Imbalance Between Tissue Inhibitor of Metalloproteinase-4 and Matrix Metalloproteinases During Acute Myoctardial Ischemia-Reperfusion Injury
Bibliographic record
Abstract
BACKGROUND: We have previously reported that matrix metalloproteinase-2 (MMP-2) contributes to myocardial ischemia-reperfusion injury by degradation of troponin I, a regulatory element of the contractile proteins. MMP activities are also tightly regulated by tissue inhibitors of metalloproteinase (TIMPs). The change in TIMPs during acute myocardial ischemia-reperfusion injury is not clear. METHODS AND RESULTS: Isolated rat hearts were perfused either aerobically for 75 minutes or subjected to 15, 20, or 25 minutes of global, no-flow ischemia followed by 30 minutes of aerobic reperfusion. During reperfusion after ischemia, there was a rapid, enhanced release of TIMP-4, the most abundant TIMP in the heart, into the coronary effluent, as shown both by reverse zymography and Western blot. There was a negative correlation between the recovery of cardiac mechanical function and the release of TIMP-4 during reperfusion in hearts subjected to different durations of ischemia. Immunogold electron microscopy revealed a close association of TIMP-4 with the sarcomeres in aerobically perfused hearts. Moreover, TIMP-4 was present only in thin myofilaments prepared from aerobically perfused hearts but not in ischemic-reperfused hearts. An enhanced MMP activity was shown in ischemic-reperfused hearts by in situ zymography. CONCLUSIONS: Loss of TIMP-4 from the cardiac myocyte leads to an increase in net myocardial MMP activity that contributes to acute myocardial stunning injury.
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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".