Serial OX40 Engagement on CD4+ T Cells and Natural Killer T Cells Causes Allergic Airway Inflammation
Bibliographic record
Abstract
RATIONALE: OX40-OX40 ligand (OX40L) interactions have been proposed to support induction of allergic airway inflammation, which may be attributable to OX40 signaling in CD4(+) helper T cells for adaptive immune responses. However, a possible involvement of natural killer T (NKT) cells in the pathogenesis suggests that the underlying mechanisms are not yet fully elucidated. OBJECTIVES: We aimed to characterize the OX40-modulated cellular contribution to allergic airway inflammation in a mouse model of house dust mite (HDM) allergen exposure. METHODS: Mice were sensitized to HDM and, 3 weeks later, challenged with HDM on three consecutive days through the airways. Two days after the last exposure, bronchoalveolar lavage fluids and blood samples and lung tissues were evaluated for the airway inflammation. MEASUREMENTS AND MAIN RESULTS: The development of HDM-induced eosinophilic airway inflammation was dependent on OX40 of both CD4(+) T cells and NKT cells; OX40 engagement on CD4(+) T cells in the sensitization led to pulmonary OX40L augmentation after the allergen challenge, which stimulated pulmonary NKT cells through OX40 to provide the pathogenic cytokine milieu. This was ablated by OX40L blockade by inhalation of the neutralizing antibody during the challenge, suggesting the therapeutic potential of targeting pulmonary OX40-OX40L interactions. Moreover, OX40 expression in CD4(+) T cells, but not in NKT cells, was reciprocally regulated by the helper T cell type 1-skewing transcription factor Runx3. CONCLUSIONS: OX40 on not only CD4(+) T cells but also NKT cells is involved in allergic airway inflammation. Notably, pulmonary blockade of OX40 ligation on NKT cells has therapeutic implications.
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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) | 0.002 | 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".