Cutting Edge: CD47 Controls the In Vivo Proliferation and Homeostasis of Peripheral CD4+CD25+Foxp3+ Regulatory T Cells That Express CD103
Bibliographic record
Abstract
Peripheral CD103(+)Foxp3(+) regulatory T cells (Tregs) can develop both from conventional naive T cells upon cognate Ag delivery under tolerogenic conditions and from thymic-derived, expanded/differentiated natural Tregs. We here show that CD47 expression, a marker of self on hematopoietic cells, selectively regulated CD103(+)Foxp3(+) Treg homeostasis at the steady state. First, the proportion of effector/memory-like (CD44(high)CD62L(low)) CD103(+)Foxp3(+) Tregs rapidly augmented with age in CD47-deficient mice (CD47(-/-)) as compared with age-matched control littermates. Yet, the percentage of quiescent (CD44(low)CD62L(high)) CD103(-)Foxp3(+) Tregs remained stable. Second, the increased proliferation rate (BrdU incorporation) observed within the CD47(-/-)Foxp3(+) Treg subpopulation was restricted to those Tregs expressing CD103. Third, CD47(-/-) Tregs maintained a normal suppressive function in vitro and in vivo and their increased proportion in old mice led to a decline of Ag-specific T cell responses. Thus, sustained CD47 expression throughout life is critical to avoid an excessive expansion of CD103(+) Tregs that may overwhelmingly inhibit Ag-specific T cell responses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".