Co-exposure to allergen and diesel exhaust enhance inflammatory responses in human airway submucosa
Bibliographic record
Abstract
Asthma is a chronic condition described by inflammation of the airways and lungs. Diesel exhaust (DE) is a major contributor to ambient particulate matter (PM) air pollution. There is rising evidence that PM acts as adjuvant on the immune responses and may lead to augmentation of allergic inflammation [ 1 , 2 ]. We aim to elucidate if DE increases allergen-induced inflammation and cellular immune response in the airways of atopic human subjects. 15 volunteer participants with allergy to house dust mite allergen (Der p 1), birch or Timothy grass were recruited. In a randomized fashion, subjects inhaled DE (300µg PM 2.5 /m ) or filtered air for 120 minutes. One hour following the exposure, the extract of an aeroallergen to which the individual is sensitive, or placebo (sterile saline), was instilled into contralateral lung segments through bronchoscopy. Endobronchial biopsies from these same segments were then acquired 48 hours after each exposure. This was repeated 4 weeks later in each subject with the alternative inhalant. Thus, biopsies under 4 different conditions were created: filtered air + saline (FAS), DE + saline (DES), filtered air + allergen (FAA) and DE + allergen (DEA). Biopsies were processed and embedded in glycol methanlacrylate acrylic resin and serial sections were cut to 2µm and used for immunostaining with monoclonal antibodies to tryptase and eosinophil cationic protein (ECP). The percent positivity and distribution of activated mast cells (tryptase+) and eosinophils (ECP+) were quantified in the bronchial submucosa by Aperio ImageScope software. The percent positivity for tryptase expression: FAS=0.54±0.05, DES=0.51±0.18, FAA=0.63±0.24, DEA= 0.94±0.23. The percent positivity for ECP expression: FAS=0.35±0.17, DES=0.38±0.11, FAA=0.61±0.14, DEA=0.73±0.33. Data are presented as mean ± SEM (n=6). Our preliminary data suggest that DE may enhance the inflammatory response to allergen in atopic individuals. This data is novel in the context of human lung tissue.
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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) | 0.000 | 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 | 0.000 |
| 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".