Development of a polyclonal antibody-based indirect competitive ELISA for determination of sterigmatocystin in wheat and corn flours
Bibliographic record
Abstract
Sterigmatocystin (STC) is a toxic secondary metabolite produced by more than 50 fungal species, including Aspergillus flavus, A. parasiticus, A. nidulans, and A. versicolor. The Joint FAO/WHO Expert Committee on Food Additives concluded that sterigmatocystin is genotoxic and carcinogenic with the critical effect determined to be carcinogenicity. The present study describes a simple method to prepare hapten and immunogens in order to generate polyclonal antibodies against this metabolite. We developed a sensitive and specific polyclonal antibody-based competitive indirect enzyme-linked immunosorbent assay (ciELISA) for monitoring STC in wheat and corn flours without the need for derivatisation of STC or clean-up of samples by immunoaffinity chromatography for quantification. The half inhibitory concentration (IC50) of the established method was 4.52 ± 0.81 ng mL−1, with the limit of detection (IC10) being 0.19 ± 0.04 ng mL−1 in wheat and corn flour matrices with the coefficient of variation of less than 22%.The assay was very specific to STC and showed no cross-reactivity with its analogue structures. The ELISA allowed for up to 5% methanol without significant influence on the IC50 value. Validation of the assay was performed by spiking STC into a blank flour matrix and the recoveries were in the range of 75.3 % to 104.5 % with a coefficient of variation less than 15%. A small retail survey was conducted by purchasing wheat (n = 8) and corn flours (n = 2) from local grocery stores. All of these retail samples were negative for STC using the developed ELISA method and were confirmed by LC-MS/MS. We demonstrated a rapid, simple, and reliable method for screening STC in wheat and corn flours.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".