Fibroblast growth factor‐2 exerts protective effects on cardiac mitochondria
Bibliographic record
Abstract
Fibroblast growth factor‐2 (FGF‐2) is a potent cardioprotective agent, by a mechanism linked to connexin43 (Cx43) phosphorylation at protein kinase C (PKC) target serines such as S262. Here we have examined the effects of FGF‐2 on mitochondrial resistance to calcium‐ induced opening of the permeability transition pore (swelling), in relation to cardiac mitochondrial Cx43 levels and phosphorylation. Subsarcolemmal mitochondria isolated from FGF‐2‐treated hearts: (a) showed 1.5–2 fold increase in total Cx43, PKCε, TOM20 translocase, and a over 30‐fold increase in phospho‐S262‐Cx43, compared to control mitochondria obtained from untreated hearts; (b) were more resistant to calcium‐induced swelling and cytochrome C release; (c) were resistant to calcium‐induced mitochondrial Cx43 degradation. Calpeptin, a potent inhibitor of the calcium activated protease calpain, prevented Cx43 degradation in control mitochondria. Stimulation of control mitochondria with the phorbol‐ester PMA, or FGF‐2, increased both mitochondrial Cx43 phosphorylation at S262 and resistance to calcium‐induced swelling / cytochrome c release. Our data imply that FGF‐2 cardioprotection is mediated by increasing mitochondrial resistance to calcium damage, via Cx43 translocation to mitochondria and mitochondrial Cx43 phosphorylation. This work is supported by Heart and Stroke Foundation of Canada and St. Boniface Hospital Research Foundation.
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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 | 0.000 |
| 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".