Immune Regulatory 1 Cells: A Novel and Potent Subset of Human T Regulatory Cells
Bibliographic record
Abstract
A subset of T regulatory cells (Tregs), identified by TIRC7 (T cell immune response cDNA 7) expression is designated as Immune Regulatory 1 Cells (IR1 cells). TIRC7 is an immune checkpoint inhibitor, co-localized with the T- cell receptor, HLA-DR and CTLA-4 during T-cell activation, which delivers regulatory signals via binding to its ligand, HLA-DR α2 domain. IR1 cells express FOXP3, and multiple other markers associated with immune suppression. They constitute as much as 10% of Tregs. IR1 cells strongly inhibit proliferation in mixed lymphocyte reactions, where they express high levels of IL-10. Ex vivo expansion of Tregs over 2 weeks in the presence of an agonist TIRC7 antibody disproportionately expands the IR1 Treg subset, while maintaining high expression of suppressive markers including CD39, IL-10, LAP and GARP. Ex vivo expanded IR1 cells are a potent, homogeneous, stable set of suppressor Tregs with the potential to modulate immune dysregulation. The characteristics of IR1 cells suggest a therapeutic advantage over polyclonal Tregs for therapeutic interventions. Early restoration of immune homeostasis using IR1 cells has the potential to fundamentally alter the natural history of conditions characterized by abnormalities in the T regulatory cell compartment.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".