Lewis Acid-Boosted Nanozyme for In Situ Metallization Electrochemical Sensing of Extracellular Vesicles
Bibliographic record
Abstract
Extracellular vesicles (EVs) mediate tumor progression by facilitating signal transduction between cancer cells and the microenvironment, positioning them as critical biomarkers for diagnosis. CD20 is a key surface antigen of B cells, and its detection is of great significance for lymphoma detection and therapy monitoring. However, conventional EVs detection methods suffer from high costs, operational complexity, and limited sensitivity. Here, we developed an electrochemical immunosensor utilizing a Lewis acid-boosted nanozyme, Ce/UiO-67, which was synthesized through a one-step hydrothermal method. Ce 4+ doping enhances its phosphatase-like activity by mimicking Zn 2+ –O–Zn 2+ active sites, catalyzing the hydrolysis of l -ascorbic acid-2-phosphate (SAP) to ascorbic acid (AA). The resultant AA reduces Ag + to Ag 0 for in situ deposition on the electrode, with the Ag 0 oxidation current quantified by differential pulse voltammetry (DPV) for specific CD20 detection on EVs. This sensor achieves a detection range of 5.12 × 10 2 to 1.6 × 10 7 particles/μL and a limit of detection (LOD) of 280 particles/μL, offering superior sensitivity and simplicity. Applied to clinical plasma, it distinguishes lymphoma patients from healthy individuals, demonstrating the potential for diagnosis and treatment evaluation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 teacher head, 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".