Sensitization to avian and fungal proteins in different work environments
Bibliographic record
Abstract
INTRODUCTION: Hypersensitivity pneumonitis (HP) is usually caused by the inhalation of avian and fungal proteins. The present study assesses a cohort of Urban Pest Surveillance and Control Service (UPSCS) workers with high exposure to avian and fungal antigens, in order to identify their degree of sensitization and the potential risk of developing HP. METHODS: Workers were divided according to their work activity into Nest pruners (Group 1) and Others (Group 2). All individuals underwent a medical interview, pulmonary function tests and the determination of specific IgG antibodies. Antigenic proteins of pigeon sera were analysed using two-dimensional immunoblotting. Proteins of interest were sequenced by liquid-chromatography-mass spectrometry (LC-MS). RESULTS: 101 workers were recruited (76 men, average age: 42 yrs); (Group 1 = 41, Group 2 = 60). Up to 30% of the study population exhibited increased levels of IgGs to pigeon, small parrot and parrot, and up to 60% showed high levels of Aspergillus and Penicillium IgGs. In Group 1, specific parakeet and Mucor IgGs were higher (p = 0.044 and 0.003 respectively) while DLCO/VA% were lower (p = 0.008) than in Group 2. Two-dimensional immunoblotting showed protein bands of 20-30 KDa recognized by HP patients but not by workers. LC-MS analysis identified Ig Lambda chain and Apolipoprotein A-I as candidate proteins for distinguishing HP patients from exposed workers. CONCLUSIONS: Two pigeon proteins were identified that may play a role in the development of pathological differences between HP patients and exposed workers. DLCO/VA may have a predictive value in the development of HP disease.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 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".