Allergen extracts and recombinant proteins: comparison of efficiency of in vitro allergy diagnostics using multiplex assay on a biological microchip
Bibliographic record
Abstract
BACKGROUND: Immunological test systems for diagnostics of type I hypersensitivity involve the following types of antigens: whole allergen extracts, individual highly purified proteins and their recombinant analogues. The goal of this study was to compare the results obtained with whole allergen extracts (birch pollen, cat dander, and timothy grass pollen) and their respective recombinant proteins in biochip-based immunoassay. METHODS: Multiplex fluorescent immunoassay of 139 patients' blood serum samples was carried out using biological microchips (biochips). sIgE concentrations for the chosen allergens and their recombinant components were measured. ROC analysis was used for comparison of the results and determination of diagnostic accuracy. RESULTS: The results for the birch pollen extract and its recombinant allergens have shown that the diagnostic accuracy of the methods utilizing the whole allergen extract, its major component Bet v 1 and the combination of major and minor components (Bet v 1 and Bet v 2) was the same. Values for diagnostic accuracy for the cat dander extract and its major recombinant component Fel d 1 were equal. In contrast with birch pollen and cat dander allergens, using of recombinant components of timothy grass pollen (Phl p 1, Phl p 5, Phl p 7 and Phl p 12) did not allow reaching the diagnostic accuracy of using natural extract. CONCLUSIONS: Multiplex analysis of samples obtained from patients with allergy to birch pollen and cat dander using biological microchips has shown that comparable accuracy was observed for the assay with natural extracts and recombinant allergens. In the case of timothy grass allergen, using the recombinant components may be insufficient.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| 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".