Suppr超能文献

利用多模式传感对神经递质进行模式识别。

Pattern recognition of neurotransmitters using multimode sensing.

作者信息

Stefan-van Staden Raluca-Ioana, Moldoveanu Iuliana, van Staden Jacobus Frederick

机构信息

Laboratory of Electrochemistry and PATLAB Bucharest, National Institute of Research for Electrochemistry and Condensed Matter, Splaiul Independentei No. 202, Bucharest, Romania; Faculty of Applied Chemistry and Material Science, Politehnica University of Bucharest, Bucharest, Romania.

Laboratory of Electrochemistry and PATLAB Bucharest, National Institute of Research for Electrochemistry and Condensed Matter, Splaiul Independentei No. 202, Bucharest, Romania; Faculty of Applied Chemistry and Material Science, Politehnica University of Bucharest, Bucharest, Romania.

出版信息

J Neurosci Methods. 2014 May 30;229:1-7. doi: 10.1016/j.jneumeth.2014.03.008. Epub 2014 Mar 25.

Abstract

BACKGROUND

Pattern recognition is essential in chemical analysis of biological fluids. Reliable and sensitive methods for neurotransmitters analysis are needed.

NEW METHOD

Therefore, we developed for pattern recognition of neurotransmitters: dopamine, epinephrine, norepinephrine a method based on multimode sensing. Multimode sensing was performed using microsensors based on diamond paste modified with 5,10,15,20-tetraphenyl-21H,23H-porphyrine, hemin and protoporphyrin IX in stochastic and differential pulse voltammetry modes.

RESULTS

Optimized working conditions: phosphate buffer solution of pH 3.01 and KCl 0.1mol/L (as electrolyte support), were determined using cyclic voltammetry and used in all measurements. The lowest limits of quantification were: 10(-10)mol/L for dopamine and epinephrine, and 10(-11)mol/L for norepinephrine. The multimode microsensors were selective over ascorbic and uric acids and the method facilitated reliable assay of neurotransmitters in urine samples, and therefore, the pattern recognition showed high reliability (RSD<1% for more than 6 months) for the simultaneous determination of dopamine, epinephrine and norepinephrine from urine and whole blood samples.

COMPARISON WITH EXISTING METHOD(S): The proposed method can perform pattern recognition of the three neurotransmitters on biological fluids at a lower determination level than chromatographic methods. The sampling of the biological fluids referees only to the buffering (1:1, v/v) with a phosphate buffer pH 3.01, while for chromatographic methods the sampling is laborious.

CONCLUSIONS

Accordingly with the statistic evaluation of the results at 99.00% confidence level, both modes can be used for pattern recognition and quantification of neurotransmitters with high reliability. The best multimode microsensor was the one based on diamond paste modified with protoporphyrin IX.

摘要

背景

模式识别在生物体液的化学分析中至关重要。需要可靠且灵敏的神经递质分析方法。

新方法

因此,我们开发了一种基于多模式传感的神经递质模式识别方法,用于多巴胺、肾上腺素、去甲肾上腺素的分析。多模式传感是使用基于用5,10,15,20 - 四苯基 - 21H,23H - 卟啉、血红素和原卟啉IX修饰的金刚石糊的微传感器,在随机伏安法和差分脉冲伏安法模式下进行的。

结果

使用循环伏安法确定了优化的工作条件:pH 3.01的磷酸盐缓冲溶液和0.1mol/L的KCl(作为电解质支持物),并用于所有测量。最低定量限为:多巴胺和肾上腺素为10(-10)mol/L,去甲肾上腺素为10(-11)mol/L。多模式微传感器对抗坏血酸和尿酸具有选择性,该方法有助于可靠地测定尿液样本中的神经递质,因此,模式识别对于从尿液和全血样本中同时测定多巴胺、肾上腺素和去甲肾上腺素显示出高可靠性(超过6个月的相对标准偏差<1%)。

与现有方法的比较

所提出的方法能够在比色谱方法更低的测定水平上对生物体液中的三种神经递质进行模式识别。生物体液的采样仅涉及用pH 3.01的磷酸盐缓冲液进行缓冲(1:1,v/v),而对于色谱方法,采样则很繁琐。

结论

根据在99.00%置信水平下对结果的统计评估,两种模式均可用于神经递质的模式识别和定量,且可靠性高。最佳的多模式微传感器是基于用原卟啉IX修饰的金刚石糊的微传感器。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验