DNA-Redox Cation Interaction Improves the Sensitivity of an Electrochemical Immunosensor for Protein Detection
Bibliographic record
Abstract
A simple DNA-redox cation interaction enhancement strategy has been developed to improve the sensitivity of electrochemical immunosensors for protein detection. Instead of labeling with fluorophores or redox-active groups, the detection antibodies were tethered with DNA single strands. Based on the electrostatic interaction between redox cations ([Ru(NH3)6](3+)) and negatively charged DNA backbone, enhanced electrochemical signals were obtained. Human chorionic gonadotropin (hCG) detection has been performed as a trial analysis. A linear response range up to the concentration of 25 mIU/mL and a detection limit of 1.25 mIU/mL have been achieved, both are comparable with the ultrasensitive enzyme-linked immunosorbent assay (ELISA) tests. The method also shows great selectivity towards hCG over other hormones such as thyroid stimulating hormone (TSH) and follicle stimulating hormone (FSH). By and large, our approach bears the merits of cost effectiveness and simplicity of instrumentation in comparison with conventional optical detection methods.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".