Proteolytic Digestion of Serum Cardiac Troponin I as Marker of Ischemic Severity
Bibliographic record
Abstract
BACKGROUND: The serum troponin assay is the biochemical gold standard for detecting myocardial infarction (MI). A major diagnostic issue is that some believe troponin levels can rise with reversible injury, in the absence of radiologically detectable infarct. HYPOTHESIS: Because cell death activates intracellular proteases, troponin released by irreversible infarct will be more proteolyzed than that released by milder processes. Our goal was to quantify proteolytic digestion of cardiac troponin I in patients with varying degrees of myocardial injury. METHODS: Serum or plasma samples from 29 patients with cardiac troponin I elevations were analyzed for proteolytic degradation, using 3 different sandwich ELISAs designed to specifically detect the N-terminal, core, or C-terminal regions of cardiac troponin I. RESULTS: As predicted, the degree of proteolytic digestion increased with increasing severity of injury, as estimated by the total troponin level, and this trend was more pronounced for C-terminal (vs N-terminal) degradation. The highest degree of proteolytic digestion was observed in patients with ST-elevation MI; the least, in type 2 MI (supply-demand ischemia rather than acute thrombus formation). CONCLUSIONS: The proteolytic degradation pattern of cardiac troponin I may be a better indicator of clinically significant MI than total serum troponin level. Distinguishing between intact and degraded forms of troponin may be useful for (a) identifying those patients with clinically significant infarct in need of revascularization, (b) monitoring intracellular proteolysis as a possible target for therapeutic intervention, and (c) providing an impetus for standardizing the epitopes used in the troponin I assay.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".