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.
循环肿瘤细胞越来越被认为是早期癌症检测中的预测性生物标志物;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,包括早期癌症检测以及癌症进展的诊断和预测。如果可以从全血中分离出存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有性,成功的分离技术必须同时满足高通量、高灵敏度、高纯度和高活力的性能指标才有用-这是从未实现的目标。为了解决这些性能指标,该项目采用了一种新的三重方法,称为三维确定性介电泳。目前,细胞分离过程中的三维几何形状、确定性横向位移和介电电泳的组合效应代表了研究中的空白。通过这项研究,流体力学,细胞变形,介电电泳力和确定性的横向位移结构之间的相互作用的全面理解将获得,这将导致大大提高灵敏度,纯度和细胞活力在高通量-所有要求都得到满足的同时。此外,该项目将对芝加哥伊利诺伊大学(联邦指定的少数民族服务机构)和华盛顿州立大学温哥华分校(本科院校研究合格的机构和西南华盛顿唯一的四年制研究型大学)的技术领域的大量代表性不足的学生产生重大影响。三维确定性介电电泳方法通过在以前不相关的想法和领域知识之间建立有意义和有价值的联系带来了变革性的影响-即确定性横向位移,介电电泳和三维打印-可能会破坏并超越所有现有的替代品。然而,为了使该方法真正用于医疗实践,必须获得有关分离过程的基本知识。本研究分为三个研究目标:1)利用实验验证的预测模型研究周期性障碍阵列中的细胞输运、细胞-障碍物碰撞动力学和细胞介电电泳; 2)制造三维确定性介电电泳装置,并表征不同的障碍物形状、几何形状、障碍物阵列图案、介电电泳场参数,载体流体和流速影响细胞分离性能; 3)根据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。该研究具有重要意义,因为多物理场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微流控装置的实验实现。这项研究的独特之处在于,介电电泳将首次与三维微结构中的确定性横向位移相结合,这是通过最先进的纳米三维打印技术实现的。随着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,该研究成果对包括早期癌症检测以及癌症进展的诊断和预测在内的临床应用具有重要意义。该奖项反映了NSF的法定使命,并通过使用基金会的知识价值和更广泛的影响评审标准进行评估,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
Basic principles and optical system design of 17.48 keV high-throughput modified Wolter x-ray microscope
17.48 keV高通量改良Wolter X射线显微镜基本原理及光学系统设计
- DOI:
10.1063/5.0105015 - 发表时间:
2022 - 期刊:
- 影响因子:1.6
- 作者:
Yaran Li;Wenjie Li;Liang Chen;Huanzhen Ma;Xinye Xu;Jie Xu;Xin Wang;Baozhong Mu - 通讯作者:
Baozhong Mu
A semi-analytical algorithm for deriving the particle size distribution slope of turbid inland water based on OLCI data: a case study in Lake Hongze
基于OLCI数据推导内陆浑浊水体粒径分布斜率的半解析算法——以洪泽湖为例
- DOI:
10.1016/j.envpol.2020.116288 - 发表时间:
2020 - 期刊:
- 影响因子:8.9
- 作者:
Shaohua Lei;Jie Xu;Yunmei Li;Lin Li;Heng Lyu;Ge Liu;Yu Chen - 通讯作者:
Yu Chen
Chinese Researchers, Scholarly Communication Behavious, and Trust
中国研究者、学术交流行为和信任
- DOI:
- 发表时间:
2016 - 期刊:
- 影响因子:2.8
- 作者:
David Nicholas;Jie Xu;Lifang Xu;Jing Su;Anthony Watkinson - 通讯作者:
Anthony Watkinson
Proton-assisted growth of ultra-flat graphene films
质子辅助生长超平坦石墨烯薄膜
- DOI:
10.1038/s41586-019-1870-3 - 发表时间:
2020-01 - 期刊:
- 影响因子:0
- 作者:
Guowen Yuan;Dongjing Lin;Yong Wang;Xianlei Huang;Wang Chen;Xuedong Xie;Junyu Zong;Qian-Qian Yuan;Hang Zheng;Di Wang;Jie Xu;Shao-Chun Li;Yi Zhang;Jian Sun;Xiaoxiang Xi;Libo Gao - 通讯作者:
Libo Gao
A facile and efficient method to improve the selectivity of methyl lactate in the chemocatalytic conversion of glucose catalyzed by homogeneous Lewis acid
一种简便有效的提高均相路易斯酸催化葡萄糖化学催化转化乳酸甲酯选择性的方法
- DOI:
10.1016/j.molcata.2014.01.017 - 发表时间:
2014-07 - 期刊:
- 影响因子:0
- 作者:
Xiaomei Yang;Yunlai Su;Tiangliang Lu;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
Collaborative Research: CCSS: Hierarchical Federated Learning over Highly-Dense and Overlapping NextG Wireless Deployments: Orchestrating Resources for Performance
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
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
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
- 资助金额:
$ 27.77万 - 项目类别:
Standard Grant
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
- 批准号:
2044991 - 财政年份:2021
- 资助金额:
$ 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
- 批准号:
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
合作研究:SWIFT:SMALL:理解和对抗对抗性频谱学习以实现频谱高效的无线网络
- 批准号:
2029858 - 财政年份:2020
- 资助金额:
$ 27.77万 - 项目类别:
Standard Grant
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
- 批准号:
2006630 - 财政年份:2020
- 资助金额:
$ 27.77万 - 项目类别:
Standard Grant
Collaborative Research: Improving Power Grids Weather Resilience through Model-free Dimension Reduction and Stochastic Search for Optimal Hardening
合作研究:通过无模型降维和随机搜索优化强化来提高电网的耐候能力
- 批准号:
1923145 - 财政年份:2019
- 资助金额:
$ 27.77万 - 项目类别:
Standard Grant
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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