Mycobacterial infection inhibits established allergic inflammatory responses via alteration of cytokine production and vascular cell adhesion molecule‐1 expression
Bibliographic record
Abstract
Our previous studies, as well as those of others, have demonstrated that local or systemic Mycobacterium bovis bacille Calmette-Guérin (BCG) infection can inhibit de novo allergen-induced asthma-like reactions, but the effect of this infection on established allergic responses is unknown. The aim of this study was therefore to examine the effect of mycobacterial infection on established allergy in a murine model of asthma-like reaction. Mice were sensitized with ovalbumin (OVA) in alum followed by infection with BCG and subsequent intranasal challenge with the same allergen. In some experiments, mice were sensitized with OVA followed by intranasal challenge with OVA and then given BCG infection with subsequent rechallenge with OVA. Mice without BCG infection but treated with OVA in the same manner, were used as a control. The mice were examined for immunoglobulin E (IgE) response and eosinophilic inflammation, mucus production, cytokine/chemokine patterns and adhesion molecule expression in the lung. The results showed that postallergen BCG infection suppressed the established airway eosinophilia and mucus overproduction, but not IgE responses. The inhibition of asthma-like reactions by BCG infection was correlated with a shift of allergen-driven cytokine production pattern and, more interestingly, with a dramatic decrease of vascular cell adhesion molecule-1 (VCAM-1) expression in the lung. These findings suggest that intracellular bacterial infection can inhibit established allergic responses via alteration of local cytokine production and the expression of adhesion molecules.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.000 | 0.001 |
| 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".