scholarly journals Automatic biological samples pretreatment for clinical tests using LCMS/MS. Fully automated sample preparation module Shimadzu CLAM-2000

Analytics ◽  
2017 ◽  
pp. 72-75
Author(s):  
D. Farmakovskiy
2004 ◽  
Vol 76 (13) ◽  
pp. 3492-3497 ◽  
Author(s):  
Benjamin J. Hindson ◽  
Steve B. Brown ◽  
Graham D. Marshall ◽  
Mary T. McBride ◽  
Anthony J. Makarewicz ◽  
...  

2021 ◽  
Author(s):  
Seyed Mosayeb Daryanavard ◽  
Hesane Zolfaghari ◽  
Abbi Abdel‐Rehim ◽  
Mohamed Abdel‐Rehim

Author(s):  
Anna Bach ◽  
Heidi Fleischer ◽  
Bhagya Wijayawardena ◽  
Kerstin Thurow

Vitamin D belongs to the fat-soluble vitamins and is an integral part of bone metabolism. In the human body, a decreased vitamin D level can be an additional risk factor for diseases like cancer, diabetes, and mental diseases. As a result, an enormous increase in the demand for vitamin D testing has been observed in recent years, increasing the demand for powerful methods for vitamin D determination at the same time. Automation is the key factor in increasing sample throughput. This study compares three fully automated sample preparation methods for the determination of 25(OH)D2 and 25(OH)D3 in plasma and serum samples. Starting from a semiautomated reference method, the method is tested manually and subsequently fully automated on the Biomek i7 Workstation by integrating a centrifuge and a positive pressure extractor into the workstation. Alternatively, the centrifugation for the separation of protein aggregates and supernatant is replaced by a filter plate. Finally, the sample throughput is further increased by using phospholipid removal cartridges. The results show that phospholipid removal significantly increases the recovery rates in liquid chromatography–mass spectrometry. With the phospholipid removal cartridges, recovery rates of 97.36% for 25(OH)D2 and 102.5% for 25(OH)D3 were achieved, whereas with the automated classic automated preparation method, the recovery rates were 83.31% for 25(OH)D2 and 86.54% for 25(OH)D3. In addition to the technical evaluation, the different methods were also examined with regard to their economic efficiency. Finally, the qualitative and quantitative performance of the developed methods is benchmarked with a selected semiautomatic reference method.


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