Myeloid deletion and therapeutic activation of AMPK do not alter atherosclerosis in male or female mice
Bibliographic record
Abstract
The dysregulation of myeloid-derived cell metabolism can drive atherosclerosis. AMP-activated protein kinase (AMPK) controls various aspects of macrophage dynamics and lipid homeostasis, which are important during atherogenesis. Using LysM-Cre to drive the deletion of both the α1 and α2 catalytic subunits (MacKO), we aimed to clarify the role of myeloid-specific AMPK signaling in male and female mice made acutely atherosclerotic by injection of AAV vector encoding a gain-of-function mutant PCSK9 (PCSK9-AAV) and WD feeding. After 6 weeks of WD feeding, mice received a daily injection of either the AMPK activator A-769662 or a vehicle control for an additional 6 weeks. Following this (12 weeks total), we assessed myeloid cell populations and differences between genotype or sex were not observed. Similarly, aortic sinus plaque size, lipid staining, and necrotic area did not differ in male and female MacKO mice compared with their littermate floxed controls. Moreover, therapeutic intervention with A-769662 showed no treatment effect. There were also no observable differences in the amount of circulating total cholesterol or triglyceride, and only minor differences in the levels of inflammatory cytokines between groups. Finally, CD68+ area and markers of autophagy showed no effect of either lacking AMPK signaling or AMPK activation. Our data suggest that while defined roles for each catalytic AMPK subunit have been identified, complete deletion of myeloid AMPK signaling does not significantly impact atherosclerosis. Additionally, these findings suggest that intervention with the first-generation AMPK activator A-769662 is not able to stem the progression of atherosclerosis.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".