Zincon-Modified CNTs Electrochemical Tool for Salivary and Urinary Zinc Detection
Bibliographic record
Abstract
Recently, the abnormal level of zinc emerged as a powerful indicator or risk factor for metabolic, endocrine, neurodegenerative and cardiovascular diseases, including cancer. Electrochemical detection has been explored to quantify zinc in a precise, rapid, and non-expensive way; however, most of the current electrochemical systems lack in specificity. In this work we studied a highly selective and sensitive electrochemical method to detect quickly and reliably free zinc ions (Zn2+). The surface of the working electrode was modified with zincon electropolymerized on carbon nanotube (CNT) to enable the binding of zinc in complex body fluids. After being physicochemically characterized, the performances of the zincon-CNT complex was electrochemically assessed. Square Wave Voltammetry (SWV) was used to determine the calibration curve and the linear range of zinc quantification in artificial saliva and urine. This zincon- CNT system could specifically quantify mobile Zn2+ in salivary and urinary matrices with a sensitivity of ~100 ng·mL−1 and a limit of detection (LOD) of ~20 ng·mL−1. Zincon-modified CNT presented as a desirable candidate for the detection and quantification of free zinc in easily body fluids that potentially can become a diagnostic non-invasive testing platform.
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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) | 0.001 | 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 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".