ArticleBMC chemistry2022
Response surface optimization of a vortex-assisted dispersive liquid-liquid microextraction method for highly sensitive determination of repaglinide in environmental water by HPLC/UV.
Article in BMC chemistry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 13 citations in OpenAlex.
- Optimization of variables for cadmium and copper removal using magnetic nanocomposite.BMC chemistry · 2025Article
- Application of Fabric Phase Sorptive Extraction as a Green Method for the Analysis of 10 Anti-Diabetic Drugs in Environmental Water Samples.Molecules (Basel, Switzerland) · 2024Article
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4 authors at 2 institutions in 1 country.
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Abstract
A vortex-assisted dispersive liquid-liquid microextraction (DLLME) method, mated to chemometrics and combined with HPLC/UV detection was optimized and validated for enrichment and determination of repaglinide in environmental samples using nateglinide as an internal standard (IS). A phosphate buffer (10 mM, pH 2.5): acetonitrile (45:55, v/v) was used as a mobile phase with a flow rate of 1 mL/min in an isocratic elution mode. Chemometrics-assisted optimization was performed using a quadratic integrated D-optimal design. The developed model assessed the statistical significance of the independent variables and their interactions to attain the optimum conditions revealing that extractant type, extractant volume and pH are the most influential factors. Optimization of the extraction procedures was performed with the aid of Design Expert 8® software, which suggested 58 different experiments. The optimal conditions were 30 µL of 1-octanol as extractant, 100 µL of acetonitrile as a disperser at pH 8. Under the optimized conditions, the method showed linearity over the range of 1-100 ng/mL with a limit of detection of 0.4 ng/mL. The accuracy, the intra- and inter-day precision were assessed, the %recoveries were found to be between 98.48 and 100.81% with %RSD lower than 1.3. Using chemometrics in method optimization helped achieve the maximum possible enrichment with the least effort, time, and reagents while considering all possible interactions between variables.
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