Inducible IL10+ Suppressor B Cells Inhibit CNS Inflammation and T Helper 17 Polarization
Bibliographic record
Abstract
Granulocyte-macrophage colony-stimulating factor (GMCSF) and MCP3 (aka CCL7) exert complementary, nonoverlapping, proimmune effects on responsive lymphoid and myeloid cells. We hypothesized that a synthetic cytokine linking GMCSF to MCP3 (hereafter GMME3) as part of a single polypeptide would acquire novel, therapeutically desirable immunomodulatory properties. We demonstrate that GMME3 has enhanced CC-chemokine receptor (CCR)-mediated intracellular Ca(++) mobilization with selective effects on the CD21(hi)CD24(hi) CD1.d(hi) subset of splenic B cells inducing substantial interleukin 10 (IL10) production. We demonstrate that B(GMME3) exert their suppressive effect through an IL10-mediated inhibition of antigen presentation. More importantly, B(GMME3) inhibit the reactivation of encephalomyelitis (EAE)-derived or TGFβ/IL6 differentiated Th17 cells by altering their polarization toward a Th1 or Th2 phenotype. The secretion of interferon-γ (IFNγ) and IL4 in turn inhibits IL17 production. The adoptive transfer of B(GMME3), but not IL10(-/-) B(GMME3) cells, to mice symptomatic with experimental autoimmune encephalitis significantly improves their disease score and inhibits lymphoid infiltration into the central nervous system (CNS). We propose that designed CCR modulators such as GMME3, allows for conversion of naive B-cells to a novel suppressor phenotype allowing for the personalized cell therapy of autoimmune ailments.
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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".