Interfacially Super-Assembled Tyramine-Modified Mesoporous Silica-Alumina Oxide Heterochannels for Label-Free Tyrosinase Detection
Bibliographic record
Abstract
Tyrosinase (TYR) is a multifunctional copper-containing enzyme that plays a critical role in the biosynthetic pathway of melanin. Thus, the detection of TYR activity possesses vast importance from clinical diagnosis to the food industry. However, most TYR detection methods are expensive, complicated, and time-consuming. Herein, a functional nanofluidic heterochannel composed of an ultrathin tyramine-modified mesoporous silica layer (Tyr-MS) and alumina oxide (AAO) arrays is constructed by an interfacial super-assembly method. The heterochannel with plenty of enzyme catalytic sites for TYR provides the response of the ion current signal against TYR concentrations. Introducing enzymatic reaction paves the way for the heterochannel to achieve label-free, selective, specific detection of TYR. Notably, a highly sensitive detection of TYR with a limit of 2 U mL –1 was obtained by optimizing the modified conditions. Detailed investigations and theoretical calculations further reveal the mechanism for the detection performance. This work provides a simple, low-cost, quick response, and label-free platform based on functional nanofluidic devices for enzyme-sensing technologies.
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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 | 0.000 | 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 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".