Graphene Oxide-Assisted Aptamer-Based Fluorescent Detection of Tetracycline Antibiotics
Bibliographic record
Abstract
Tetracyclines are a group of common antibiotics, but owing to their toxicity, most of them are only used in animal husbandry and veterinary medicine. A DNA aptamer for tetracyclines has recently been reported. Upon aptamer binding, the fluorescence of tetracyclines was enhanced. This unique fluorescence enhancement was used to selectively detect the tetracyclines. The purpose of this study was to use graphene oxide (GO) to suppress the background fluorescence for enhanced detection. First, the adsorption of doxycycline on GO was studied. At pH 8.0, 82.7% of doxycycline was adsorbed by GO, and adding 2 µM aptamer desorbed 55.4% of doxycycline. With GO, the signal increase was comparable from pH 6 to 8, whereas without GO, the increase was significantly lower at pH 8. Under optimized condition, a detection limit of 1.6 nM doxycycline was achieved at pH 8.0 in the presence of GO, whereas without GO, the detection limit was 18.9 nM. This is an interesting example of the use of nanomaterials to enhance the performance of aptamer-based biosensors.
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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 | 0.000 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".