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Investigation of faecal volatile organic metabolites as novel diagnostic biomarkers in inflammatory bowel disease.粪便挥发性有机代谢产物作为炎症性肠病新型诊断生物标志物的研究。
Aliment Pharmacol Ther. 2016 Mar;43(5):596-611. doi: 10.1111/apt.13522. Epub 2016 Jan 25.
2
Electronic nose can discriminate colorectal carcinoma and advanced adenomas by fecal volatile biomarker analysis: proof of principle study.电子鼻通过粪便挥发性生物标志物分析可区分结直肠癌和高级腺瘤：原理研究证明。
Int J Cancer. 2014 Mar 1;134(5):1132-8. doi: 10.1002/ijc.28446. Epub 2013 Sep 2.
3
Analysis of volatile organic compounds of bacterial origin in chronic gastrointestinal diseases.分析慢性胃肠疾病中细菌来源的挥发性有机化合物。
Inflamm Bowel Dis. 2013 Sep;19(10):2069-78. doi: 10.1097/MIB.0b013e31829a91f6.
4
A pilot study combining a GC-sensor device with a statistical model for the identification of bladder cancer from urine headspace.一种将 GC 传感器设备与统计模型相结合的初步研究，用于从尿液头空间中识别膀胱癌。
PLoS One. 2013 Jul 8;8(7):e69602. doi: 10.1371/journal.pone.0069602. Print 2013.
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使用气相色谱仪与金属氧化物传感器联用，对肠易激综合征和炎症性肠病患者的粪便样本进行快速评估。

The use of a gas chromatograph coupled to a metal oxide sensor for rapid assessment of stool samples from irritable bowel syndrome and inflammatory bowel disease patients.

作者信息

Shepherd S F, McGuire N D, de Lacy Costello B P J, Ewen R J, Jayasena D H, Vaughan K, Ahmed I, Probert C S, Ratcliffe N M

机构信息

Institute of Bio-sensing Technology, University of the West of England, Bristol BS16 1QY, UK.

出版信息

J Breath Res. 2014 Jun;8(2):026001. doi: 10.1088/1752-7155/8/2/026001. Epub 2014 Mar 27.

DOI:10.1088/1752-7155/8/2/026001
PMID:24674940
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4871257/
Abstract

There is much clinical interest in the development of a low-cost and reliable test for diagnosing inflammatory bowel disease (IBD) and irritable bowel syndrome (IBS), two very distinct diseases that can present with similar symptoms. The assessment of stool samples for the diagnosis of gastro-intestinal diseases is in principle an ideal non-invasive testing method. This paper presents an approach to stool analysis using headspace gas chromatography and a single metal oxide sensor coupled to artificial neural network software. Currently, the system is able to distinguish samples from patients with IBS from patients with IBD with a sensitivity and specificity of 76% and 88% respectively, with an overall mean predictive accuracy of 76%.

摘要

开发一种低成本且可靠的测试方法来诊断炎症性肠病（IBD）和肠易激综合征（IBS）引起了临床的广泛关注，这两种截然不同的疾病却可能表现出相似的症状。通过评估粪便样本诊断胃肠疾病原则上是一种理想的非侵入性检测方法。本文介绍了一种利用顶空气相色谱法和与人工神经网络软件相结合的单一金属氧化物传感器进行粪便分析的方法。目前，该系统能够区分IBS患者和IBD患者的样本，灵敏度和特异性分别为76%和88%，总体平均预测准确率为76%。