High molecular weight FGF-2 promotes postconditioning-like cardioprotection linked to activation of the protein kinase C isoforms Akt and p70 S6 kinaseThis article is one of a selection of papers published in a special issue celebrating the 125th anniversary of the Faculty of Medicine at the University of Manitoba.
Bibliographic record
Abstract
Fibroblast growth factor 2 (FGF-2) is a multifunctional protein translated as high and low molecular weight isoforms (hi- and lo-FGF-2, respectively). Although the postconditioning cardioprotective effect of lo-FGF-2 (18 kDa) has been documented, hi-FGF-2 is less well studied. We used an isolated perfused rat heart model of ischemia-reperfusion to study the effects of postischemic (during reperfusion) administration of hi-FGF-2 on recovery of contractile function and tissue salvage, as indicated by decreased cytosolic cytochrome c levels. Compared with the vehicle-treated group, hi-FGF-2-treated hearts had significantly improved recovery of systolic pressure, developed pressure, rates of contraction and relaxation, and coronary flow, as well as decreased relative levels of cytosolic cytochrome c. The effects of hi-FGF-2 on functional recovery and cytosolic cytochrome c were indistinguishable from those induced by lo-FGF-2. Both hi- and lo-FGF-2 upregulated relative levels of phosphorylated (activated) Akt and p70 S6 kinase, and they both promoted translocation of alpha, epsilon, and zeta isoforms of protein kinase C (PKC) to the particulate fraction of reperfused hearts. The magnitude of the effect on PKCzeta and p70 S6 kinases, however, was significantly more potent in the hi-FGF-2 than in the lo-FGF-2 group. We conclude that acute postischemic cardioprotection by hi- or lo-FGF-2 is isoform nonspecific and likely to be mediated by PKC and Akt. Nevertheless, isoform-specific functions are suggested by the augmented sensitivity of p70 S6 and PKCzeta to hi-FGF-2.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".