Acute dexamethasone-induced increase in cardiac lipoprotein lipase requires activation of both Akt and stress kinases
Bibliographic record
Abstract
Following dexamethasone (DEX), cardiac energy generation is mainly through utilization of fatty acids (FA), with DEX animals demonstrating an increase in coronary lipoprotein lipase (LPL), an enzyme that hydrolyzes lipoproteins to FA. We examined the mechanisms by which DEX augments cardiac LPL. DEX was injected in rats, and hearts were removed, or isolated cardiomyocytes were incubated with DEX (0-8 h), for measurement of LPL activity and Western blotting. Acute DEX induced whole body insulin resistance, likely an outcome of a decrease in insulin signaling in skeletal muscle, but not cardiac tissue. The increase in luminal LPL activity after DEX was preceded by rapid nongenomic alterations, which included phosphorylation of AMPK and p38 MAPK, that led to phosphorylation of heat shock protein (HSP)25 and actin cytoskeleton rearrangement, facilitating LPL translocation to the myocyte cell surface. Unlike its effects in vivo, although DEX activated AMPK and p38 MAPK in cardiomyocytes, there was no phosphorylation of HSP25, nor was there any evidence of F-actin polymerization or an augmentation of LPL activity up to 8 h after DEX. Combining DEX with insulin appreciably enhanced cardiomyocyte LPL activity, which closely mirrored a robust elevation in phosphorylation of HSP25 and F-actin polymerization. Silencing of p38 MAPK, inhibition of PI 3-kinase, or preincubation with cytochalasin D prevented the increases in LPL activity. Our data suggest that, following DEX, it is a novel, rapid, nongenomic phosphorylation of stress kinases that, together with insulin, facilitates LPL translocation to the myocyte cell surface.
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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 | 0.001 |
| 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".