Chemokine production by regulatory T cells is required for therapeutic attenuation of autoimmunity and allograft rejection
Bibliographic record
Abstract
Abstract Regulatory T cells (Tregs) control immune homeostasis by preventing inappropriate responses to self and non-harmful foreign antigens. Tregs use multiple mechanisms to control immune responses, all of which require Tregs to be near their targets of suppression, but how Treg-to-target proximity is controlled is unknown. We found that Tregs produce chemokines to attract CD4+ and CD8+ T cells close to their proximity in vitro and in vivo. Mouse and human lineage committed Tregs, as well as murine in vitro induced Tregs, produced CCL3 and CCL4 at message and protein level. Chemokine producing Tregs had an activated Treg phenotype with high expression of multiple proteins associated with suppressive function. Furthermore the human CCL3 and CCL4 promoter could be transactivated by FOXP3. In vitro and in vivo migration experiments indicated that CCR5 was the major receptor required by target cells. CCL3 and CCL4 deficient Tregs were impaired in their ability to prevent experimental autoimmune encephalomyelitis or islet allograft rejection, but suppressive in a standard in vitro assay. Moreover, Tregs from subjects with established type 1 were impaired in their ability to produce CCL3 and CCL4. These results demonstrate a previously unknown facet of Treg function and suggest that chemokine secretion by Tregs is a fundamental aspect of their in vivo function and therapeutic effect in autoimmunity and transplantation.
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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) | 0.001 | 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".