Adsorption–desorption nano-aptasensors: fluorescent screening assays for ochratoxin A
Bibliographic record
Abstract
In this study, a FRET-based fluorescent aptasensor for the detection of ochratoxin A (OTA) was optimized based on the quenching efficiency of single-walled carbon nanotubes (SWCNTs) and the binding affinity of aptamers. OTA aptamers were conjugated with quantum dots and adsorbed to the surface of both acid-modified and unmodified SWCNTs. The maximum fluorescence quenching efficiency of the SWCNTs were compared. Acid-modified SWCNTs (amSWCNTs) have moderate quenching efficiency, providing an optimal sensitivity for qualitative fluorescence-enhancement biosensor assays. The binding parameters of the QD-modified OTA aptamers (1.12.2 and A08min) on the surface of amSWCNTs were compared. Based on our results, the A08min aptamer is a better candidate for OTA detection. Using the A08min aptamer, the SWCNT method had a limit of detection (LOD) of 40 nM. The amSWCNT method had a significantly lower LOD of 14 nM. Turn-on fluorescent nano-aptasensors are emerging as an effective diagnostic tool for simple detection of mycotoxins. Nanocomplexes designed for the detection of mycotoxins in solution and paper-based tests have proven to be useful.
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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) | 0.001 | 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 | 0.001 |
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".