Dendritic Cells from Mycobacteria-Infected Mice Inhibits Established Allergic Airway Inflammatory Responses to Ragweed via IL-10– and IL-12–Secreting Mechanisms
Bibliographic record
Abstract
Previous studies have demonstrated that Mycobacterium bovis bacillus Calmette-Guerin (BCG) infection can inhibit de novo and established allergen-induced asthma-like responses. The aim of this study was to examine the role of dendritic cells (DCs) in BCG infection-mediated inhibition of established allergy to a common environmental allergen--ragweed. The results showed that adoptive transfer of DCs from BCG-infected mice (DC[BCG]), in contrast to DCs from naive mice (DC[naive]), significantly inhibited established allergic airway eosinophilia and mucus overproduction. The inhibitory effect was correlated with alterations of allergen-driven cytokine and chemokine production as well as VCAM-1 expression in the lung. Flow cytometric analysis showed higher surface expression of CD8alpha and costimulatory markers in DC(BCG) than in DC(naive). Moreover, DC(BCG) produced significantly higher levels of IL-10 and IL-12 and expressed higher levels of TLRs than did DC(naive). Furthermore, blockade of IL-10 or IL-12 significantly reversed the inhibitory effect of DC(BCG) on established allergic airway inflammation and Th2 cytokine responses. These findings suggest that DCs play a crucial role in infection-mediated inhibition of established allergic responses, and IL-10 and IL-12 production by these DCs may be a major mechanism for the inhibition.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".