Usage Information
Abstract
Atherosclerosis is a leading cause of death worldwide in industrialized countries. Disease progression and regression are associated with different activation states of macrophages derived from inflammatory monocytes entering the plaques. The features of monocyte-to-macrophage transition and the full spectrum of macrophage activation states during either plaque progression or regression, however, are incompletely established. Here, we use a combination of single-cell RNA sequencing and genetic fate mapping to profile, for the first time to our knowledge, plaque cells derived from CX3CR1+ precursors in mice during both progression and regression of atherosclerosis. The analyses revealed a spectrum of macrophage activation states with greater complexity than the traditional M1 and M2 polarization states, with progression associated with differentiation of CXC3R1+ monocytes into more distinct states than during regression. We also identified an unexpected cluster of proliferating monocytes with a stem cell–like signature, suggesting that monocytes may persist in a proliferating self-renewal state in inflamed tissue, rather than differentiating immediately into macrophages after entering the tissue.
Authors
Jian-Da Lin, Hitoo Nishi, Jordan Poles, Xiang Niu, Caroline Mccauley, Karishma Rahman, Emily J. Brown, Stephen T. Yeung, Nikollaq Vozhilla, Ada Weinstock, Stephen A. Ramsey, Edward A. Fisher, P’ng Loke
Usage data is cumulative from December 2024 through December 2025.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 2,219 | 698 |
| 223 | 153 | |
| Figure | 660 | 7 |
| Supplemental data | 152 | 74 |
| Citation downloads | 148 | 0 |
| Totals | 3,402 | 932 |
| Total Views | 4,334 | |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.
