IL-12-Dependent Vascular Cell Adhesion Molecule-1 Expression Contributes to Airway Eosinophilic Inflammation in a Mouse Model of Asthma-Like Reaction
Bibliographic record
Abstract
Bronchial-alveolar eosinophilic inflammation is among the characteristic pathological changes in asthma, which has been shown to be correlated with type 2 cytokine and chemokine production. Exogenous IL-12 has been found to be inhibitory for pulmonary eosinophilia in reported studies. Using a murine asthma-like model induced by OVA, we found in the present study that IL-12 gene knockout (KO) mice showed substantially reduced airway recruitment of eosinophils compared with wild-type control mice following OVA sensitization/challenge, although the levels of circulating eosinophils were comparable in these two groups of mice. Cytokine analysis showed Ag-driven Th1 (IFN-gamma) and Th2 (IL-4, IL-5, IL-10, and IL-13) cytokine production by CD4 T cells from local draining lymph nodes and spleen. Similarly, local eotaxin production was comparable in wild-type and IL-12 KO mice. In contrast, immunohistochemical analysis showed that the expression of VCAM-1 on the lung endothelium of IL-12 KO mice was dramatically less than that in wild-type mice. Furthermore, administration of rIL-12 at the stage of sensitization and challenge with OVA restored airway eosinophilia and VCAM-1 expression in IL-12 KO mice. The results suggest that endogenous IL-12 contributes to the recruitment of eosinophils into airways observed in asthma, possibly via enhancement of the expression of VCAM-1 on local vascular endothelial cells.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".