Fluorous-paired derivatization approach towards highly sensitive and accurate determination of long chain unsaturated fatty acids by liquid chromatography-tandem mass spectrometry

化学 衍生化 色谱法 质谱法 液相色谱-质谱法 串联质谱法 分辨率(逻辑) 基质(化学分析) 试剂 高效液相色谱法 样品制备 有机化学 计算机科学 人工智能
作者
Jia‐Yi Zheng,Yingying Jin,Zi‐Qi Shi,Jian‐Liang Zhou,Lifang Liu,Gui‐Zhong Xin
出处
期刊:Analytica Chimica Acta [Elsevier BV]
卷期号:1136: 187-195 被引量:12
标识
DOI:10.1016/j.aca.2020.09.052
摘要

Long chain unsaturated fatty acids (LCUFAs) are emerging as critical contributors to inflammation and its resolution. Sensitive and accurate measurement of LCUFAs in biological samples is thus of great value in disease diagnosis and prognosis. In this work, a fluorous-derivatization approach for UPLC-MS/MS quantification of LCUFAs was developed by employing a pair of fluorous reagents, namely 3-(perfluorooctyl)-propylamine (PFPA) and 2-(perfluorooctyl)-ethylamine (PFEA). With this method, the LCUFAs in biological samples were perfluoroalkylated with PFPA and specifically retained on a fluorous-phase LC column, which largely reduced matrix interferences-induced quantitation deviation. Moreover, PFEA-labeled LCUFAs standards were introduced as one-to-one internal standards to farthest ensure unbiased results. Application of the proposed method enabled a reliable determination of eight typical LCUFAs with high sensitivity (LLOQ ranged from 30 amol to 6.25 fmol) and low matrix interferences (almost less than 10%). Such a high sensitivity could facilitate the determination of small-volume and low-concentration bio-samples. Further metabolic characterization of these targeted LCUFAs was monitored in OVA-induce asthma mice, requiring only 5 μL serum sample. Our results showed that asthmatic attack led to significant disturbances not only in the concentrations but also in the ratio among these LCUFAs. In view of the favorable advantages in sensitivity and accuracy, the present fluorous-paired derivatization approach will be expected to serve as a new avenue for dissecting the physiological and clinical implications of LCUFAs, thereby shedding light on the management of diseases related to their disturbances.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
2秒前
7秒前
9秒前
12秒前
今天晚上早点睡完成签到 ,获得积分10
12秒前
Poman完成签到,获得积分10
16秒前
Xiaoyisheng完成签到,获得积分10
16秒前
zhusy347发布了新的文献求助10
18秒前
apocalypse完成签到 ,获得积分10
19秒前
研友_LMgQXZ完成签到,获得积分10
21秒前
cuddly完成签到 ,获得积分10
21秒前
徐涛完成签到 ,获得积分10
25秒前
研友_89eKw8完成签到,获得积分10
26秒前
CodeCraft应助追寻邑采纳,获得10
26秒前
朴素冰双发布了新的文献求助10
28秒前
Sxq完成签到,获得积分10
29秒前
zhusy347完成签到,获得积分10
29秒前
上官若男应助司空天德采纳,获得10
32秒前
Hao完成签到,获得积分10
32秒前
2012csc完成签到 ,获得积分0
33秒前
34秒前
斯文败类应助科研通管家采纳,获得10
34秒前
SciGPT应助科研通管家采纳,获得10
34秒前
34秒前
34秒前
34秒前
34秒前
czz014完成签到,获得积分10
38秒前
听风轻语完成签到,获得积分10
40秒前
无法无天完成签到 ,获得积分10
40秒前
香菜完成签到 ,获得积分10
42秒前
左传琦完成签到 ,获得积分10
44秒前
44秒前
红毛兔完成签到,获得积分10
45秒前
朴素冰双完成签到 ,获得积分10
47秒前
衣兮发布了新的文献求助10
48秒前
49秒前
枫溪完成签到,获得积分10
49秒前
衣兮完成签到,获得积分10
53秒前
byron完成签到 ,获得积分10
54秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Various Faces of Animal Metaphor in English and Polish 800
Signals, Systems, and Signal Processing 610
Photodetectors: From Ultraviolet to Infrared 500
On the Dragon Seas, a sailor's adventures in the far east 500
Yangtze Reminiscences. Some Notes And Recollections Of Service With The China Navigation Company Ltd., 1925-1939 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6353208
求助须知:如何正确求助?哪些是违规求助? 8168160
关于积分的说明 17191745
捐赠科研通 5409275
什么是DOI,文献DOI怎么找? 2863689
邀请新用户注册赠送积分活动 1840984
关于科研通互助平台的介绍 1689834