Abstract 659: PKR-Like Endoplasmic Reticulum Kinase and Glycogen Synthase Kinase-3α/ß Signaling Regulates Endoplasmic Reticulum Stress-Induced Foam Cell Formation
Bibliographic record
Abstract
Background: Evidence suggests a causative role for endoplasmic reticulum (ER) stress in the development of atherosclerosis. The molecular mechanisms by which conditions of ER stress promote pro-atherogenic processes are not understood. We have found that ER stress-inducing agents can activate glycogen synthase kinase (GSK)-3α/β, a protein involved in many metabolic pathways. The objective of this study is to investigate the role of GSK3α/β in pro-atherogenic ER stress signaling. Methods and Results: Thp1-derived macrophages were treated with the ER stress-inducing agents, glucosamine, thapsigargin or palmitate, in the presence or absence of the GSK3α/β inhibitor CT99021. GSK3α/β inhibition did not affect the adaptive unfolded protein response (UPR), but did block ER stress-induced lipid accumulation as well as the up regulation of genes associated with lipid biosynthesis and uptake. Using small molecule inhibitors of specific UPR pathways, we found that PERK, but not IRE1 or ATF6, is required for the activation of GSK3α/β by ER stress. GSK3α/β inhibition attenuated ER stress-induced expression of distal components of the PERK pathway, including CHOP and ATF4. Atherosclerotic plaques from ApoE-/- mice, fed a diet supplemented with the GSK3α/β inhibitor valproate, had reduced levels of CHOP within the macrophage foam cells. In primary mouse macrophages PERK inhibition blocked ER stress induced lipid accumulation whereas the overexpression of constitutively active S9A-GSK3β promoted foam cell formation and CHOP expression, even in cells treated with a PERK inhibitor. Conclusions: Pharmacological inhibition of GSK3α/β attenuates ER stress-induced lipid accumulation and macrophage foam cell formation. These findings indicate that GSK3α/β is an important factor in the ER stress-PERK signaling pathway and may play a central role in the pro-atherogenic dysregulation of lipid metabolism.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".