上海交通大学学报（医学版）

上海交通大学学报（医学版） >

2016 , Vol. 36 >Issue 1: 143

DOI: https://doi.org/10.3969/j.issn.1674-8115.2016.01.029

技术与方法

游离脂肪酸结构信息和保留时间相关性及预测模型的建立

  • 王守丽 ,
  • 卫润民 ,
  • 黄凤杰 ,
  • 等
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  • 上海交通大学 1.附属第六人民医院转化医学中心， 上海 200233； 2.药学院， 上海 200240
王守丽（1991—）， 女， 硕士生; 电子信箱: balihewangshouli@163.com。

网络出版日期: 2016-02-26

基金资助

国家自然科学基金（31501079）；上海市科委青年科技英才扬帆计划（15YF1409100）

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Correlation between structure of free fatty acid and its retention time and establishment of prediction model

  • WANG Shou-li ,
  • WEI Run-min ,
  • HUANG Feng-jie ,
  • et al
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  • 1.Center for Translational Medicine, Shanghai Sixth Peoples Hospital, Shanghai Jiao Tong University, Shanghai 200233, China; 2.School of Pharmacy, Shanghai Jiao Tong University, Shanghai 200240, China

Online published: 2016-02-26

Supported by

National Natural Science Foundation of China, 31501079; Sail Plan of Shanghai Youth Science and Technology Talents of Science and Technology Commission of Shanghai Municipality, 15YF1409100。

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摘要

目的 分析游离脂肪酸(FFA)的结构与测得的保留时间(RT)之间的关系，构建和验证RT预测模型。方法 利用UPLC-QTOF/MS平台检测72个FFA标准品的RT和结构信息。考察FFA的碳链长度、双键个数以及双键位置与RT的关系，建立多组广义回归模型，采用交叉验证和赤池信息量选择最佳模型。结果 各种结构信息与RT之间是非线性关系；建立了最佳预测模型并评估了其性能。结论 多元正交多项式回归模型能够较好地预测72种FFA标准品的RT;采用该回归模型对其他目标物质的RT进行预测，有助于对缺乏标准品的FFA进行鉴定。

关键词： 游离脂肪酸; 保留时间; 结构信息; 回归模型

本文引用格式

王守丽 , 卫润民 , 黄凤杰 , 等 . 游离脂肪酸结构信息和保留时间相关性及预测模型的建立[J]. 上海交通大学学报（医学版）, 2016 , 36(1) : 143 . DOI: 10.3969/j.issn.1674-8115.2016.01.029

Abstract

Objective To analyze the correlation between the structure of free fatty acid (FFA) and its retention time (RT) and establish and verify a RT prediction model. Methods The RT and structural information of 72 standard samples of FFAs were detected by UPLC-QTOF/MS platform. The correlation between RT and the length, number of double bonds, and locations of double bonds of the carbon chain of FFAs was investigated. The multiple generalized regression models were established and the optimal model was selected by cross-validation and Akaike information criterion. Results The structural information was nonlinear with RT. The optimal prediction model was established and the performance was evaluated. Conclusion The multi-element orthogonal polynomical regression model can well predict the RT of 72 standard samples of FFAs and can be used to predict the RT of other target substances. It is helpful for identifying FFAs without standard samples.

Key words： free fatty acid; retention time; structural information; regression model

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