High-throughput powder X-ray diffraction, IR-spectroscopy and ion chromatography analysis of urinary stones: A comparative study

被引:8
|
作者
Yusenko, Elena V. [1 ]
Yusenko, Kirill V. [2 ]
Korolkov, Ilya V. [3 ]
Shubin, Alexandr A. [4 ]
Kapsargin, Fedor P. [5 ]
Efremov, Alexandr A. [1 ]
Yusenko, Maria V. [6 ]
机构
[1] Siberian Fed Univ, Dept Analyt & Organ Chem, Krasnoyarsk 660041, Russia
[2] Univ Oslo, Dept Chem, Ctr Mat Sci & Nanotechnol, N-0315 Oslo, Norway
[3] Nikolaev Inst Inorgan Chem, Dept Crystal Chem, Novosibirsk 630090, Russia
[4] Siberian Fed Univ, Dept Phys & Inorgan Chem, Krasnoyarsk 660041, Russia
[5] Vojno Yasenetsky Krasnoyarsk Med State Univ, Dept Urol Androl & Sexol, Krasnoyarsk 660022, Russia
[6] Univ Munster, Fac Med, Inst Mol Tumor Biol IMTB, D-48149 Munster, Germany
来源
CENTRAL EUROPEAN JOURNAL OF CHEMISTRY | 2013年 / 11卷 / 12期
关键词
Urinary stones composition; Ion chromatography; Powder X-ray diffraction; IR-spectroscopy; Hierarchical clustering; RENAL CALCULI; KIDNEY-STONES; CLASSIFICATION; UROLITHIASIS; ELEMENTS; ACID; OIL;
D O I
10.2478/s11532-013-0335-z
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
The instrumental qualitative analysis of urinary stones is a critical step in clinical practice and urological research. A powder X-ray diffraction, IR-spectroscopy and ion chromatography have been applied for the qualitative analysis of 20 urinary stones. Suggestions for a sample preparation and an optimal measurement strategy were formulated. The main difficulties for the powder X-ray diffraction qualitative analysis are a limiting amount of the sample and a preferential orientation of crystals, both issues should be minimized by the special sample preparation. Urinary stones samples have been clustered into four groups using different sets of numerical input data (cation and anion content, phase composition). At the same time a high-throughput multivariate clustering has been applied for powder X-ray diffraction and IR-spectroscopy data. The multivariate whole-profile approach can be used as a tool for a high-throughput time reducing technique for clinical practice, when a quick and stable classification of samples is required. All three sets of the data can be automatically separated into three clusters: oxalate-reach, oxalate-pure and non-oxalate samples. Uricite-pure and uricite-rich samples can be easily clustered.
引用
收藏
页码:2107 / 2119
页数:13
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