Intrinsic “Turn-On” Aptasensor Detection of Ochratoxin A Using Energy-Transfer Fluorescence
Bibliographic record
Abstract
Ochratoxin A (OTA) is an intrinsically fluorescent phenolic mycotoxin that contaminates a wide range of food products and is a serious health threat to animals and humans. An OTA binding aptamer (OTABA) that folds into an antiparallel G-quadruplex (GQ) in the absence and presence of target OTA has been incorporated into a vast variety of aptasensor platforms for OTA detection. The development of a simple, aptamer-based approach would allow for detection of the toxin without the use of complex analytical instrumentation, which has been the gold standard for OTA detection thus far. However, to date, none of the aptasensor platforms have utilized the natural fluorescence of the phenolic toxin for detection. Herein, we report that OTA binding to OTABA involves π-stacking interactions that lead to GQ-to-toxin energy transfer (ET), which affords a "turn-on" fluorescence self-signaling platform in which the emission of the aptamer-target complex is enhanced in comparison to the free toxin alone. Selective excitation of the GQ-OTA complex at 256 nm leads to a 4-fold enhancement in OTA fluorescence. The GQ-OTA ET detection platform boasts a limit of detection ∼2 ng/mL, which is comparable to a previously demonstrated fluorescence resonance energy transfer immunoassay platform for OTA detection, and displays excellent OTA selectivity and recovery from red wine samples.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".