S1P1 Contributes to Endotoxin-enhanced B-Cell Functions Involved in Hypersensitivity Pneumonitis
Bibliographic record
Abstract
Abstract In a proportion of patients with hypersensitivity pneumonitis, the biological and environmental factors that sustain inflammation are ill defined, resulting in no effective treatment option. Bioaerosols found in occupational settings are complex and often include Toll-like receptor ligands, such as endotoxins. How Toll-like receptor ligands contribute to the persistence of hypersensitivity pneumonitis, however, remains poorly understood. In a previous study, we found that an S1P1 (sphingosine-1-phosphate receptor 1) agonist prevented the reactivation of antigen-driven B-cell responses in the lung. Here, we assessed the impact of endotoxins on B-cell activation in preexisting hypersensitivity pneumonitis and the role of S1P1 in this phenomenon. The impact of endotoxins on pre-established hypersensitivity pneumonitis was studied in vivo. S1P1 levels were tracked on B cells in the course of the disease using S1P1-eGFP knockin mice, and the role of S1P1 on B-cell functions was assessed using pharmacological tools. S1P1 was found on B cells in experimental hypersensitivity pneumonitis. Endotoxin exposure enhanced neutrophil accumulation in the BAL of mice with experimental hypersensitivity pneumonitis. This was associated with enhanced CD69 cell-surface expression on lymphocytes in the BAL. In isolated B cells, endotoxins increased cell-surface levels of costimulatory molecules and CD69, which was prevented by an S1P1 agonist. S1P1 modulators also reduced TNF production by B cells and their capacity to trigger T-cell cooperation ex vivo. An S1P1 ligand directly inhibited endotoxin-induced B-cell activation.
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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) | 0.000 | 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 | 0.001 | 0.001 |
| 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".