Macrophages and Dendritic Cells
Bibliographic record
Abstract
Atherosclerosis is a complex chronic disease. The accumulation of myeloid cells in the arterial intima, including macrophages and dendritic cells (DCs), is a feature of early stages of disease. For decades, it has been known that monocyte recruitment to the intima contributes to the burden of lesion macrophages. Yet, this paradigm may require reevaluation in light of recent advances in understanding of tissue macrophage ontogeny, their capacity for self-renewal, as well as observations that macrophages proliferate throughout atherogenesis and that self-renewal is critical for maintenance of macrophages in advanced lesions. The rate of atherosclerotic lesion formation is profoundly influenced by innate and adaptive immunity, which can be regulated locally within atherosclerotic lesions, as well as in secondary lymphoid organs, the bone marrow and the blood. DCs are important modulators of immunity. Advances in the past decade have cemented our understanding of DC subsets, functions, hematopoietic origin, gene expression patterns, transcription factors critical for differentiation, and provided new tools for study of DC biology. The functions of macrophages and DCs overlap to some extent, thus it is important to reassess the contributions of each of these myeloid cells taking into account strict criteria of cell identification, ontogeny, and determine whether their key roles are within atherosclerotic lesions or secondary lymphoid organs. This review will highlight key aspect of macrophage and DC biology, summarize how these cells participate in different stages of atherogenesis and comment on complexities, controversies, and gaps in knowledge in the field.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".