A Molecularly Imprinted Sol-Gel Electrochemical Sensor for Naloxone Determination
Bibliographic record
Abstract
A molecularly imprinted sol-gel is reported for selective and sensitive electrochemical determination of the drug naloxone (NLX). The sensor was developed by combining molecular imprinting and sol-gel techniques and electrochemically grafting the sol solution onto a functionalized multiwall carbon nanotube modified indium-tin oxide (ITO) electrode. The sol-gel layer was obtained from acid catalyzed hydrolysis and condensation of a solution composed of triethoxyphenylsilane (TEPS) and tetraethoxysilane (TES). The fabrication, structure and properties of the sensing material were characterized via scanning electron microscopy, spectroscopy and electrochemical techniques. Parameters affecting the sensor's performance were evaluated and optimized. A sensor fabricated under the optimized conditions responded linearly between 0.0 µM and 12 µM NLX, with a detection limit of 0.02 µM. The sensor also showed good run-to-run repeatability and batch-to-batch performance reproducibility with relative standard deviations (RSD) of 2.5-7.8% (n = 3) and 9.2% (n = 4), respectively. The developed sensor displayed excellent selectivity towards NLX compared to structurally similar compounds (codeine, fentanyl, naltrexone and noroxymorphone), and was successfully used to measure NLX in synthetic urine samples yielding recoveries greater than 88%.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 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".