Monocyte recruitment to sites of inflammation, including atherosclerotic lesions, is dependent on the mechanosensitive ion channel Piezo1 3377
Bibliographic record
Abstract
Abstract Description Monocyte recruitment from the blood into tissues is a fundamental component of inflammatory conditions, including atherosclerosis. During recruitment, monocytes adherent to activated endothelium are exposed to external forces imparted by flowing blood. How they respond and resist detachment remains poorly understood. Using parallel plate flow chamber assays, we showed that force-dependent, α4 integrin-mediated monocyte spreading on VCAM-1 requires a Ca2+ influx that is mediated by the mechanosensitive ion channel Piezo1. In Ccr2-CreERT2; Piezo1fl/fl mice, conditional deletion of Piezo1 in Ly6Chi monocytes significantly lowered the number of monocytes and monocyte-derived macrophages in the peritoneal cavity following thioglycolate- or ovalbumin-induced peritonitis. Piezo1 deletion had no effect on the number of circulating blood monocytes. To study atherogenesis, we backcrossed Piezo1-floxed transgenics into the Ldlr–/– background. Deletion of monocyte Piezo1 in Ldlr–/– mice fed a cholesterol-rich diet reduced the size and macrophage content of 3-week atherosclerotic lesions. Neither the uptake of oxidized LDL nor phagocytosis were impaired in monocyte-derived Piezo1-deficient macrophages, suggesting that smaller lesions may be due to reduced monocyte recruitment primarily and not impaired macrophage lipid uptake. These findings provide novel molecular insights into the regulation of monocyte recruitment and demonstrate a role for monocyte Piezo1 in atherogenesis. Funding Sources Supported by CIHR FDN-154299 (M.I.C.). M.I.C. holds a Tier 1 Canada Research Chair. H.I. is supported by Queen Elizabeth II/ Heart and Stroke Foundation of Ontario Graduate Scholarship in Science and Technology. Topic Categories Cellular Adhesion, Migration, and Inflammation (CAM)
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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 | 0.000 |
| 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 | 0.000 |
| 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".