Data-Independent Acquisition Proteomics and N-Terminomics Methods Reveal Alterations in Mitochondrial Function and Metabolism in Ischemic-Reperfused Hearts
Bibliographic record
Abstract
Myocardial ischemia-reperfusion (IR) (stunning) injury triggers changes in the proteome and degradome of the heart. Here, we utilize quantitative proteomics and comprehensive degradomics to investigate the molecular mechanisms of IR injury in isolated rat hearts. The control group underwent aerobic perfusion, while the IR injury group underwent 20 min of ischemia and 30 min of reperfusion to induce a stunning injury. As MMP-2 activation has been shown to contribute to myocardial injury, hearts also underwent IR injury with ARP-100, an MMP-2-preferring inhibitor, to dissect the contribution of MMP-2 to IR injury. Using data-independent acquisition (DIA) and mass spectroscopy, we quantified 4468 proteins in ventricular extracts, whereby 447 proteins showed significant alterations among the three groups. We then used subtiligase-mediated N-terminomic labeling to identify more than a hundred specific cleavage sites. Among these protease substrates, 15 were identified following IR injury. We identified alterations in numerous proteins involved in mitochondrial function and metabolism following IR injury. Our findings provide valuable insights into the biochemical mechanisms of myocardial IR injury, suggesting alterations in reactive oxygen/nitrogen species handling and generation, fatty acid metabolism, mitochondrial function and metabolism, and cardiomyocyte contraction.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 teacher head, 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".