Sphingosine-1-Phosphate Receptors in the Central Nervous and Immune Systems
Bibliographic record
Abstract
Sphingosine-1-phosphate receptor (S1PR) modulators have entered clinical practice as immune-modulators for the treatment of multiple sclerosis (MS). Pharmacologic modulation of S1PR expression on lymphocytes inhibits these cells capacity to respond to the S1P gradient within regional lymph nodes (LNs) (and thymus) that promotes their exit into peripheral circulation. The resultant peripheral blood restricted lymphopenia is considered to underlie the capacity of S1PR modulators to reduce new inflammatory lesion formation in MS in the absence of global immune suppression. These modulators also regulate entry of selective lymphocyte populations and dendritic cells (DCs) into LNs and modulate sphingosine-1-phosphate (S1P) cell signaling networks that govern the generation of specific cell subsets within LNs. S1PR modulators that access the CNS can also have functional effects within this compartment since S1PRs are expressed by cells comprising the blood brain barrier (BBB) and by those within the parenchyma, including neurons, astrocytes, oligodendrocytes and microglia. Absence of S1P1 receptor (S1PR1) on astrocytes reduces disease severity in experimental autoimmune encephalomyelitis (EAE). Even under conditions that inhibit cell responses to the natural ligand, S1PR modulators can continue to induce active signaling responses; such responses may be relevant for promoting neuroprotection and augmenting tissue repair within the CNS.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".