High-throughput vibrational cytometry
高通量振动细胞术
基本信息
- 批准号:7876089
- 负责人:
- 金额:$ 18.46万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2010
- 资助国家:美国
- 起止时间:2010-05-01 至 2012-04-30
- 项目状态:已结题
- 来源:
- 关键词:AddressAreaBiological ModelsBiomedical ResearchCell CommunicationCell modelCellsCharacteristicsChemical StructureChemicalsClinicalCytometryDetectionDevelopmentEyeFlow CytometryFluorescenceImmunologyLifeLiquid substanceMeasuresMethodologyMethodsMicroscopicMonitorMultiparametric AnalysisNoiseOpticsParticle SizePathologyPharmacologic SubstancePharmacology and ToxicologyPropertyReproducibilityResearchSamplingScienceSignal TransductionSorting - Cell MovementSpectrum AnalysisSpeedStreamSystemTechniquesTechnologyTestinganalytical toolbaseinstrumentinstrumentationlight scatteringnovelparticlepathogenpublic health relevancetoolwater quality
项目摘要
DESCRIPTION (provided by applicant): Flow cytometry is a technology that allows a single cell or particle to be measured for a variety of characteristics, determined by looking at their properties while they flow in a liquid stream. High speed of flow and huge number of objects to be analyzed imposes some strict criteria on which methods can be used for analysis. Most of the known commercial instruments are currently using light scattering for particle sizing and fluorescence detection for chemical recognition. However, vibrational spectroscopy is the only non-invasive optical spectroscopy tool, which has proven to provide chemically-specific information about the interrogated sample. It is hypothesized that vibrational spectroscopy, based on nonlinear Raman scattering can be used to serve as an analytical tool for cytometry by providing rapid and accurate chemical recognition of flowing materials. In the proposed exploratory (R21) research, the idea of ultra-rapid analysis of chemical species will be experimentally tested with an eye on potential accommodation of the developed instrumentation to a commercial flow cytometer. A new instrument will be constructed (Aim 1) to attain the desired parameters needed for rapid, i.e. of the order of 10,000 analyses per second, detection and examination of living cells. The developed instrumentation will be meticulously tested (Aim 2) for its (a) sensitivity, (b) reproducibility, (c) signal- noise-ratio, and (e) speed of spectra acquisition and analysis. Finally (Aim 3), the developed and optimized instrumentation will be tested using a living cell model system to understand the applicability and potential trade-offs of vibrational spectroscopy to flow cytometry of cellular systems. The long-term of this proposal is to develop a rapid, non-invasive methodology for cell and particle analysis, which can be applied for cell/particle analysis and sorting, detection of bacterial pathogens, and cell interactions with pharmaceuticals. The proposed instrument is envisioned to become an important tool in fundamental and clinical biomedical research and will impact many areas of biomedical sciences by providing a novel way to analyze cells and chemical structures at unprecedented speed levels.
PUBLIC HEALTH RELEVANCE: Flow cytometry is a technique for counting, examining, and sorting microscopic particles in a stream of fluid. It allows simultaneous multiparametric analysis of the physical and/or chemical characteristics of single cells and particles. A truly non-invasive flow cytometer system, capable of providing chemically specific information, is proposed and will be developed and validated. The proposed technology has applications in a number of fields, such as pathology, immunology, toxicology, and pharmacology.
