Myocardial expression of PDECGF is associated with extracellular matrix remodeling in experimental myocardial infarction in rats
Bibliographic record
Abstract
Platelet-derived endothelial cell growth factor (PDECGF) is a potent angiogenic peptide with anti-apoptotic activity expressed widely in tumours. However, its expression in myocardial infarction (MI) is not yet established. This study aimed to assess the myocardial expression of PDECGF in rats after MI. Extracellular matrix (ECM) remodeling plays an important role in angiogenesis; hence, changes in the ECM components were investigated in the myocardium after MI, which was induced in rats by coronary artery ligation (CAL) and verified using biochemical markers and histopathology. Immunohistochemistry, RT-PCR, and activity assays identified the expression pattern of PDECGF on days 1, 2, 4, 8, 16, and 32 after CAL. The levels of TNF-alpha, MMP-2, collagen, and glycosaminoglycans in the ECM were assessed. Studies on immunohistochemistry, RT-PCR, and PDECGF activity demonstrated elevated levels of PDECGF expression from day 2 after CAL. Macrophages, endothelial cells, fibroblasts, and cardiomyocytes, especially at the border region of the lesion, showed an enhanced expression for PDECGF. Remodeling of the ECM was depicted by changes in the levels of TNF-alpha, MMP-2, collagen, and GAG. Hence, this study clearly indicated PDECGF as an important angiogenic molecule expressed during MI and the alterations in ECM components facilitated the process of angiogenesis.
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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) | 0.001 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".