Apoptosis in Human Acute Myocardial Infarction: The Rationale for Clinical Trials of Apoptosis Inhibition in Acute Myocardial Infarction
Bibliographic record
Abstract
The objective of the present review was to examine apoptosis in patients with acute myocardial infarction (MI) and to address (i) the prevalence of apoptosis in acute MI, (ii) techniques to determine apoptosis, (iii) time period from the onset of acute MI to the detection of apoptosis, (iv) criticisms about apoptosis in acute MI. A systematic literature search identified over 20 publications comprising over 400 patients. The prevalence of apoptosis varied from over 90% in nuclear imaging studies using annexin binding to 0.25% in an autopsy study using monoclonal antibody to single-stranded DNA. Apoptosis was present in 50–60% of infarcted hearts within 24 hours of MI (detected by Bax and activated caspase-3), 26% of myocytes in patients who died within 11 days of MI (pooled mean from 5 studies using only TUNEL staining), and 12% of the myocytes of patients who died, on average, 20 days after onset of MI (pooled mean from eight studies using dual staining with caspase-3 plus TUNEL). Criticisms of the TUNEL assay appear unjustified as TUNEL is at least 85% specific using caspase-3 activation as a marker of apoptosis. Taken together, DNA fragmentation on agarose gel electrophoresis, TUNEL staining of nuclei, caspase-3 activation, bcl-2 and Bax expression, and annexin V binding overwhelming support apoptotic cell death as an important component of MI. The amount of cardiac apoptosis correlates with the presence of heart failure and fatal arrhythmias. Heart failure as a complication of MI carries a high mortality and indicates the amount of myocardium lost during the infarct. Taken together, these findings suggest the need for clinical trials in acute MI to confirm whether inhibition of apoptosis can reduce patient morbidity and mortality.
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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 | 0.042 | 0.057 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.004 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.003 | 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".