MXene Nanoconfinement of SAM-Modified Molecularly Imprinted Electrochemical Biosensor for Point-of-Care Monitoring of Carcinoembryonic Antigen
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 it