Microneedle-Integrated Screen-Printed Electrode Modified with Gold Nanoparticle-Boron-Doped Diamond Nanoparticle Nanocomposites for Electrochemical Theophylline Detection
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Theophylline is a drug with a narrow therapeutic index, with normal plasma levels ranging from 10 to 20 mg/L. Theophylline overdose can lead to several symptoms, including nausea, vomiting, headaches, pancreatitis, and death. Thus, it is important to monitor theophylline after its consumption. Microneedles (MNs) can be integrated with screen-printed electrodes (SPE) to enable the minimally invasive monitoring of theophylline. In this study, we developed a highly sensitive and accurate electrochemical sensor to detect theophylline based on a gold nanoparticle/boron-doped diamond nanoparticle nanocomposite-modified SPE (AuNP-BDDNP/SPE). In addition, this study aims to determine the feasibility of MN integration with AuNP-BDDNP/SPE for theophylline detection. UV–vis, TEM, and XPS confirmed the successful synthesis of AuNP-BDDNP, whereas FESEM images confirmed the successful modification of SPE. Theophylline detection was performed using differential pulse voltammetry (DPV) with concentrations ranging from 20 to 140 μM, producing an R 2 value of 0.999, an LOD of 0.14 μM, and an LOQ of 0.48 μM. AuNP-BDDNP/SPE was also selective in the presence of interferents. AuNP-BDDNP/SPE can accurately detect theophylline in urine, coffee, and capsule samples. Moreover, AuNP-BDDNP/SPE was successfully integrated with MNs, maintaining the accuracy for detecting theophylline in urine, coffee, and capsule samples. AuNP-BDDNP/SPE demonstrated excellent performance in theophylline detection and can potentially be successfully integrated with MNs.
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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) | 0.000 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".