BLIMP-1-dependent differentiation of T follicular helper cells into Foxp3+ T regulatory type 1 cells
Bibliographic record
Abstract
T-regulatory-type-1 (TR1) cells are a subset of interleukin-10-producing but Foxp3– Treg cells that arise in response to chronic antigenic stimulation. We have shown that systemic delivery of autoimmune disease-relevant peptide-major histocompatibility complex class II (pMHCII)-coated nanoparticles (pMHCII-NP) triggers the formation of large pools of disease-suppressing Foxp3– TR1 cells from cognate T-follicular helper (TFH) cell precursors. Here we show that, upon treatment withdrawal, these Foxp3– TR1 cells spontaneously differentiate into a novel immunoregulatory Foxp3+ TR1 subset that inherits epigenetic and transcriptional hallmarks of their precursors, including clonotypic T-cell receptors, and is distinct from other Foxp3+ Treg subsets. Whereas the transcription factor BLIMP-1 is dispensable for development of conventional Foxp3+ Treg cells, it is necessary for development of Foxp3+ TR1 cells. In a model of central nervous system autoimmunity, abrogation of BLIMP-1 or IL-10 expression in the Foxp3– and/or Foxp3+ TR1 subsets inhibits their development or anti-encephalitogenic activity. Thus, the TFH-TR1 transdifferentiation pathway results in the generation of two distinct autoimmune disease-suppressing, IL-10-producing TR1 subsets that are distinguished by the expression of Foxp3 and Foxp3 target genes.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".