An Impedimetric‐Fluorescence Double‐Checking Biosensor with Enhanced Reliability Based on Graphene Oxide
Bibliographic record
Abstract
MicroRNA (miRNA) is a class of clinically significant diagnostic and prognostic markers for some diseases, especially for cancer. Graphene oxide (GO) has been reported to bind and quench dye‐labeled single‐stranded DNA (ssDNA) probes while it has less affinity toward double‐stranded DNA (dsDNA) or hybrids of DNA/RNA. This property makes it very suitable to construct a double‐checking system for miRNA detection, thus increasing the reliability of detection. This kind of double‐checking sensor will have great potential in clinical diagnosis. Based on this concept, in this study a simple and sensitive electrochemical impedance spectroscopy biosensor for miRNA‐21 is developed using a GO‐coated electrode. Simultaneously, the fluorescence of the remaining hybridization solution which contains dissociated duplex of ssDNA/miRNA is also investigated to double check the signal and increase its reliability. Therefore, a GO‐based double‐checking biosensor is developed for miRNA‐21 detection, which shows simplicity, high sensitivity and selectivity, and outstanding reliability. This is the first time to integrate the electrochemical impedimetric method and fluorescence method in one sensing system for detecting miRNA based on GO. It is believed that this work will have a profound impact on the design of graphene‐based biosensors for miRNA detection.
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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 | 0.000 |
| 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".