PI3K Phosphorylation Is Linked to Improved Electrical Excitability in an <i>In Vitro</i> Engineered Heart Tissue Disease Model System
Bibliographic record
Abstract
Myocardial infarction, a prevalent cardiovascular disease, is associated with cardiomyocyte cell death, and eventually heart failure. Cardiac tissue engineering has provided hopes for alternative treatment options, and high-fidelity tissue models for drug discovery. The signal transduction mechanisms relayed in response to mechanoelectrical (physical) stimulation or biochemical stimulation (hormones, cytokines, or drugs) in engineered heart tissues (EHTs) are poorly understood. In this study, an EHT model was used to elucidate the signaling mechanisms involved when insulin was applied in the presence of electrical stimulation, a stimulus that mimics functional heart tissue environment in vitro. EHTs were insulin treated, electrically stimulated, or applied in combination (insulin and electrical stimulation). Electrical excitability parameters (excitation threshold and maximum capture rate) were measured. Protein kinase B (AKT) and phosphatidylinositol-3-kinase (PI3K) phosphorylation revealed that insulin and electrical stimulation relayed electrical excitability through two separate signaling cascades, while there was a negative crosstalk between sustained activation of AKT and PI3K.
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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) | 0.001 | 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".