Targeted Cardiac Overexpression of A20 Improves Left Ventricular Performance and Reduces Compensatory Hypertrophy After Myocardial Infarction
Bibliographic record
Abstract
BACKGROUND: A20 was originally characterized as a tumor necrosis factor-inducible gene in human umbilical vein endothelial cells. As an inhibitor of nuclear factor-kappaB signaling, A20 protects against apoptosis, inflammation, and cardiac hypertrophy. In the present study, we tested the hypothesis that cardiac-specific overexpression of A20 could protect the heart from myocardial infarction. METHODS AND RESULTS: We investigated the role of constitutive human A20 expression in acute myocardial infarction using a transgenic model. Transgenic mice containing the human A20 gene under the control of the alpha-myosin heavy chain promoter were constructed. Myocardial infarction was produced by coronary ligation in A20 transgenic mice and control animals. The extent of infarction was then quantified by 2-dimensional and M-mode echocardiography and by molecular and pathological analyses of heart samples in infarct and remote heart regions 7 days after myocardial infarction. Constitutive overexpression of A20 in the murine heart resulted in attenuated infarct size and improved cardiac function 7 days after myocardial infarction. Significantly, we found a decrease in nuclear factor-kappaB signaling and apoptosis, as well as proinflammatory response, cardiac remodeling, and interstitial fibrosis, in noninfarct regions in the hearts of constitutive A20-expressing animals compared with control animals. CONCLUSIONS: Cardiac-specific overexpression of A20 improves cardiac function and inhibits cardiac remodeling, apoptosis, inflammation, and fibrosis after acute myocardial infarction.
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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 | 0.000 |
| 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".