Analysis of feline and canine allergen components in patients sensitized to pets
Bibliographic record
Abstract
BACKGROUND: Component resolved allergen diagnosis allows for a precise evaluation of the sensitization profiles of patients sensitized to felines and canines. An accurate interpretation of these results allows better insight into the evolution of a given patients sensitizations, and allows for a more precise evaluation of their prognoses. METHODS: 70 patients (42 women and 28 men, aged 18-65, with the average of 35.5) with a positive feline or canine allergy diagnosis were included in the research group. 30 patients with a negative allergy diagnosis were included in the control group. The total IgE levels of all patients with allergies as well as their allergen-specific IgE to feline and canine allergens were measured. Specific IgE levels to canine (Can f 1, Can f 2, Can f 3, Can f 5) and feline (Fel d 1, Fel d 2, Fel d 4) allergen components were also measured with the use of the ImmunoCap method. RESULTS: Monosensitization for only one canine or feline component was found in 30% of patients. As predicted, the main feline allergen was Fel d 1, which sensitized as many as 93.9% of patients sensitized to felines. Among 65 patients sensitized to at least one feline component, for 30 patients (46.2%) the only sensitizing feline component was Fel d 1. Only 19 patients in that group (63.3%) were not simultaneously sensitized to dogs and 11 (36.7%), the isolated sensitization to feline Fel d 1 notwithstanding, displayed concurrent sensitizations to one of the canine allergen components. Fel d 4 sensitized 49.2% of the research group.64.3% of patients sensitized to canine components had heightened levels of specific IgE to Can f 1. Monosensitization in that group occurred for 32.1% of the patients. Sensitization to Can f 5 was observed among 52.4% of the patients. CONCLUSIONS: Concurrent sensitizations to a few allergic components, not only cross-reactive but also originating in different protein families, are a significant problem for patients sensitized to animals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".