Surfactant assisted magnetic dispersive micro solid phase extraction-HPLC as a straightforward and green procedure for preconcentrating and determining Caffeine, Lidocaine, and Chlorpromazine in biological and water samples

Author(s):  
Mohsen Varak Neshin ◽  
Razieh Sanavi Khoshnood ◽  
Davoud Sanavi Khoshnoud
Author(s):  
Kamran Bashir ◽  
Zhimin Luo ◽  
Guoning Chen ◽  
Hua Shu ◽  
Xia Cui ◽  
...  

Griseofulvin (GSF) is clinically employed to treat fungal infections in humans and animals. GSF was detected in surface waters as a pharmaceutical pollutant. GSF detection as an anthropogenic pollutant is considered as a possible source of drug resistance and risk factor in ecosystem. To address this concern, a new extraction and enrichment method was developed. GSF-surface molecularly imprinted polymers (GSF-SMIPs) were prepared and applied as solid phase extraction (SPE) sorbent. A dispersive solid phase extraction (DSPE) method was designed and combined with HPLC for the analysis of GSF in surface water samples. The performance of GSF-SMIPs was assessed for its potential to remove GSF from water samples. The factors affecting the removal efficiency such as sample pH and ionic strength were investigated and optimized. The DSPE conditions such as the amount of GSF-SMIPs, the extraction time, the type and volume of desorption solvents were also optimized. The established method is linear over the range of 0.1–100 µg/mL. The limits of detection and quantification were 0.01 and 0.03 µg/mL respectively. Good recoveries (91.6–98.8%) were achieved after DSPE. The intra-day and inter-day relative standard deviations were 0.8 and 4.3% respectively. The SMIPs demonstrated good removal efficiency (91.6%) as compared to powder activated carbon (67.7%). Moreover, the SMIPs can be reused 10 times for water samples. This is an additional advantage over single-use activated carbon and other commercial sorbents. This study provides a specific and sensitive method for the selective extraction and detection of GSF in surface water samples.


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