Protein Kinases as Drug Development Targets for Heart Disease Therapy
Bibliographic record
Abstract
Protein kinases are intimately integrated in different signal transduction pathways for the regulation of cardiac function in both health and disease. Protein kinase A (PKA), Ca²⁺-calmodulin-dependent protein kinase (CaMK), protein kinase C (PKC), phosphoinositide 3-kinase (PI3K) and mitogen-activated protein kinase (MAPK) are not only involved in the control of subcellular activities for maintaining cardiac function, but also participate in the development of cardiac dysfunction in cardiac hypertrophy, diabetic cardiomyopathy, myocardial infarction, and heart failure. Although all these kinases serve as signal transducing proteins by phosphorylating different sites in cardiomyocytes, some of their effects are cardioprotective whereas others are detrimental. Such opposing effects of each signal transduction pathway seem to depend upon the duration and intensity of stimulus as well as the type of kinase isoform for each kinase. In view of the fact that most of these kinases are activated in heart disease and their inhibition has been shown to improve cardiac function, it is suggested that these kinases form excellent targets for drug development for therapy of heart disease.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".