Human CD4+ CD25hi Foxp3+ regulatory T cells are derived by rapid turnover of memory populations in vivo
Bibliographic record
Abstract
While memory T cells are maintained by continuous turnover, it is not clear how human regulatory CD4+ CD45RO+ CD25hi Foxp3+ T lymphocyte populations persist throughout life. We therefore used deuterium labeling of cycling cells in vivo to determine whether these cells could be replenished by proliferation. We found that CD4+ CD45RO+ Foxp3+ CD25hi T lymphocytes were highly proliferative, with a doubling time of 8 days, compared with memory CD4+ CD45RO+ Foxp3- CD25- (24 days) or naive CD4+ CD45RA+ Foxp3- CD25- populations (199 days). However, the regulatory population was susceptible to apoptosis and had critically short telomeres and low telomerase activity. It was therefore unlikely to be self regenerating. These data are consistent with continuous production from another population source. We found extremely close TCR clonal homology between regulatory and memory CD4+ T cells. Furthermore, antigen-related expansions within certain TCR Vbeta families were associated with parallel numerical increases of CD4+ CD45RO+ CD25hi Foxp3+ Tregs with the same Vbeta usage. It is therefore unlikely that all human CD4+ CD25+ Foxp3+ Tregs are generated as a separate functional lineage in the thymus. Instead, our data suggest that a proportion of this regulatory population is generated from rapidly dividing, highly differentiated memory CD4+ T cells; this has considerable implications for the therapeutic manipulation of these cells in vivo.
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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) | 0.001 | 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".