Hydrophilic interaction chromatography combined with ultrasound-assisted ionic liquid dispersive liquid-liquid microextraction for determination of underivatized neurotransmitters in dementia patients' urine samples
| Autor: | Yuping Tang, Pei-Dong Chen, Lian Yin, Jin-Ao Duan, Gui-Sheng Zhou, Yi-Chu Yuan, Ren-Jie Xu, Yan Liu, You Yin |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Male
Central composite design Liquid Phase Microextraction Ionic Liquids Urine Tandem mass spectrometry Biochemistry Analytical Chemistry chemistry.chemical_compound Limit of Detection Tandem Mass Spectrometry medicine Environmental Chemistry Dementia Liquid liquid Humans Sample preparation Spectroscopy Chromatography High Pressure Liquid Aged Aged 80 and over Neurotransmitter Agents Chromatography Hydrophilic interaction chromatography Middle Aged medicine.disease chemistry Ultrasonic Waves Ionic liquid Multivariate Analysis Female Biomarkers |
| Zdroj: | Analytica chimica acta. 1107 |
| ISSN: | 1873-4324 |
| Popis: | A sensitive, rapid, precise and specific analytical method of hydrophilic interaction ultra-performance liquid chromatography coupled with triple-quadrupole linear ion-trap tandem mass spectrometry (HILIC-UHPLC–QTRAP®/MS2) combined with a high-efficiency and easy sample preparation technology of ultrasound-assisted ionic liquid dispersive liquid–liquid microextraction (UA-IL-DLLME) was developed to investigate neurotransmitters (NTs) in mild cognitive impairment, mild dementia and moderate dementia patients’ urine samples. Firstly, the UA-IL-DLLME parameters were optimized using Plackett–Burman screening and rotatable central composite design, and the main optimal conditions were obtained: ultrasound power of 307 W, ultrasound time of 4.3 min and agitation time of 4.8 min. Secondly, HILIC-UHPLC–QTRAP®/MS2 method was developed to simultaneously determine 15 underivatized NTs in urine samples. The analysis results of clinical samples showed that some NTs such as γ-aminobutyric acid (GABA), acetylcholine (Ach) and glutamic acid (Glu) presented significant differences in different dementia stages. Finally, multivariate analysis based on the combination of principal component analysis and supervised counter propagation artificial neural network was developed for comprehensive analysis of the obtained clinical data sets. As a result, GABA and Glu were simultaneously presented meaningful contribution for classification of samples, and might be considered as potential differential compounds to the urine samples from cluster patients with different dementia stages. In summary, the presented strategy of preparation, analysis and statistics might be used to investigate NTs in different clinical biological fluids. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect