Measurement of wheat gluten and barley hordeins in contaminated oats from Europe, the United States and Canada by Sandwich R5 ELISA
Bibliographic record
Abstract
OBJECTIVES: We have investigated the extent of contamination with wheat, barley, rye or a mixture of these cereals in a large number of grains and commercial oats. We have also attempted to identify the type of cereal contaminant. METHODS: Sandwich R5 ELISA (using either gliadins or hordeins as standards), western blot, matrix-assisted laser desorption/ionization time-of-flight mass spectrometric and quantitative real-time PCR (Q-PCR) techniques have been used to analyze a total of 134 oats, comprising grains and commercial oat products collected from Europe, the United States and Canada. RESULTS: Twenty-five of the 134 pure, uncontaminated oat varieties were found to have undetectable levels of gluten, whereas most of the 109 grains and commercial oat products were mainly contaminated with mixtures of wheat, barley and rye, barley being the predominant contaminant. The percentages of these cereals in the oat samples have been calculated by specific wheat, barley and rye Q-PCR systems. The oat samples were grouped according to the avenin spectra determined by the mass spectrometric technique. The data confirmed that contaminated oat foods, based on the same variety, could have different levels of wheat, barley and rye contamination. CONCLUSION: This study has verified that contamination with wheat gliadins or barley hordeins in oat samples can be measured by the Sandwich R5 ELISA, using either gliadins or hordeins as standards, and also the importance of using confirmatory techniques (such as western blot, Q-PCR and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry) to confirm that most oats are contaminated with mixtures of wheat, barley and rye.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".