Binding-Induced DNA Dissociation Assay for Small Molecules: Sensing Aflatoxin B1
Bibliographic record
Abstract
We describe a new fluorescence turn-on sensor for homogeneous detection of aflatoxin B1 (AFB1), a potent low molecular weight mycotoxin. A key innovation is the binding-induced intramolecular interaction involving the following two sets of probes: (1) a gold nanoparticle (AuNP) immobilized with hundreds of assistant oligonucleotides (AO) and dozens of anti-AFB1 monoclonal antibodies, and (2) the AFB1-BSA (BSA = bovine serum albumin) antigen conjugated with fluorophore-labeled signal oligonucleotides (SO) that contained a short sequence complementary to AO. Specific binding of AFB1-BSA to the antibody brought the fluorophore very close to the surface of the AuNP through a stable intramolecular hybridization between AO and SO, resulting in efficient quenching of fluorescence. The improved fluorescence quenching substantially reduced the background, due to the binding-induced intramolecular hybridization, and improved the signal-to-background ratio by 390%. In the presence of AFB1 in a sample, competitive binding of AFB1 in the sample to the antibodies immobilized on the AuNP caused the release of the fluorophore-labeled AFB1-BSA from the AuNP, turning on fluorescence. A detection limit of 2.3 nM was achieved, which meets the requirement for AFB1 detection at regulatory levels. Analyses of rice samples using this assay showed recoveries of 86-102%. Incorporating appropriate antibody probes could extend the assay to the detection of other small molecules.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 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".