Acute protection of ischemic heart by FGF-2: involvement of FGF-2 receptors and protein kinase C
Bibliographic record
Abstract
We examined the effect of fibroblast growth factor (FGF)-2 on myocardial resistance to injury when administered after the onset of ischemia, in vivo and ex vivo, and the role of FGF-2 receptors and protein kinase C (PKC). FGF-2 was injected into the left ventricle of rats undergoing permanent surgical coronary occlusion leading to myocardial infarction (MI). After 24 h, FGF-2-treated hearts displayed significantly reduced injury, determined by histological staining and troponin T release, and improved developed pressure compared with untreated controls. An FGF-2 mutant with diminished affinity for the tyrosine kinase FGF-2 receptor 1 (FGFR1) was not cardioprotective. FGF-2-treated hearts retained improved function and decreased damage at 6 wk after MI. In the ex vivo heart, FGF-2 administration during reperfusion after 30-min ischemia improved functional recovery and increased relative levels of PKC subtypes alpha, epsilon, and zeta in the particulate fraction, in a chelerythrine-preventable mode; it also decreased loss of energy metabolites. We conclude that intramyocardial FGF-2 administration shortly after the onset of ischemia confers protection from acute and chronic cardiac dysfunction and damage; FGF-2 delivered during reperfusion protects from ischemia-reperfusion injury; and protection by FGF-2 requires intact binding to FGFR1 and is likely mediated by PKC.
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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 | 0.000 | 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 | 0.001 |
| 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".