描述(由申请人提供):流式细胞仪是一项技术,可以通过在液体流中流动时查看其特性来确定其特性,以测量单个单元格或粒子。高速流量和要分析的大量对象施加了一些严格的标准,可以在其中使用方法进行分析。目前,大多数已知的商业仪器都使用光散射来进行颗粒尺寸和荧光检测进行化学识别。然而,振动光谱是唯一的非侵入性光谱工具,该工具已证明可以提供有关被询问样品的化学特异性信息。假设基于非线性拉曼散射的振动光谱可以通过提供流动材料的快速,准确的化学识别来用作细胞仪的分析工具。在拟议的探索性研究(R21)研究中,化学物种的超优化分析的想法将在实验测试中,以期待开发的仪器对商业流式细胞仪的潜在容纳。将构建一种新仪器(目标1),以达到快速的所需参数,即每秒10,000个分析的阶,对活细胞进行检测和检查。开发的仪器将针对其(a)灵敏度,(b)可重复性,(c)信号噪声比率和(e)光谱获取和分析的速度进行精心测试(AIM 2)。最后(AIM 3),将使用活细胞模型系统对开发和优化的仪器进行测试,以了解振动光谱对细胞系统流式细胞仪的适用性和潜在的权衡。该建议的长期是开发一种快速,非侵入性的方法来用于细胞和颗粒分析,该方法可用于细胞/颗粒分析和排序,检测细菌病原体以及与药物的细胞相互作用。拟议的仪器设想成为基本和临床生物医学研究的重要工具,并通过提供一种新颖的方式来以前所未有的速度水平分析细胞和化学结构,从而影响生物医学科学的许多领域。
公共卫生相关性:流式细胞仪是一种用于计数,检查和分类微观颗粒的技术。它允许对单细胞和颗粒的物理和/或化学特征同时进行多参数分析。提出并将开发和验证一个真正的非侵入性流式细胞仪系统,能够提供化学特定的信息。拟议的技术在许多领域中都有应用,例如病理学,免疫学,毒理学和药理学。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Vladislav V. Yakovlev其他文献
How to drive CARS in reverse
如何倒车行驶汽车
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2014 - 期刊:
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B. Hokr;Gary D. Noojin;Georgi I. Petrov;Hope T. Beier;Robert J. Thomas;Benjamin A. Rockwell;Vladislav V. Yakovlev - 通讯作者:
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Investigating chemotherapy effects on peripheral nerve elasticity
研究化疗对周围神经弹性的影响
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2024 - 期刊:
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- 作者:
Vsevolod Cheburkanov;Junwei Du;Mikhail Y. Berezin;Vladislav V. Yakovlev - 通讯作者:
Vladislav V. Yakovlev
Towards high-accuracy noninvasive ocular melanoma imaging and prognostics
迈向高精度非侵入性眼部黑色素瘤成像和预后
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Vsevolod Cheburkanov;Vladislav V. Yakovlev - 通讯作者:
Vladislav V. Yakovlev
Controlling quasi-parametric amplifications: From multiple PT-symmetry phase transitions to non-Hermitian sensing
控制准参数放大:从多个 PT 对称相变到非厄米传感
- DOI:
- 发表时间:
2024 - 期刊:
- 影响因子:0
- 作者:
Xiaoxiong Wu;Kai Bai;Penghong Yu;Zhaohui Dong;Yanyan He;Jingui Ma;Vladislav V. Yakovlev;Meng Xiao;Xianfeng Chen;Luqi Yuan - 通讯作者:
Luqi Yuan
Vladislav V. Yakovlev的其他文献
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{{ truncateString('Vladislav V. Yakovlev', 18)}}的其他基金
Sensing local nano-environment with coherent Raman microspectroscopy
使用相干拉曼显微光谱检测局部纳米环境
- 批准号:
10477258 - 财政年份:2021
- 资助金额:
$ 18.46万 - 项目类别:
Sensing local nano-environment with coherent Raman microspectroscopy
使用相干拉曼显微光谱检测局部纳米环境
- 批准号:
10218816 - 财政年份:2021
- 资助金额:
$ 18.46万 - 项目类别:
Brillouin Microscope for Biomedical Research
用于生物医学研究的布里渊显微镜
- 批准号:
10015304 - 财政年份:2018
- 资助金额:
$ 18.46万 - 项目类别:
Brillouin Microscope for Biomedical Research
用于生物医学研究的布里渊显微镜
- 批准号:
10239059 - 财政年份:2018
- 资助金额:
$ 18.46万 - 项目类别:
REAL-TIME MICROSCOPIC IMAGING OF MEMBRANE POTENTIAL
膜电位的实时显微成像
- 批准号:
6364640 - 财政年份:2001
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$ 18.46万 - 项目类别:
REAL-TIME MICROSCOPIC IMAGING OF FAST MEMBRANE POTENTIA
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6530140 - 财政年份:2001
- 资助金额:
$ 18.46万 - 项目类别:
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