Investigating the Role of Endothelial Glycogen Synthase Kinase3α/β in Atherogenesis in Low Density Lipoprotein Receptor Knockout Mice
Bibliographic record
Abstract
Risk factors for developing cardiovascular disease (CVD) are associated with inflammation and endothelial activation. Activated endothelial cells (ECs) express adhesion proteins that recruit monocytes to the subendothelial layer initiating plaque development. Understanding the mechanism(s) by which ECs increase adhesion protein expression will facilitate the development of therapies aimed at preventing CVD progression and mortality. Glycogen synthase kinase (GSK)3α/β are constitutively active kinases which have been associated with many cellular pathways regulating cell viability and metabolism. While roles for myeloid GSK3α/β in the development of atherosclerosis have been established, there is limited knowledge on the potential roles of endothelial GSK3α/β. With the use of Cre recombinase technology, GSK3α/β was knocked out of both ECs and macrophages (Tie2Cre GSK3α/βfl/fl LDLR−/−). A bone marrow transplant was used to replenish GSK3α/β in the myeloid lineage allowing the assessment of an endothelial-selective GSK3α/β knockout (BMT Tie2Cre GSK3α/βfl/fl LDLR−/−). In both models, adhesion protein expression, macrophage recruitment and plaque volume were reduced in GSK3α knockout mice. GSK3β knockout had no significant effect. Results from this study are the first to suggest a pro-atherogenic role of endothelial GSK3α and support existing evidence for targeting GSK3α in the treatment of atherosclerotic CVD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".