Selective Nanomolar Detection of Dopamine Using a Boron-Doped Diamond Electrode Modified with an Electropolymerized Sulfobutylether-β-cyclodextrin-Doped Poly(<i>N</i>-acetyltyramine) and Polypyrrole Composite Film
Bibliographic record
Abstract
N-acetyltyramine was synthesized and electropolymerized together with a negatively charged sulfobutylether-beta-cyclodextrin on a boron-doped diamond (BDD) electrode followed by the electropolymerization of pyrrole to form a stable and permselective film for selective dopamine detection. The selectivity and sensitivity of the formed layer-by-layer film was governed by the sequence of deposition and the applied potential. Raman results showed a decrease in the peak intensity at 1329 cm(-1) (sp(3)), the main feature of BDD, upon each electrodeposition step. Such a decrease was correlated well with the change of the charge-transfer resistance derived from impedance data, i.e., reflecting the formation of the layer-by-layer film. The polycrystalline BDD surface became more even with lower surface roughness as revealed by scanning electron and atomic force microscopy. The modified BDD electrode exhibited rapid response to dopamine within 1.5-2 s and a low detection limit of 4-5 nM with excellent reproducibility. Electroactive interferences caused by 4-dihydroxyphenylalanine, 3,4-dihydroxyphenylacetic acid, ascorbic acid, and uric acid were completely eliminated, whereas the signal response of epinephrine and norepinephrine was significantly suppressed by the permselective film.
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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) | 0.001 | 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".