Microfabricated electrochemical aptasensing chip modified with dual-function antifouling linker for single-drop label-free assay of oxytetracycline in milk
Bibliographic record
Abstract
Abstract The fabrication and characterization of a novel integrated electrochemical aptasensing device and its application to oxytetracycline (OTC) determination in milk is described. The microfabricated three-electrode chip is composed of gold working and counter electrodes and a silver reference electrode deposited on a Kapton film by physical vapor deposition. The working electrode is modified with α-lipoic acid-NHS, an antifouling linker, onto which an amine-modified OTC-specific aptamer is further attached. The label-free assay of OTC involves incubation of the sample with the linker/aptamer bioconjugate immobilized on the working electrode and monitoring of the OTC-aptamer binding event by means of the electrochemical response of the [Fe(CN)6]3−/[Fe(CN)6]4− redox couple, The decrease of the signal magnitude, induced by blocking the diffusion of the probe, is related to the concentration of OTC. The limit of detection for OTC is 7 ng mL−1 and the inter-sensor reproducibility is 13.7%. The sensor is applied to milk samples with recoveries between 107 and 110%. This aptasensing chip demonstrates strong potential for rapid on-site detection of OTC in the food industry due to its high degree of integration, easy functionalization, and potential for single-drop operation. Graphical abstract
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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) | 0.001 | 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) | 0.003 | 0.002 |
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".