FGF-16 is released from neonatal cardiac myocytes and alters growth-related signaling: a possible role in postnatal development
Bibliographic record
Abstract
FGF-16 has been reported to be preferentially expressed in the adult rat heart. We have investigated the expression of FGF-16 in the perinatal and postnatal heart and its functional significance in neonatal rat cardiac myocytes. FGF-16 mRNA accumulation was observed by quantitative RT-PCR between neonatal days 1 and 7, with this increased expression persisting into adulthood. FGF-2 has been shown to increase neonatal rat cardiac myocyte proliferative potential via PKC activation. Gene array analysis revealed that FGF-16 inhibited the upregulation by FGF-2 of cell cycle promoting genes including cyclin F and Ki67. Furthermore, the CDK4/6 inhibitor gene Arf/INK4A was upregulated with the combination of FGF-16 and FGF-2 but not with either factor on its own. The effect on Ki67 was validated by protein immunodetection, which also showed that FGF-16 significantly decreased FGF-2-induced Ki67 labeling of cardiac myocytes, although it alone had no effect on Ki67 labeling. Inhibition of p38 MAPK potentiated cardiac myocyte proliferation induced by FGF-2 but did not alter the inhibitory action of FGF-16. Receptor binding assay showed that FGF-16 can compete with FGF-2 for binding sites including FGF receptor 1. FGF-16 had no effect on activated p38, ERK1/2, or JNK/SAPK after FGF-2 treatment. However, FGF-16 inhibited PKC-alpha and PKC-epsilon activation induced by FGF-2 and, importantly, IGF-1. Collectively, these data suggest that expression and release of FGF-16 in the neonatal myocardium interfere with cardiac myocyte proliferative potential by altering the local signaling environment via modulation of PKC activation and cell cycle-related gene expression.
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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".