Induction of immune tolerance and reduction of aggravated lung eosinophilia by co-exposure to Asian sand dust and ovalbumin for 14 weeks in mice
Bibliographic record
Abstract
BACKGROUND: Atmospheric contamination caused by Asian sand-dust (ASD) storms aggravates asthma in both human adults and children. This study aims to investigate a series of manifestations in allergic airway disease caused by co-exposure to allergens and ASD for 6 weeks and 14 weeks. METHODS: CD-1 Mice were instilled intratracheally with 0.1 mg of ASD/mouse four times (6 weeks) or eight times (14 weeks) at 2-week intervals (total dose of 0.4 mg or 0.8 mg/mouse) with or without ovalbumin (OVA). The pathologic changes in the airway, cytological alteration in bronchoalveolar lavage fluid (BALF), and levels of inflammatory cytokines/chemokines in BALF, and OVA-specific IgE and IgG1 antibodies in serum were measured in the treated CD-1 mice. RESULTS: Four-time co-exposure to OVA and ASD aggravates allergic airway inflammation along with Th2-cytokine IL-13 and eosinophil-relevant cytokine/chemokines IL-5, Eotaxin and MCP-3 in BALF, and fibrous thickening of the subepithelial layer in the airway. On the other hand, eight-time co-exposure attenuates these changes along with a significant increase of TGF-β1 in BALF. Adjuvant effects of ASD toward IgG1 and IgE production in sera were, however, still seen in the eight-time co-exposure. CONCLUSIONS: These results indicate that the immune responses in airways are exacerbated by four-time co-exposure to ASD with OVA, but that there is a shift to suppressive responses in eight-time co-exposure, suggesting that the responses are caused by TGF-β1-related immune tolerance.
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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 | 0.001 |
| Bibliometrics | 0.001 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".