardiomyocytes, which was blocked by inhibition of JNK1 signalling. The role of c-fos expression in LPS-induced TNF-alpha expression was investigated in both cultured c-fos(-/-) cardiomyocytes and isolated c-fos(-/-) hearts. Deficiency of c-fos significantly enhanced LPS-induced TNF-alpha expression in cardiomyocytes and isolated hearts. Over-expression of c-fos decreased TNF-alpha expression in LPS-stimulated cardiomyocytes, which was associated with a decrease in phosphorylation of ERK1/2 and p38. In mice with endotoxaemia, deficiency of either JNK1 or c-fos further decreased cardiac function compared with corresponding wild-type controls. CONCLUSION: JNK1/c-fos inhibits ERK1/2 and p38 MAPK signalling, leading to decreased cardiomyocyte TNF-alpha expression and improvements in cardiac function during endotoxaemia.
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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) | 0.002 | 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".