CLEC5A knockdown protects against cardiac dysfunction after myocardial infarction by suppressing macrophage polarization, NLRP3 inflammasome activation, and pyroptosis
Bibliographic record
Abstract
Increasing evidence has shown that the NOD-like receptor protein 3 (NLRP3) inflammasome and pyroptotic cell death play vital roles in the pathophysiology of myocardial infarction (MI), a common cardiovascular disease characterized by cardiac dysfunction. C-type lectin member 5A (CLEC5A) has been reported to be strongly associated with activation of the NLRP3 inflammasome and pyroptosis. In this study, an in vivo MI model was established by ligation of the left anterior descending coronary artery in male C57BL/6 mice, and CLEC5A knockdown was further achieved by intra-myocardial injection of adenovirus delivering shRNA-CLEC5A. CLEC5A was found to be highly expressed in the left ventricle of MI mice, while CLEC5A knockdown alleviated cardiac dysfunction in MI mice. In addition, MI-induced classical activation of macrophages was significantly inhibited after CLEC5A silencing. Additionally, CLEC5A knockdown dramatically inhibited MI-triggered activation of NLRP3 inflammasome, pyroptosis, and NF-κB signaling in the left ventricle of mice. In vitro experiments further validated that CLEC5A knockdown suppressed M1 polarization in LPS/IFNγ-stimulated RAW264.7 cells and inhibited the polarized RAW264.7-induced activation of NLRP3 inflammasome/pyroptosis signaling in co-cultured cardiomyocytes. In conclusion, CLEC5A knockdown protects against MI-induced cardiac dysfunction by regulating macrophage polarization, NLRP3 inflammasome, and cell pyroptosis.
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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 | 0.001 |
| 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 | 0.001 | 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".