Detection of immunoglobulin antibodies in the sera of patients using purified latex allergens
Bibliographic record
Abstract
BACKGROUND: Latex allergy is largely an occupational allergy due to sensitization to natural rubber latex allergens present in a number of health care and household products. Although several purified allergens are currently available for study, information on the usefulness of these purified, native or recombinant allergens in the demonstration of specific immunoglobulin (Ig) E in the sera of patients is lacking. OBJECTIVE: To evaluate the purified latex allergens and to demonstrate specific IgE antibody in the sera of health care workers and spina bifida patients with clinical latex allergy. METHODS: Two radioallergosorbent and an enzyme-linked immunosorbent assay (ELISA) using latex proteins Hev b 1, 2, 3, 4, 6 and 7 along with two glove extracts and Malaysian nonammoniated latex (MNA) were evaluated to demonstrate IgE in the sera of health care workers and spina bifida with latex allergy and controls with no history of latex allergy. RESULTS: ELISA using the purified latex allergens demonstrated specific IgE in 32-65% health care workers and 54-100% of spina bifida patients with latex allergy. The corresponding figures for RAST were 13-48 and 23-85 for RAST-1 and 19-61 and 36-57 for RAST-2. These results were comparable with the results obtained with glove extracts and crude rubber latex proteins. CONCLUSIONS: When used simultaneously, latex proteins Hev b 2 and Hev b 7 reacted significantly with specific serum IgE in 80% of health care workers and 92% of spina bifida patients with latex allergy by ELISA technique, while this combination gave lower positivity when the RASTs were used. By the addition of Hev b 3, specific IgE was detected in all spina bifida patients with latex allergy. Both RASTs failed to show specific IgE in the control subjects, while the ELISA showed significant latex-specific IgE in 22% of controls.
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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) | 0.001 | 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".