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中文摘要
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描述(申请人提供):在涉及天然产品和其他复杂生物样品的生物医学研究中,复杂的天然混合物的分析是一个重大的科学挑战,特别是当需要分离次要成分时。逆流色谱(CCC)具有高负载能力、完全样品回收和高纯度馏分的特点。它利用温和的液体固定相,防止不稳定的样品降解,已经是天然产品研究中的一种有价值的工具。CCC分离消耗的溶剂相对较少,不需要使用昂贵的固体载体,使其在环境和财务上都非常经济。消耗品的节约使用使CCC比其他竞争对手的技术更加“绿色”。确定分配系数(K值)是CCC提供的一种独特的分析能力。然而,使用现代CCC仪器准确测量分析物分配系数需要将样品载量限制在远低于系统容量。在目前的技术条件下,当对测定K值的条件进行优化时,CCC独特的实用优势基本上消失了。此外,目前成功使用CCC需要专门的培训和相当长的操作员时间。自动化,就像它对许多其他技术所做的那样,可以有效地减轻吸收散布在数百篇期刊论文中的数十年关键信息的学术负担,以及操作复杂的多组件系统的实际负担。液体CCC柱的动态性质带来的挑战阻碍了自动化CCC的开发,直到SBC在该SBIR项目的第一阶段取得了突破性的概念证明。该项目的长期目标,也是最终可销售的产品,将是一个全功能的自动CCC控制器,它将为受过最少培训的用户提供CCC的分离能力,并增强现有的功能,并为有经验的用户提供新的功能。自动化CCC将为美国国立卫生研究院(NIH)的目标做出重大贡献,使生物医学研究人员能够分析复杂的生物活性样本并减轻人类疾病。该项目的成功将通过将其应用于提纯和研究常见消费植物产品中存在的生物活性天然产品来证明,其中一种植物产品在抗击结核病方面显示出了希望。 公共卫生相关性:高度复杂的化学混合物的分析是一个重大的科学挑战,特别是在涉及天然产品和其他复杂生物样品的生物医学研究中。逆流色谱(CCC)是由美国国立卫生研究院开发的一项技术,它能够解决这一领域的许多挑战。这项SBIR研究方案提供了实现CCC分析能力的巨大潜力所需的关键技术,使生物医学研究人员能够通过生化发现获得急需的新工具,以对抗疾病。
英文摘要
DESCRIPTION (provided by applicant): The analysis of complex natural mixtures presents a significant scientific challenge in biomedical studies involving natural products and other complex biogenic samples, particularly when the need for isolation of minor constituents arises. Countercurrent chromatography (CCC) offers high loading capacity, complete sample recovery, and high purity fractions. It makes use of a gentle liquid stationary phase that prevents degradation of labile samples, and is already a valuable tool in natural products research. CCC separations consume relatively little solvent and don't require the use of expensive solid supports, making them highly economical, both environmentally and fiscally. The frugal use of consumables makes CCC much more "green" than other competing technologies. Determination of partition coefficients (K-values) is a unique analytical capability offered by CCC. However, accurate measurement of analyte partition coefficients with modern CCC instruments requires that sample loading be constrained far below system capacity. With current technology, the unique practical advantages of CCC are essentially lost when the conditions are optimized to determine K- values. In addition, successful use of CCC currently requires specialized training and considerable operator time. Automation, as it has for many other technologies, could effectively mitigate both the academic burden of assimilating decades of key information spread over hundreds of journal articles, and the practical burden of operating a complex multi-component system. Challenges imposed by the dynamic nature of the liquid CCC column had prevented the development of automated CCC until the SBC achieved a breakthrough proof of concept during Phase I of this SBIR project. The long-term objective of this project, and the ultimately marketable product, will be a fully functional automated CCC controller that will provide the separation power of CCC to minimally trained users, as well as enhance current capabilities and provide new functionality to experienced users. Automated CCC will provide a significant contribution to the goals of the National Institutes of Health (NIH), empowering biomedical researchers in their quest to analyze complex bioactive samples and alleviate human disease. The success of this project will be demonstrated by its application to the purification and study of bioactive natural products present in commonly consumed botanical products, one of which has shown promise in the fight against tuberculosis. PUBLIC HEALTH RELEVANCE: The analysis of highly complex chemical mixtures presents a significant scientific challenge, particularly in biomedical studies involving natural products and other complex biogenic samples. Countercurrent chromatography (CCC) is a technique, originally developed at NIH, which is able to solve many challenges in this area. This SBIR research proposal provides the key piece of technology required to bring the immense potential of CCC's analytical capabilities to realization, empowering biomedical researchers with a much-needed new tool in the arsenal to combat disease through biochemical discovery.
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DOI: 10.1021/acs.analchem.5b01613
发表时间: 2015-07-21
期刊: Analytical chemistry
影响因子: 7.4
作者: [Pauli GF, Pro SM, Chadwick LR, Burdick T, Pro L, Friedl W, Novak N, Maltby J, Qiu F, Friesen JB]
通讯作者: Friesen JB
Center for Natural Product Technologies at UIC (CeNAPT)
Center for Natural Product Technologies at UIC (CeNAPT)
Center for Natural Product Technologies at UIC (CeNAPT)
Center for Natural Product Technologies at UIC (CeNAPT)
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