Platelet Jak2 deficiency accelerates atherosclerosis with increased inflammatory response
Bibliographic record
Abstract
Cardiovascular disease (CVD) is the leading cause of mortality worldwide, of which atherosclerosis is the major pathology. Chronic inflammation underlies atherosclerosis, and Janus kinase 2 (Jak2) is a critical signaling node that mediates this process. Jak2 V617F activating mutation has recently been implicated in clonal hematopoiesis of indeterminate potential as an emerging major CVD risk factor. While platelets' role in hemostasis and thrombosis is well-established in CVD, the essential role of platelet Jak2 in mediating inflammation in atherosclerosis is unknown. To this end, we assessed the in vivo role of platelet Jak2 in atherosclerosis using ApoE -/- mice with platelet Jak2 deficiency. These mice developed accelerated atherosclerosis in the aortic roots and arches with no significant changes in metabolic parameters. Systemically, there were increased numbers of inflammatory cells including various leukocytes and platelets. Given the prominent role of macrophages in atherogenesis, we also assessed bone marrow (BM)-derived macrophages from these mice which exhibited upregulated expression of proinflammatory genes in response to lipopolysaccharide (LPS). Furthermore, flow cytometric analysis of the BM showed significant expansion of hematopoietic stem and progenitor cells (HSPCs), suggesting platelet Jak2 effect on HSPC expansion. Together, these results show that platelet Jak2 attenuates atherogenesis likely through pleiotropic effects including regulation of inflammation in myeloid cells.
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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 | 0.000 |
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 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".