Nanozyme-Linked Immunosorbent Assays: A Kinetic Perspective
Bibliographic record
Abstract
Nanozymes with peroxidase-like (POD) activity are increasingly utilized as functional replacements for horseradish peroxidase in various assays. In particular, their application in enzyme-linked immunosorbent assays (ELISA) has led to the development of nanozyme-linked immunosorbent assays (NLISA). NLISA follow the well-established ELISA procedure and have been reported for a wide range of nanozymes and analytes. However, most developments overlook the fundamental differences between enzyme and nanozyme catalysis, often resulting in nonoptimal protocols in a kinetically limited regime. Herein, using core@shell Au@Pt and Au@Pd POD-like nanozymes, we demonstrate significant differences in the Michaelis-Menten constant depending on the shell thickness. Furthermore, for the first time, we report the unusually high stability of POD-like activity at ultralow pH values (down to minus 0.56). This unique feature enabled us to propose new strategies for terminating the catalytic reaction. In summary, we show that consideration of the distinct catalytic properties of nanozymes enables the development of NLISA protocols with up to an order of magnitude higher sensitivity and minimized background.
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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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.001 | 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".