S1pping fire: Sphingosine-1-phosphate signaling as an emerging target in inflammatory bowel disease and colitis-associated cancer
Bibliographic record
Abstract
Inflammatory bowel disease (IBD) is a complex disease that involves unpredictable and destructive inflammation in the gastrointestinal tract resulting in gastrointestinal symptoms, infection, and tissue destruction, and which can be associated with an increased risk of colon cancer. The underlying cause of IBD involves disruption of the innate and adaptive immune mechanisms that maintain homeostasis between the gut mucosa and its environment. Elucidating how the homeostatic mechanisms controlling gut mucosal immunity and inflammation are disrupted in IBD represents the first steps to identifying novel therapeutic targets. Sphingosine-1-phosphate (S1P) is a bioactive sphingolipid that is enriched in the blood and lymph, and functions in innate and adaptive immunity. S1P signaling regulates inflammation via its impact on the trafficking, differentiation, and effector functions of bone marrow-derived immune cells. S1P also activates nuclear factor kappa B and signal transducer and activator of transcription 3 inflammatory pathways. S1P is generated by the ubiquitously expressed lipid kinase, sphingosine kinase (SphK)1 and its tissue-restricted homolog, SphK2. S1P is irreversibly degraded by S1P lyase, which is highly expressed in enterocytes. Recent studies targeting S1P metabolism and signaling have shown promise in preclinical models of IBD and have shed light on the mechanisms by which S1P signaling impacts IBD. The evidence suggests that targeting S1P signaling and metabolism may represent a novel strategy in treating IBD and it may reduce colon cancer risk by interrupting the progression from inflammation to carcinogenesis.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".