Collaborative Research: Towards High-Throughput Label-Free Circulating Tumor Cell Separation using 3D Deterministic Dielectrophoresis (D-Cubed)
合作研究:利用 3D 确定性介电泳 (D-Cubed) 实现高通量无标记循环肿瘤细胞分离
基本信息
- 批准号:1917295
- 负责人:
- 金额:$ 27.77万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2019
- 资助国家:美国
- 起止时间:2019-07-01 至 2023-06-30
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Circulating tumor cells are increasingly recognized as predictive biomarkers in early cancer detection; therefore, detecting circulating tumor cells in the peripheral blood of patients has important implications for clinical applications, which include early cancer detection as well as diagnoses and prediction of cancer progression. If viable unmodified circulating tumor cells can be separated from whole blood, then subsequent clinical analysis of these cells can lead to personalized cancer treatment. However, due to the extreme rarity of circulating tumor cells, a successful separation technology must meet the performance metrics of high-throughput, high-sensitivity, high-purity, and high-viability simultaneously to be useful - a goal that has never been achieved. To tackle these performance metrics, this project utilizes a novel threefold method called Three-Dimensional Deterministic Dielectrophoresis. Currently, the combined effects of three-dimensional geometry, deterministic lateral displacement and dielectrophoresis in a cell separation process represent a gap in research. Through this research, comprehensive understanding of the interplay between fluid mechanics, cell deformation, dielectrophoretic forces, and deterministic lateral displacement structures will be gained, which will lead to much improved sensitivity, purity, and cell viability at high-throughput - all requirements to be met at the same time. Additionally, the project will have a significant impact on a large number of underrepresented students in technical fields at both University of Illinois at Chicago (a federally designated Minority Serving Institution) and Washington State University Vancouver (a Research in Undergraduate Institutions eligible institution and the only four-year research university in southwest Washington). The Three-Dimensional Deterministic Dielectrophoresis method brings a transformative impact by creating meaningful and valuable links between previously unconnected ideas and domain knowledge - namely deterministic lateral displacement, dielectrophoresis, and three-dimensional printing - potentially disrupting and outperforming all existing alternatives. However, in order to make the method truly useful for medical practice, fundamental knowledge about the separation process must be gained. This breaks down into three research objectives: 1) Study cell transport, cell-obstacle collision dynamics, and cell dielectrophoresis in periodic obstacle arrays using predictive models with experimental validations; 2) Fabricate Three-Dimensional Deterministic