Fatty Acid-Induced Nuclear Translocation of Heparanase Uncouples Glucose Metabolism in Endothelial Cells
Bibliographic record
Abstract
OBJECTIVE: Heparanase is an endoglycosidase that specifically cleaves carbohydrate chains of heparan sulfate. We have recently reported that high fatty acid increased the nuclear content of endothelial heparanase. Here, we examined the mechanism and the consequences behind this nuclear translocation of heparanase. METHODS AND RESULTS: Bovine coronary artery endothelial cells were grown to confluence and incubated with palmitic acid. Palmitic acid induced rapid nuclear accumulation of heparanase that was dependent on Bax activation and lysosome permeabilization. Heat shock protein 90 was an important mediator of palmitic acid-induced shuttling of heparanase to the nucleus. Nuclear heparanase promoted cleavage of heparan sulfate, a potent inhibitor of histone acetyltransferase activity and gene transcription. A TaqMan gene expression assay revealed an increase in genes related to glucose metabolism and inflammation. In addition, glycolysis was uncoupled from glucose oxidation, resulting in accumulation of lactate. CONCLUSIONS: The results presented in this study demonstrate that fatty acid can provoke lysosomal release of heparanase, its nuclear translocation, activation of genes controlling glucose metabolism, and accumulation of lactate. Given that lactate and inflammation have been implicated in the progression of atherosclerosis, our data may serve to reduce the associated cardiovascular complications seen during diabetes.
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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 | 0.000 |
| 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".