Monoclonal-Antibody-Based Immunoassays for the Mycotoxins NX-2 and NX-3 in Wheat
Bibliographic record
Abstract
The fungal infestation of crops can cause major economic losses. Toxins produced by the causative fungi (mycotoxins) represent a potential safety hazard to people and livestock consuming them. One such mycotoxin is deoxynivalenol (DON, also known as vomitoxin), a trichothecene associated with Fusarium Head Blight of wheat. DON is commonly found in cereal crops worldwide. A group of trichothecene mycotoxins closely related to DON, the NX toxins, have been reported to occur in the northeastern United States and southern Canada. While many commercial immunoassays are available to detect DON, there are no rapid screening assays for the NX toxins. We describe the development and isolation of three monoclonal antibodies (mAbs) specific towards two NX toxins: NX-2 and NX-3. The mAbs did not recognize DON or several other closely related trichothecenes. One of the mAbs was selected for development of an enzyme-linked immunosorbent assay (ELISA) for NX-2 and NX-3 in wheat. The dynamic ranges for the assay were 7.7 to 127 μg/kg for NX-2 and 59 μg/kg to 1540 μg/kg for NX-3 in wheat. Recoveries from spiked wheat averaged 84.4% for NX-2 and 99.3% for NX-3, with RSDs of 10.4% and 11.3%, respectively (n = 24). The results suggest that this assay can be used to screen for NX toxins in wheat at levels relevant to human food and animal feed safety.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".