Simultaneous and Individual Determination of Six Redox-Active Biomolecules Using a Modified Graphite Paste Electrode with Immobilized Ferric Cyanide-Chitosan Polymer Ion Pair on the Multi-Walled Carbon Nanotubes
Bibliographic record
Abstract
Redox-active biomolecules such as Ascorbic acid (AA), Dopamine (DA), Uric acid (UA), Tryptophan (Trp), Xanthine (XA), and Caffeine (CA) are all critical for biological homeostatic maintenance. The depletion or over consumption in any of the biomolecules can lead to detrimental effects. For example, previous reports have suggested the depletion of dopamine in the brain is highly correlated to the progression of Parkinson’s disease 1. Caffeine, though not a bio-molecules, it is frequently consumed, and overdose can lead to neurological damage, or even death 2,3. In extension, these bio-molecules tend to exists as a mixture. Thus, it becomes important to develop a platform that enables the monitoring of these biomolecule concentrations simultaneously. In recent years, carbon nanotubes have collected a great amount of attention from the electrochemical sensor development communities 4. Due to their high surface to volume ratio, carbon nanotubes are able to enhance the electrical catalytic activity increasing the overall conductance 5. This characteristic is highly essential as not only it can increase the potential application range, it can also resolve and separate for biomolecules that have overlapping redox-potentials. In addition, nanotubes are highly biocompatible and do not pose a toxic effect on the biological system. In this work, a novel immobilized ferric cyanide-chitosan polymer ion pair on the multi-walled carbon nanotube-based nanocomposite was synthesized and utilized for the construction of a sensor platform capable of simultaneously detecting six redox-active biomolecules. Using Fourier-transform infrared spectroscopy, and scanning electron microscopy, the nanocomposite was shown to be successfully synthesized. Cyclic voltammetry, and electrochemical impedance spectroscopy both demonstrated the final modified electrode has improved electrochemical activity. Using differential pulse voltammetry, AA, DA, UA, Trp, XA, and CA were all detected simultaneously (Shown in Figure 1). Finally, the sensor performance was analyzed in real samples and demonstrated a comparable performance. These results demonstrated the reported sensor has a strong potential to become the next generation of biosensors. Reference 1. A. Nobili et al., Nat. Commun., 8, 14727 (2017). 2. J. W. Daly, Cell. Mol. Life Sci., 64, 2153–2169 (2007). 3. B. J. Gurley, S. C. Steelman, and S. L. Thomas, Clin. Ther., 37, 275–301 (2015). 4. J. Wang, Electroanalysis, 17, 7–14 (2005). 5. A. Eatemadi et al., Nanoscale Res. Lett., 9, 1–13 (2014). Figure 1
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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 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".