Respiratory and nasal symptoms during live-cat versus milled cat hair exposure
Bibliographic record
Abstract
Introduction: The Red Maple Trials NEC is a fixed exposure chamber where allergen shed from live cats is aerosolized using a modified robot vacuum. The Mobile NEC™ is a portable allergen exposure tent, where milled cat hair is aerosolized in a similar manner. This study was designed to compare the allergic response to cat antigen provocation in the Mobile NEC™ and the Fixed NEC™. Method: Cat allergic subjects (skin-prick test mean diameter ≥5mm) underwent a 2-hour exposure to cat allergen in the Fixed NEC and the Mobile NEC. Fel d 1 measured by sampling pumps was quantified by ELISA. Nasal, ocular and respiratory symptoms were measured every 10 minutes and spirometry every 20 minutes. Subjects with an FEV1 fall ≥20% of baseline or low nasal symptom scores during the first challenge were not rechallenged. Results: Eight subjects completed both challenges. Mean Total Nasal Symptom Score (TNSS) was higher in the Mobile NEC for most of the 2-hour duration (p<0.001); however, TNSS averaged over the last 30 minutes was not (paired t-test, p=0.16; mean (SE) 6.1 (1.2) and 4.5 (0.6), Mobile and Fixed NEC , respectively). Although there was no difference in FEV1 between the two challenges (p=0.52), respiratory symptom scores were higher in the Mobile NEC over the last 60 minutes of the exposure (p=0.002). There was no difference in average Fel d 1 concentrations between the chambers (Mobile: 55; Fixed: 54 ng/m3). Conclusions: The Mobile NEC offers comparable cat-allergen exposure and nasal and respiratory responses to the Fixed NEC. Its portability facilitates expansion to multi-site chamber studies for clinical validation of allergy therapies. Future work could expand its capabilities to other aeroallergens.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".