Pivotal role of phospholipase C in cardiac TNF‐α expression during endotoxemia
Bibliographic record
Abstract
Myocardial dysfunction is a common complication of sepsis. Lipopolysaccharides (LPS) of Gram‐negative bacteria are important pathogens responsible for myocardial depression during sepsis. LPS‐induced TNF‐α is one of the main factors for cardiac dysfunction. The purpose of this study was to investigate the role of phospholipase C (PLC) in cardiac TNF‐α expression during LPS stimulation. In cultured neonatal cardiomyocytes, U73122 treatment abrogated TNF‐α expression induced by LPS, suggesting an essential role of PLC in LPS‐induced TNF‐α expression. To clarify which isozyme of three classes of PLC isozymes (β, γ, δ) is important in LPS‐induced TNF‐α expression, cardiomyocytes were co‐incubated with LPS and a protein tyrosine kinase inhibitor genestein. Genestein blocked LPS‐induced TNF‐α expression, suggesting that PLCγ may play an important role in TNF‐α expression since only PLCγ is activated through tyrosine kinase. This was confirmed by the following experimental results. First, LPS increased PLCγ1 phosphorylation in cardiomyocytes. Second, knockdown of PLCγ1 using specific siRNA decreased LPS‐induced TNF‐α expression by 55% in cardiomyocytes. To investigate the role of PLC in endotoxemia, adult mice were treated with LPS (4 mg/kg, i.p.) in the presence of vehicle or U73122 for 2 hours. U73122 treatment decreased cardiac TNF‐α mRNA by 60% and significantly attenuated LPS‐induced myocardial depression. In conclusion, our data demonstrated an important role of PLCγ1 in cardiac TNF‐α expression and myocardial dysfunction during 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) | 0.000 | 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 | 0.001 |
| 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".