Functional crosstalk between dendritic cells and Foxp3+ regulatory T cells in the maintenance of immune tolerance
Bibliographic record
Abstract
Peripheral immune tolerance requires a controlled balance between the maintenance of self-tolerance and the capacity to engage protective immune responses against pathogens. Dendritic cells (DCs) serve as sentinels of the immune system by sensing environmental and inflammatory signals, and play an essential role in the maintenance of immune tolerance. To achieve this, DC play a key role in dictating the outcome of immune responses by influencing the balance between inflammatory or Foxp3(+) regulatory T (T(reg)) cell responses. At the heart of this immunological balance is a finely regulated DC and T(reg) cell crosstalk whereby T(reg) cells modulate DC phenotype and function, and DC drive the differentiation of Foxp3(+) T(reg) cells in order to control immune responses. This review will focus on recent advances, which highlight the importance of this bidirectional DC and T(reg) cell crosstalk during the induction of tolerance and organ-specific autoimmunity. More specifically, we will discuss how T(reg) cells modulate DC function for the suppression of inflammatory responses and how DC subsets employ diverse mechanisms to drive differentiation of T(reg) cells. Finally, we will discuss the therapeutic potential of tolerogenic DCs for the induction of tolerance in autoimmune diseases.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".