Dielectrophoresis devices and characterize how different obstacle shapes, geometries, obstacle array patterns, dielectrophoresis field parameters, carrier fluids and flow rates influence the cell separation performance; 3) Characterize circulating tumor cell separation performance for lung tumor cells against the four performance metrics above. This proposed research is significant because the multiphysics numerical models will elucidate scientific mechanisms of the complex separation principles of this method, which will guide experimental realization of a microfluidic device for high-throughput label-free circulating tumor cell separation. The research is unique in that dielectrophoresis will be combined with deterministic lateral displacement in a three-dimensional micro-structure for the first time, which is enabled by state-of-the-art nano three-dimensional printing technology. The research outcomes here have important implications for clinical applications including early cancer detection as well as diagnosis and prediction of cancer progression, as circulating tumor cells are increasingly recognized as predictive biomarkers in early stage cancer.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
循环肿瘤细胞被认为是癌症早期检测的预测生物标志物,因此检测患者外周血中的循环肿瘤细胞对临床应用具有重要意义,包括癌症的早期检测以及对癌症进展的诊断和预测。如果可以从全血中分离出活的未经修饰的循环肿瘤细胞,那么随后对这些细胞的临床分析可以导致个性化的癌症治疗。然而,由于循环肿瘤细胞的极端稀缺性,成功的分离技术必须同时满足高通量、高灵敏度、高纯度和高活性的性能指标才能有用--这是一个从未实现的目标。为了解决这些性能指标,该项目使用了一种新的三重方法,称为三维确定介电泳法。目前,在细胞分离过程中,三维几何、确定性侧向位移和介电泳法的综合效应是研究的一个空白。通过这项研究,将全面了解流体力学、细胞变形、介电泳力和确定性的横向位移结构之间的相互作用,这将大大提高灵敏度、纯度和高通量下的细胞存活率-所有这些要求都将同时得到满足。此外,该项目将对伊利诺伊大学芝加哥分校(联邦指定的少数族裔服务机构)和华盛顿州立大学温哥华分校(符合条件的本科院校研究机构,也是华盛顿州西南部唯一的四年制研究型大学)在技术领域的大量代表不足的学生产生重大影响。三维确定性介电泳法通过在以前未连接的想法和领域知识之间创建有意义和有价值的链接-即确定性横向位移、介电泳法和三维打印-带来了革命性的影响,潜在地颠覆了所有现有的替代方案,并超越了所有现有的替代方案。然而,为了使该方法真正用于医疗实践,必须获得关于分离过程的基本知识。本研究分为三个研究目标:1)使用预测模型研究周期性障碍阵列中的细胞传输、细胞-障碍碰撞动力学和细胞介电;2)制作三维确定性介电设备,并表征不同障碍形状、几何形状、障碍阵列模式、介电泳场参数、载液和流速对细胞分离性能的影响;3)以上述四个性能指标表征肺肿瘤细胞的循环肿瘤细胞分离性能。这项研究具有重要意义,因为多物理数值模型将阐明该方法复杂分离原理的科学机制,这将指导高通量无标记循环肿瘤细胞分离的微流控装置的实验实现。这项研究的独特之处在于,通过最先进的纳米三维打印技术,将首次在三维微结构中将介电泳与确定的横向位移相结合。这里的研究成果对临床应用具有重要的影响,包括早期癌症检测以及癌症进展的诊断和预测,因为循环肿瘤细胞越来越多地被认为是早期癌症的预测生物标志物。这一奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
项目成果
期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Separation of Non-Viable Chinese Hamster Ovary (CHO) Cells Using Dielectrophoresis in a Deterministic Lateral Displacement Ratchet
使用确定性横向位移棘轮中的介电泳分离无活力的中国仓鼠卵巢 (CHO) 细胞
- DOI:10.1115/imece2020-23520
- 发表时间:2020
- 期刊:
- 影响因子:0
- 作者:Khan, Mohammed;Chen, Xiaolin;Xu, Jie
- 通讯作者:Xu, Jie
AC electroosmosis micromixing on a lab-on-a-foil electric microfluidic device
- DOI:10.1016/j.snb.2022.131611
- 发表时间:2022-02
- 期刊:
- 影响因子:0
- 作者:Mengren Wu;Yuan Gao;A. Ghaznavi;Weiqi Zhao;Jie Xu
- 通讯作者:Mengren Wu;Yuan Gao;A. Ghaznavi;Weiqi Zhao;Jie Xu
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Jie Xu其他文献
Design Challenges and Guidelines for Persuasive Technologies that Facilitate Healthy Lifestyles.
