Increase toll‐like receptor 4 expression after ischemia/reperfusion contributes to myocardial apoptosis: role of PI3Kγ/NFκB pathway
Bibliographic record
Abstract
This study is to explore increase toll‐like receptor 4 (TLR4) expression and its regulation pathway in the ischemia/reperfusion (I/R) ‐induced myocardial apoptosis. Methods TLR4 expression, PI3Kγ, NFκB and apoptosis were assessed in cardiac myocytes challenged with an anoxia/reoxygenation (A/R). In vivo, mice were subjected to coronary artery occlusion followed by releasing for myocardial I/R. Myocardial TLR4 expression, apoptosis were evaluated. Results A/R challenge resulted in increased TLR4 expression and myocyte apoptosis. Myocytes deficient in TLR4 did not show increase in myocyte apoptosis after A/R. PI3Kγ and p65 (a subunit of NFκB were phosphorylated in cardiomyocytes with A/R. The phosphorylation of p65 occurred after PI3Kγ. A/R‐induced p65 phosphorylation did not occur in myocytes deficient in PI3Kγ. Pretreatment of myocytes with MG132, an inhibitor of NFκB, prevented the A/R‐induced increase in TLR4 expression. I/R resulted in increase myocardial TLR4 expression and apoptosis. I/R‐induced myocardial apoptosis was attenuated in mice deficient in TLR4 and PI3Kγ. Conclusion Our results indicate increase in TLR4 expression contributes to I/R‐induced myocardial apoptosis. PI3Kγ/NFκB signaling pathway is pivotal in regulating TLR4 expression. (HSFO NA 6316)
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".