Inhibition of p38 MAPK decreases myocardial TNF-alpha expression and improves myocardial function and survival in endotoxemia
Bibliographic record
Abstract
OBJECTIVES: The role of p38 mitogen-activated protein kinase (MAPK) activation in lipopolysaccharide (LPS)-induced myocardial dysfunction has not been clearly defined. Our aim was to investigate the contribution of p38 MAPK in myocardial tumor necrosis factor-alpha (TNF-alpha) expression, cardiac function and survival during acute endotoxemia in mice. METHODS: Acute endotoxemia was induced by LPS (10 mg/kg, i.p.) in mice. Two hours after LPS treatment, left ventricular (LV) function was assessed. Phosphorylation of p38 MAPK was measured by Western blotting. TNF-alpha mRNA and protein levels were determined by semi-quantitative reverse-transcriptase polymerase chain reaction and enzyme-linked immunosorbent assay, respectively. RESULTS: LPS rapidly increased phosphorylation of p38 MAPK, followed by TNF-alpha mRNA expression and protein expression in the LV myocardium. Pre-treatment of the p38 MAPK inhibitor SB202190 (2 mg/kg, i.p.) decreased TNF-alpha mRNA and protein by 65 and 36%, respectively (P<0.05). Immunohistochemical staining confirmed that cardiomyocytes were the major source of TNF-alpha production in the myocardium and blocking p38 MAPK activation inhibited TNF-alpha expression in response to LPS. Pre-treatment of SB202190 or a TNF-alpha antagonist etanercept (2 mg/kg, i.p) significantly reversed LPS-induced LV depression (P<0.05). LPS (20 mg/kg, i.p.) induced 94% mortality in mice within 72 h and pre-treatment with SB202190 and etanercept decreased LPS-induced mortality to 65 and 40%, respectively (P<0.01). CONCLUSION: p38 MAPK activation represents an important mechanism leading to myocardial TNF-alpha production and cardiac dysfunction during acute endotoxemia in mice. Our data suggest that p38 MAPK is a potential therapeutic target of endotoxemia.
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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) | 0.001 | 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) | 0.002 | 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".