促进健康生活方式的说服性技术的设计挑战和指南。
- DOI:
- 发表时间:
2012 - 期刊:
- 影响因子:0
- 作者:
Jie Xu;Ping;Scott Uglow;Alison Scott;E. Montague - 通讯作者:
E. Montague
On demand generation of drop and bubble in a microfluidic chip
微流控芯片中按需生成液滴和气泡
- DOI:
- 发表时间:
2008 - 期刊:
- 影响因子:0
- 作者:
Jie Xu;Daniel Attinger - 通讯作者:
Daniel Attinger
Structure and Properties of Ultrathin SiOx Films on Cu(111)
Cu(111)上超薄SiOx薄膜的结构与性能
- DOI:
10.1021/acs.langmuir.2c01701 - 发表时间:
2022 - 期刊:
- 影响因子:3.9
- 作者:
Jie Xu;Changle Mu;Mingshu Chen - 通讯作者:
Mingshu Chen
Designing messages with high sensation value: When activation meets reactance
设计具有高感觉价值的消息:当激活遇到抗拒时
- DOI:
10.1080/08870446.2014.977280 - 发表时间:
2015 - 期刊:
- 影响因子:3.3
- 作者:
Jie Xu - 通讯作者:
Jie Xu
Well dispersive Ni nanoparticles embedded in core-shell supports as efficient catalysts for 4-nitrophenol reduction
嵌入核壳载体中的分散性良好的镍纳米粒子作为 4-硝基苯酚还原的有效催化剂
- DOI:
10.1007/s11051-019-4551-0 - 发表时间:
2019-06 - 期刊:
- 影响因子:2.5
- 作者:
Xiaoshan Yang;Zhenwei Wang;Yuanyuan Shang;Yingjiu Zhang;Qing Lou;Baojun Li;Jie Xu - 通讯作者:
Jie Xu
Jie Xu的其他文献
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{{ truncateString('Jie Xu', 18)}}的其他基金
Elucidating Mechanisms of Metal Sulfide-Enabled Growth of Anoxygenic Photosynthetic Bacteria Using Transcriptomic, Aqueous/Surface Chemical, and Electron Microscopic Tools
使用转录组、水/表面化学和电子显微镜工具阐明金属硫化物促进不产氧光合细菌生长的机制
- 批准号:
2311021 - 财政年份:2023
- 资助金额:
$ 27.77万 - 项目类别:
Standard Grant
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协作研究:CCSS:高密度和重叠的 NextG 无线部署的分层联合学习:编排资源以提高性能
- 批准号:
2319780 - 财政年份:2023
- 资助金额:
$ 27.77万 - 项目类别:
Standard Grant
SAI-R: Strengthening American Electricity Infrastructure for an Electric Vehicle Future: An Energy Justice Approach
SAI-R:加强美国电力基础设施以实现电动汽车的未来:能源正义方法
- 批准号:
2228603 - 财政年份:2022
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CAREER: Wireless InferNets: Enabling Collaborative Machine Learning Inference on the Network Path
职业:无线推理网:在网络路径上实现协作机器学习推理
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2044991 - 财政年份:2021
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$ 27.77万 - 项目类别:
Continuing Grant
CCSS: Collaborative Research: Towards a Resource Rationing Framework for Wireless Federated Learning
CCSS:协作研究:无线联邦学习的资源配给框架
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2033681 - 财政年份:2020
- 资助金额:
$ 27.77万 - 项目类别:
Standard Grant
Collaborative Research: SWIFT: SMALL: Understanding and Combating Adversarial Spectrum Learning towards Spectrum-Efficient Wireless Networking
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2029858 - 财政年份:2020
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$ 27.77万 - 项目类别:
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Collaborative Research: CNS Core: Small: Towards Automated and QoE-driven Machine Learning Model Selection for Edge Inference
合作研究:CNS 核心:小型:面向边缘推理的自动化和 QoE 驱动的机器学习模型选择
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2006630 - 财政年份:2020
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1923145 - 财政年份:2019
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$ 27.77万 - 项目类别:
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Collaborative Research: NSF/ENG/ECCS-BSF: Complex liquid droplet structures as new optical and optomechanical materials
合作研究:NSF/ENG/ECCS-BSF:复杂液滴结构作为新型光学和光机械材料
- 批准号:
1711798 - 财政年份:2017
- 资助金额:
$ 27.77万 - 项目类别:
Standard Grant
EAGER-Dynamic Data: A New Scalable Paradigm for Optimal Resource Allocation in Dynamic Data Systems via Multi-Scale and Multi-Fidelity Simulation and Optimization
EAGER-动态数据:通过多尺度和多保真度仿真和优化实现动态数据系统中最佳资源分配的新可扩展范式
- 批准号:
1462409 - 财政年份:2015
- 资助金额:
$ 27.77万 - 项目类别:
Standard Grant
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