Insulin-Like Growth Factor-1 and PTEN Deletion Enhance Cardiac L-Type Ca <sup>2+</sup> Currents via Increased PI3Kα/PKB Signaling
Bibliographic record
Abstract
Ca2+ influx through the L-type Ca2+ channel (I(Ca,L)) is a key determinant of cardiac contractility and is modulated by multiple signaling pathways. Because the regulation of I(Ca,L) by phosphoinositide-3-kinases (PI3Ks) and phosphoinositide-3-phosphatase (PTEN) is unknown, despite their involvement in the regulation of myocardial growth and contractility, I(Ca,L) was recorded in myocytes isolated from mice overexpressing a dominant-negative p110alpha mutant (DN-p110alpha) in the heart, lacking the PI3Kgamma gene (PI3Kgamma(-/-)) or with muscle-specific ablation of PTEN (PTEN(-/-)). Combinations of these genetically altered mice were also examined. Although there were no differences in the expression level of CaV1.2 proteins, basal I(Ca,L) densities were larger (P<0.01) in PTEN(-/-) myocytes compared with littermate controls, PI3Kgamma(-/-), or DN-p110alpha myocytes and showed negative shifts in voltage dependence of current activation. The I(Ca,L) differences seen in PTEN(-/-) mice were eliminated by pharmacological inhibition of either PI3Ks or protein kinase B (PKB) as well as in PTEN(-/-)/DN-p110alpha double mutant mice but not in PTEN(-/-)/PI3Kgamma(-/-) mice. On the other hand, application of insulin-like growth factor-1 (IGF-1), an activator of PKB, increased I(Ca,L) in control and PI3Kgamma(-/-), while having no effects on I(Ca,L) in DN-p110alpha or PTEN(-/-) mice. The I(Ca,L) increases induced by IGF-1 were abolished by PKB inhibition. Our results demonstrate that IGF-1 treatment or inactivation of PTEN enhances I(Ca,L) via PI3Kalpha-dependent increase in PKB activation.
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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) | 0.000 | 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) | 0.002 | 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".