Inflammatory Chemokine Receptors Support Inflammatory Macrophage and Dendritic Cell Maturation
Bibliographic record
Abstract
Dendritic cells form clusters in vivo, but the mechanism behind this has not been determined. In this article, we demonstrate that monocytes from mice deficient in the chemokine receptors CCR1, CCR2, CCR3, and CCR5 display reduced clustering in vitro, which is associated with impaired dendritic cell and macrophage differentiation. We further show that the differentiating cells themselves produce ligands for these receptors that function, in a redundant manner, to regulate cell clustering. Deletion of, or pharmacological blockade of, more than one of these receptors is required to impair clustering and differentiation. Our data show that chemokines and their receptors support clustering by increasing expression of, and activating, cell-surface integrins, which are associated with cell-cell interactions and, in the context of monocyte differentiation, with reduced expression of Foxp1, a known transcriptional suppressor of monocyte differentiation. Our data therefore provide a mechanism whereby chemokines and their receptors typically found in inflammatory environments can interact to promote murine monocyte differentiation to macrophages and dendritic 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) | 0.000 | 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) | 0.002 | 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".