CXCR5/CXCL13 Interaction Is Important for Double-Negative Regulatory T Cell Homing to Cardiac Allografts
Bibliographic record
Abstract
Accumulating evidence indicates that regulatory T (Treg) cells control development of various diseases both systemically and locally. However, molecular mechanisms involved in Treg cell homing remain elusive. We have shown previously that alphabetaTCR(+)CD3(+)CD4(-)CD8(-) double-negative (DN) Treg cells selectively accumulate in tolerant allografts to maintain localized immune regulation. However, the molecular mechanism leading to the accumulation of DN Treg cells in tolerant grafts was not known. Our cDNA microarray analysis revealed significant up-regulation of chemokine receptor CXCR5 mRNA in DN Treg clones compared with nonregulatory clones. In this study, we examined the importance of CXCR5 in mediating DN Treg migration. Compared with CD4 and CD8 T cells, both primary DN Treg cells and clones constitutively express high levels of CXCR5 protein, enabling them to migrate toward increasing CXCL13 gradients in vitro. After infusion into recipient mice, CXCR5(+) DN Treg clones, but not their CXCR5(-) mutants, preferentially accumulated in cardiac allografts and could prevent graft rejection. Furthermore, we found that allogeneic cardiac allografts express high levels of CXCL13 mRNA compared with either recipient native hearts or nontransplanted donor hearts. Ab neutralization of CXCL13 abrogated DN Treg cell migration in vitro and prevented in vivo homing of DN Treg clones into allografts. These data demonstrate that DN Treg cells preferentially express CXCR5, and interaction of this chemokine receptor with its ligand CXCL13 plays an important role in DN Treg cell migration both in vitro and 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) | 0.002 | 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".