Endothelial cells respond to hyperglycemia by increasing the LPL transporter GPIHBP1
Bibliographic record
Abstract
In diabetes, when glucose uptake and oxidation are impaired, the heart is compelled to use fatty acid (FA) almost exclusively for ATP. The vascular content of lipoprotein lipase (LPL), the rate-limiting enzyme that determines circulating triglyceride clearance, is largely responsible for this FA delivery and increases following diabetes. Glycosylphosphatidylinositol-anchored high-density lipoprotein-binding protein [GPIHBP1; a protein expressed abundantly in the heart in endothelial cells (EC)] collects LPL from the interstitial space and transfers it across ECs onto the luminal binding sites of these cells, where the enzyme is functional. We tested whether ECs respond to hyperglycemia by increasing GPIHBP1. Streptozotocin diabetes increased cardiac LPL activity and GPIHBP1 gene and protein expression. The increased LPL and GPIHBP1 were located at the capillary lumen. In vitro, passaging EC caused a loss of GPIHBP1, which could be induced on exposure to increasing concentrations of glucose. The high-glucose-induced GPIHBP1 increased LPL shuttling across EC monolayers. GPIHBP1 expression was linked to the EC content of heparanase. Moreover, active heparanase increased GPIHBP1 gene and protein expression. Both ECs and myocyte heparan sulfate proteoglycan-bound platelet-derived growth factor (PDGF) released by heparanase caused augmentation of GPIHBP1. Overall, our data suggest that this protein "ensemble" (heparanase-PDGF-GPIHBP1) cooperates in the diabetic heart to regulate FA delivery and utilization by the cardiomyocytes. Interrupting this axis may be a novel therapeutic strategy to restore metabolic equilibrium, curb lipotoxicity, and help prevent or delay heart dysfunction that is characteristic of 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) | 0.001 | 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".