Expansion of FOXP3high regulatory T cells by human dendritic cells (DCs) in vitro and after injection of cytokine-matured DCs in myeloma patients
Bibliographic record
Abstract
CD4(+)CD25(+)FOXP3(+) regulatory T cells (Treg's) play an important role in the maintenance of immune tolerance. The mechanisms controlling the induction and maintenance of Treg's in humans need to be defined. We find that human myeloid dendritic cells (DCs) are superior to other antigen presenting cells for the maintenance of FOXP3(+) Treg's in culture. Coculture of DCs with autologous T cells leads to an increase in both the number of Treg's, as well as the expression of FOXP3 protein per cell both in healthy donors and myeloma patients. DC-mediated expansion of FOXP3(high) Treg's is enhanced by endogenous but not exogenous interleukin-2 (IL-2), and DC-T-cell contact, including the CD80/CD86 membrane costimulatory molecules. DCs also stimulate the formation of Treg's from CD25(-) T cells. The efficacy of induction of Treg's by DCs depends on the nature of the DC maturation stimulus, with inflammatory cytokine-treated DCs (Cyt-DCs) being the most effective Treg inducers. DC-induced Treg's from both healthy donors and patients with myeloma are functional and effectively suppress T-cell responses. A single injection of cytokine-matured DCs led to rapid enhancement of FOXP3(+) Treg's in vivo in 3 of 3 myeloma patients. These data reveal a role for DCs in increasing the number of functional FOXP3(high) Treg's in humans.
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 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".