Simultaneous determination of nifedipine and atenolol in combined dosage forms using a boron-doped diamond electrode with differential pulse voltammetry
Bibliographic record
Abstract
Combinations of nifedipine (NIF) and atenolol (ATN) are used for the treatment of arterial hypertension. Dosages values different from those presented on the label of pharmaceuticals can significantly impact a consumer’s health. To control the quality of the pharmaceuticals effectively, a method for the simultaneous determination of these both drugs using an anodically pretreated boron-doped diamond electrode coupled to differential pulse voltammetry technique was developed. The influence of supporting electrolyte, pH and scan rate on the current response of these both antihypertensives was examined to select the optimum experimental conditions. It was found that NIF and ATN provided two well-shaped and reproducible oxidation peaks at 0.97 V and 1.36 V (vs. Ag/AgCl electrode), respectively, in TRIS buffer solution (pH 8.0). At optimized differential pulse voltammetric parameters, the current response of NIF and ATN was proportionally linear in the concentration range of 3.98–107 μmol L–1 and 1.99–47.2 μmol L–1, with detection limit of 0.612 and 0.999 μmol L−1, respectively. The proposed method was successfully applied in analysis of several commercial combined dosage forms, whose accuracy was attested by good agreement of the results (paired t test at a 95% confidence level) with those obtained using high performance liquid chromatography.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".