Impedimetric Detection of Cancer Markers Based on Nanofiber Copolymers
Bibliographic record
Abstract
The sensitive determination of folate receptors (FRs) in the early stages of cancer is of great significance for controlling the progression of cancerous cells. Many folic acid (FA)-based electrochemical biosensors have been utilized to detect FRs with promising performances, but most were complicated, non-reproducible, non-biocompatible, and time and cost consuming. Here, we developed an environmentally friendly and sensitive biosensor for FR detection. We proposed an electrochemical impedimetric biosensor formed by nanofibers (NFs) of bio-copolymers prepared by electrospinning. The biosensor combines the advantages of bio-friendly polymers, such as sodium alginate (SA) and polyethylene oxide (PEO) as an antifouling polymer, with FA as a biorecognition element. The NF nanocomposites were characterized using various techniques, including SEM, FTIR, zeta potential (ZP), cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS). We evaluated the performance of the NF biosensor using EIS and demonstrated FR detection in plasma with a limit of detection of 3 pM. Furthermore, the biosensor showed high selectivity, reliability, and good stability when stored for two months. This biosensor was constructed from 'green credentials' holding polymers that are highly needed in the new paradigm shift in the medical industry.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".