Development of a cloud point extraction and spectrophotometry-based microplate method for the determination of nitrite in human urine and blood
| Autor: | Chongyang Fan, Jun Wang, Yunhui Lu, Yaling Yang, Jiao Zhao |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Trace Amounts
Octoxynol Calibration curve Chemical Fractionation Polyethylene Glycols Analytical Chemistry Matrix (chemical analysis) Surface-Active Agents chemistry.chemical_compound Limit of Detection Griess test Spectrophotometry medicine Humans Nitrite Instrumentation Nitrites Spectroscopy Detection limit Chromatography medicine.diagnostic_test Chemistry Extraction (chemistry) Equipment Design Atomic and Molecular Physics and Optics |
| Zdroj: | Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy. 136:802-807 |
| ISSN: | 1386-1425 |
| Popis: | A novel and simple method for the sensitive determination of trace amounts of nitrite in human urine and blood has been developed by combination of cloud point extraction (CPE) and microplate assay. The method is based on the Griess reaction and the reaction product is extracted into nonionic surfactant Triton-X114 using CPE technique. In this study, decolorization treatment of urine and blood was applied to overcome the interference of matrix and enhance the sensitivity of nitrite detection. Multi-sample can be simultaneously detected thanks to a 96-well microplate technique. The effects of different operating parameters such as type of decolorizing agent, concentration of surfactant (Triton X-114), addition of (NH 4 ) 2 SO 4, extraction temperature and time, interfering elements were studied and optimum conditions were obtained. Under the optimum conditions, a linear calibration graph was obtained in the range of 10–400 ng mL −1 of nitrite with limit of detection (LOD) of 2.5 ng mL −1 . The relative standard deviation (RSD) for determination of 100 ng mL −1 of nitrite was 2.80%. The proposed method was successfully applied for the determination of nitrite in the urine and blood samples with recoveries of 92.6–101.2%. |
| Databáze: | OpenAIRE |
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