Nanoconfinement effect based in-fiber extraction and derivatization method for ultrafast analysis of twenty amines in human urine by GC-MS: Application to cancer diagnosis biomarkers? screening

被引:0
|
作者
Zheng, Jinshi [1 ]
Jiang, Xinran [1 ]
Zhang, Qian [1 ]
Zhang, Yiwen [1 ]
Bi, Kaishun [1 ]
Li, Donghao [2 ]
Li, Qing [1 ]
机构
[1] Shenyang Pharmaceut Univ, Sch Pharm, 103 Wenhua Rd, Shenyang 110016, Peoples R China
[2] Yanbian Univ, Dept Chem, Pk Rd 977, Yanji 133002, Jilin, Peoples R China
基金
中国国家自然科学基金;
关键词
In-fiber extraction and derivatization; Nanoconfinement effect; Amines; Cancer biomarkers; SOLID-PHASE MICROEXTRACTION; CHROMATOGRAPHY-MASS SPECTROMETRY; GAS-CHROMATOGRAPHY; DIRECT IMMERSION; METABOLITES; METABOLOMICS; POLYAMINES; SAMPLES; TISSUE; WATER;
D O I
10.1016/j.aca.2022.339985
中图分类号
O65 [分析化学];
学科分类号
070302 ; 081704 ;
摘要
Amines, including amino acids and biogenic amines are widely recognized as cancer biomarkers for early diagnosis and treatment. But rapid analysis of amines in biological samples with high sensitivity, good durability and low cost is still challenging. Herein, we proposed an ultrafast biological sample preparation method based on in-fiber extraction and derivatization using a homemade needle-tip devise. Under the nanoconfinement effect, the extraction was completed within 2 min in nanofibers, followed by the in-suit derivatization within 3 min under room temperature using pentafluoropropionic anhydride (PFA) as derivatization reagent, then the needle was inserted into the inlet of GC-MS directly for thermal desorption to enable the complete injection. Additionally, the established sample preparation strategy consumed only 20 mu L organic solvent and urine sample, and the sensitivity was increased compared with other methods. After systematical optimization and validation, coupled to GC-MS, the established method was successfully applied to quantify twenty amines in urine of healthy people and lung, colorectal and breast cancer patients. The diagnosis biomarkers for each cancer were screened out and accessed by multiple statistical approaches. Then we further constructed the cancer diagnosis model of each cancer through binary logistic regression analysis for clinical use. Taken together, the established nanoconfinement effect based in-fiber extraction and derivatization biological sample preparation strategy in
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页数:9
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