Glucosamine-Induced Endoplasmic Reticulum Dysfunction Is Associated With Accelerated Atherosclerosis in a Hyperglycemic Mouse Model
Bibliographic record
Abstract
Diabetes is a major independent risk factor for cardiovascular disease and stroke; however, the molecular and cellular mechanisms by which diabetes contributes to the development of vascular disease are not fully understood. Our previous studies demonstrated that endoplasmic reticulum (ER) stress-inducing agents, including homocysteine, promote lipid accumulation and activate inflammatory pathways-the hallmark features of atherosclerosis. We hypothesize that the accumulation of intracellular glucosamine observed in diabetes may also promote atherogenesis via a mechanism that involves ER stress. In support of this theory, we demonstrate that glucosamine can induce ER stress in cell types relevant to the development of atherosclerosis, including human aortic smooth muscle cells, monocytes, and hepatocytes. Furthermore, we show that glucosamine-induced ER stress dysregulates lipid metabolism, leading to the accumulation of cholesterol in cultured cells. To examine the relevance of the ER stress pathway in vivo, we used a streptozotocin-induced hyperglycemic apolipoprotein E-deficient mouse model of atherosclerosis. Using molecular biological and histological techniques, we show that hyperglycemia is associated with tissue-specific ER stress, hepatic steatosis, and accelerated atherosclerosis. This novel mechanism may not only explain how diabetes and hyperglycemia promote atherosclerosis, but also provide a potential new target for therapeutic intervention.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".