A Sphingosine-1-Phosphate Receptor 1-Directed Agonist Reduces Central Nervous System Inflammation in a Plasmacytoid Dendritic Cell-Dependent Manner
Bibliographic record
Abstract
Gradients of the sphingolipid sphingosine-1-phosphate (S1P) are responsible for the egress of lymphocytes from lymph nodes by activating the S1P1 receptor expressed on the surface of lymphocytes. Small molecule drugs that downregulate S1P receptors induce the sequestration of lymphocytes within lymph nodes, thus preventing lymphocytes from accessing sites of inflammation. In particular, FTY720, a pan-S1P receptor agonist, has been efficacious in the treatment of multiple sclerosis as well as its animal model, experimental autoimmune encephalomyelitis (EAE), by virtue of its ability to restrain lymphocytes within the lymph nodes, thus precluding their migration into the CNS. However, multiple leukocyte subsets express S1P receptors of varying types, and although it is beneficial to prevent transmigration of proinflammatory lymphocytes into the CNS, allowing access of regulatory leukocyte subsets to the CNS is desirable. In this study, we show that an S1P1-specific agonist (AUY954) is clinically efficacious in ameliorating pre-established EAE in SJL/J mice. Efficacy of AUY954 correlated with a reduction of lymphocytes in the CNS, but access of plasmacytoid dendritic cells (pDCs) to the CNS was unimpaired, and the presence of pDCs was found to be an important cofactor in mediating the clinical efficacy of AUY954. These results indicate that pDCs are important in quieting autoimmune responses during EAE, and that trafficking inhibitors that are permissive for pDC accumulation in the CNS may be of therapeutic value for the treatment of multiple sclerosis.
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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".