Sensitive determination of d‐lactic acid and l‐lactic acid in urine by high‐performance liquid chromatography–tandem mass spectrometry

乳酸 色谱法 化学 液相色谱-质谱法 检出限 串联质谱法 质谱法 尿 选择性反应监测 高效液相色谱法 细菌 生物化学 遗传学 生物
作者
Hugues Henry,Nelly Conus,Philippe Steenhout,Alexandre Béguin,Olivier Boulat
出处
期刊:Biomedical Chromatography [Wiley]
卷期号:26 (4): 425-428 被引量:41
标识
DOI:10.1002/bmc.1681
摘要

ABSTRACT d ‐Lactic acid in urine originates mainly from bacterial production in the intestinal tract. Increased d ‐lactate excretion as observed in patients affected by short bowel syndrome or necrotizing enterocolitis reflects d ‐lactic overproduction. Therefore, there is a need for a reliable and sensitive method able to detect d ‐lactic acid even at subclinical elevation levels. A new and highly sensitive method for the simultaneous determination of l ‐ and d ‐lactic acid by a two‐step procedure has been developed. This method is based on the concentration of lactic acid enantiomers from urine by supported liquid extraction followed by high‐performance liquid chromatography–tandem mass spectrometry. The separation was achieved by the use of an Astec Chirobiotic™ R chiral column under isocratic conditions. The calibration curves were linear over the ranges of 2–400 and 0.5–100 µmol/L respectively for l ‐ and d ‐lactic acid. The limit of detection of d ‐lactic acid was 0.125 µmol/L and its limit of quantification was 0.5 µmol/L. The overall accuracy and precision were well within 10% of the nominal values. The developed method is suitable for production of reference values in children and could be applied for accurate routine analysis. Copyright © 2011 John Wiley & Sons, Ltd.
最长约 10秒,即可获得该文献文件

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
刚刚
1秒前
1秒前
孔雨珍完成签到,获得积分10
2秒前
娇气的春天完成签到 ,获得积分10
2秒前
3秒前
3秒前
3秒前
大模型应助奔奔采纳,获得10
4秒前
5秒前
5秒前
Owen应助西哈哈采纳,获得10
5秒前
Jessie完成签到 ,获得积分10
5秒前
烟花应助孔雨珍采纳,获得10
6秒前
王小志发布了新的文献求助10
6秒前
科研通AI5应助SCI采纳,获得10
6秒前
net完成签到 ,获得积分10
6秒前
Sally完成签到,获得积分10
7秒前
飘逸蘑菇完成签到 ,获得积分10
7秒前
8秒前
小二郎应助tao采纳,获得10
8秒前
陈丫发布了新的文献求助10
8秒前
8秒前
8秒前
小二郎应助凉风有信9527采纳,获得10
9秒前
LEMON发布了新的文献求助20
10秒前
炜大的我完成签到,获得积分10
10秒前
haimianbaobao发布了新的文献求助10
10秒前
传奇3应助研友_nPoXoL采纳,获得10
10秒前
lpp完成签到,获得积分10
10秒前
10秒前
ww发布了新的文献求助10
10秒前
22发布了新的文献求助10
11秒前
zhui发布了新的文献求助10
11秒前
12秒前
Jenny应助哈哈哈哈采纳,获得10
13秒前
笨笨芯应助Miracle采纳,获得10
13秒前
研友_LJGpan完成签到,获得积分10
13秒前
xiaozhenA完成签到,获得积分10
13秒前
junzilan发布了新的文献求助10
13秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527849
求助须知:如何正确求助?哪些是违规求助? 3107938
关于积分的说明 9287239
捐赠科研通 2805706
什么是DOI,文献DOI怎么找? 1540033
邀请新用户注册赠送积分活动 716893
科研通“疑难数据库(出版商)”最低求助积分说明 709794