Macrophage Jak2 deficiency accelerates atherosclerosis through defects in cholesterol efflux
Bibliographic record
Abstract
Abstract Atherosclerosis is a chronic inflammatory condition in which macrophages play a major role. Janus kinase 2 (JAK2) is a pivotal molecule in inflammatory and metabolic signaling, and Jak2V617F activating mutation has recently been implicated with enhancing clonal hematopoiesis and atherosclerosis. To determine the essential in vivo role of macrophage (M)-Jak2 in atherosclerosis, we generate atherosclerosis-prone ApoE-null mice deficient in M-Jak2. Contrary to our expectation, these mice exhibit increased plaque burden with no differences in macrophage proliferation, recruitment or bone marrow clonal expansion. Notably, M-Jak2-deficient bone marrow derived macrophages show a significant defect in cholesterol efflux. Pharmacologic JAK2 inhibition with ruxolitinib also leads to defects in cholesterol efflux and accelerates atherosclerosis. Liver X receptor agonist abolishes the efflux defect and attenuates the accelerated atherosclerosis that occurs with M-Jak2 deficiency. Macrophages of individuals with the Jak2V617F mutation show increased efflux which is normalized when treated with a JAK2 inhibitor. Together, M-Jak2-deficiency leads to accelerated atherosclerosis primarily through defects in cholesterol efflux from macrophages.
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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 | 0.000 |
| 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) | 0.002 | 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".