MXene Nanoconfinement of SAM-Modified Molecularly Imprinted Electrochemical Biosensor for Point-of-Care Monitoring of Carcinoembryonic Antigen
Bibliographic record
Abstract
MXene and imprinted ortho-phenylenediamine (o-PD) for the detection of carcinoembryonic antigen (CEA), a biomarker for various cancers surveillance, especially colorectal cancer (CRC). Accordingly, MXene was drop-casted on the surface of a disposable silver electrode to increase the sensitivity and create high-energy nanoareas on the surface, which are usable for protein immobilization and detection. A self-assembled monolayer (SAM) was exploited for oriented CEA immobilization on the MXene-modified electrode. The monomer-protein interaction and successful protein removal were confirmed by molecular docking and atomic force microscopy (AFM) investigations to evaluate the quality of the fabricated molecularly imprinted polymer (MIP). Also, the role of MXene in increasing the electrical field inside the nanoareas was simulated using COMSOL Multiphysics software. A suitable limit of detection (9.41 ng/mL), an appropriate linear range of detection (10 to 100 ng/mL) in human serum, and a short detection time (10 min) resulted from the use of SAM/MIP next to MXene. This biosensor presented outstanding repeatability (97.60%) and reproducibility (98.61%). Moreover, acceptable accuracy (between 93.04 and 116.04%) in clinical serum samples was obtained compared with immunoassay results, indicating the high potential of our biosensor for real sample analysis. This biomimetic and disposable sensor provides a cost-effective method for facile and POC monitoring of cancer patients during treatment.
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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) | 0.001 | 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".