A key role for IL‐7R in the generation of microenvironments required for thymic dendritic cells
Bibliographic record
Abstract
Interleukin‐7 receptor (IL‐7R) signaling is critical for multiple stages of T‐cell development, but a role in the establishment of the mature thymic architecture needed for T‐cell development and thymocyte selection has not been established. Crosstalk signals between developing thymocytes and thymic epithelial cell (TEC) precursors are critical for their differentiation into cortical TECs (cTECs) and medullary TECs (mTECs). In addition, mTEC‐derived factors have been implicated in the recruitment of thymic dendritic cells (DCs) and intrathymic DC development. We therefore examined corticomedullary structure and DC populations in the thymus of Il7r−/− mice. Analysis of TEC phenotype and spatial organization revealed a striking shift in the mTEC to cTEC ratio, accompanied by disorganized corticomedullary structure. Several of the thymic subsets known to have DC potential were nearly absent, accompanied by reductions in DC cell numbers. We also examined chemokine expression in the Il7r−/− thymus, and found a significant decrease in mTEC‐derived CCR7 ligand expression, and high levels of cTEC‐derived chemokines, including CCL25 and CXCL12. Although splenic DCs were similarly affected, bone marrow (BM) precursors capable of giving rise to DCs were unperturbed. Finally, BM chimeras showed that there was no intrinsic need for IL‐7R signaling in the development or recruitment of thymic DCs, but that the provision of wild‐type progenitors enhanced reconstitution of thymic DCs from Il7r−/− progenitors. Our results are therefore supportive of a model in which Il7r‐dependent cells are required to set up the microenvironments that allow accumulation of thymic DCs.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".