Uncovering the Heterogeneity and Ontogeny of Mouse Thymic Macrophages Reveals an Unexpected Early Checkpoint Role
Bibliographic record
Abstract
ABSTRACT Thymic macrophages (TMs) maintain tissue homeostasis by clearing the large numbers of apoptotic cells generated during T cell development, but how TM heterogeneity relates to their developmental origin and role in thymocyte maturation remains incompletely understood. Using complementary flow-cytometric, single-cell transcriptomic, and genetic approaches, we resolved two major TM populations corresponding to TIMD4 + cortical and CX3CR1 + medullary/cortico-medullary macrophages. TIMD4 + VCAM1 + TMs displayed a prominent efferocytosis and apoptotic-cell-clearance program, whereas TIMD4 − VCAM1 + TMs were enriched for antigen-presentation and interferon-response pathways. Fate mapping revealed unequal progenitor contributions to these populations, and CCR2 deficiency selectively reduced TIMD4 − VCAM1 + TMs and thymic monocytes, supporting ongoing input from circulating precursors. Exploratory pseudotime analysis further identified a transcriptional continuum from Ly6c2 + Ccr2 + monocytes toward macrophage states. Using MaFIA fetal thymic organ cultures, AP20187-mediated depletion of Csf1r- expressing myeloid cells reduced CD4 + CD8 + thymocyte differentiation and produced a coordinated accumulation of DN3 cells, loss of DN4 cells, and reduction in CD27 expression. These convergent changes identify the DN3-to-DN4 transition as a developmental stage that requires an intact Csf1r -expressing myeloid compartment, and establish a functional connection between the thymic myeloid niche and early αβ T cell development. Together, our study refines the phenotypic and developmental organization of mouse TMs and reveals a previously under-appreciated requirement for myeloid-cell support during progression through the β-selection checkpoint.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".