Involvement of atypical protein kinase C in the regulation of cardiac glucose and long-chain fatty acid uptake
Bibliographic record
Abstract
AIM: The signaling pathways involved in the regulation of cardiac GLUT4 translocation/glucose uptake and CD36 translocation/long-chain fatty acid uptake are not fully understood. We compared in heart/muscle-specific PKC-λ knockout mice the roles of atypical PKCs (PKC-ζ and PKC-λ) in regulating cardiac glucose and fatty acid uptake. RESULTS: Neither insulin-stimulated nor AMPK-mediated glucose and fatty acid uptake were inhibited upon genetic PKC-λ ablation in cardiomyocytes. In contrast, myristoylated PKC-ζ pseudosubstrate inhibited both insulin-stimulated and AMPK-mediated glucose and fatty acid uptake by >80% in both wild-type and PKC-λ-knockout cardiomyocytes. In PKC-λ knockout cardiomyocytes, PKC-ζ is the sole remaining atypical PKC isoform, and its expression level is not different from wild-type cardiomyocytes, in which it contributes to 29% and 17% of total atypical PKC expression and phosphorylation, respectively. CONCLUSION: Taken together, atypical PKCs are necessary for insulin-stimulated and AMPK-mediated glucose uptake into the heart, as well as for insulin-stimulated and AMPK-mediated fatty acid uptake. However, the residual PKC-ζ activity in PKC-λ-knockout cardiomyocytes is sufficient to allow optimal stimulation of glucose and fatty acid uptake, indicating that atypical PKCs are necessary but not rate-limiting in the regulation of cardiac substrate uptake and that PKC-λ and PKC-ζ have interchangeable functions in these processes.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".