RUI:Development of a portable ECL immunosensor with mobile technologies

RUI:利用移动技术开发便携式ECL免疫传感器

基本信息

  • 批准号:
    1706597
  • 负责人:
  • 金额:
    $ 24.92万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2017
  • 资助国家:
    美国
  • 起止时间:
    2017-07-01 至 2022-06-30
  • 项目状态:
    已结题

项目摘要

Mobile technology is becoming the hub of future biosensor development. The proposed work attempts to develop an Electrochemiluminescence (ECL) sensor utilizing existing mobile (smartphone) technology, transforming what was traditionally an expensive and bulky biosensor technology into a portable and affordable one. ECL sensors work by a simple principle - when a small electric voltage is applied to an ECL chemical, the chemical emits light. The ECL combined with mobile technology enables minimal instrumentation and mobile app analysis. Our goal is to make this new sensor platform equivalent not only in performance to that of existing expensive biosensors, but also more affordable and for many different biosensor needs. The goal of this project is to advance the traditional electrochemiluminescence (ECL) immunosensor instrumentation to make it more portable and inexpensive using the latest mobile technologies. When an ECL reaction is triggered by the application of electric potential, the emitted light is in a visible spectrum, providing a great potential to satisfy the requirements for an ultra-sensitive immunoassay and in an ultra-compact format. Successful development of the proposed ECL biosensor will significantly enhance biosensor instrumentation by maximizing the practicality of mobile technologies while providing the sensitivity realized by expensive and specialized instruments. There have been attempts to develop ECL sensor with cell phone detectors but they have not been successful in detecting biomarkers at clinically relevant concentrations. The key effort of the proposed work are enhancing the inherently low ECL signal to a level that is detectable with consumer cameras and developing minimal instrumentation for efficient ECL-based detection. The research will focus on design as well as development of protocols with co-reactants, microfluidic channels on screen-printed-electrodes, electric circuits to trigger reactions, and a mobile app to control the circuit, imaging, and data analysis. The ECL immunosensor can be used for diagnosis of disease biomarkers. Its inexpensive and portable nature will make it an ideal platform to use in disaster rescue and recovery situations. The project will be performed at an undergraduate predominant institute maximizing educational aspects and emphasizing the community outreach.
移动技术正在成为未来生物传感器发展的中心。这项工作试图利用现有的移动(智能手机)技术开发一种电化学发光(ECL)传感器,将传统上昂贵而笨重的生物传感器技术转变为便携式和负担得起的技术。ECL传感器的工作原理很简单——当一个小电压加到ECL化学物质上时,这种化学物质就会发光。ECL与移动技术相结合,可以实现最小的仪器和移动应用程序分析。我们的目标是使这个新的传感器平台不仅在性能上与现有昂贵的生物传感器相当,而且更经济实惠,可以满足许多不同的生物传感器需求。该项目的目标是利用最新的移动技术,推进传统的电化学发光(ECL)免疫传感器仪器,使其更加便携和廉价。当ECL反应由电势触发时,发射的光在可见光谱中,提供了巨大的潜力,以满足超灵敏的免疫测定和超紧凑的格式的要求。所提出的ECL生物传感器的成功开发将通过最大限度地提高移动技术的实用性,同时提供昂贵和专用仪器所实现的灵敏度,从而显着增强生物传感器仪器。已经有人尝试开发带有手机检测器的ECL传感器,但它们在检测临床相关浓度的生物标志物方面尚未成功。所提出的工作的关键是将固有的低ECL信号增强到可以用消费者相机检测到的水平,并开发用于高效ECL检测的最小仪器。研究将集中在设计和开发共反应物协议、丝网印刷电极上的微流体通道、触发反应的电路以及控制电路、成像和数据分析的移动应用程序。ECL免疫传感器可用于疾病生物标志物的诊断。它的廉价和便携性将使它成为在灾难救援和恢复情况下使用的理想平台。该项目将在一个以本科生为主的学院进行,最大限度地提高教育水平,并强调社区外展。

项目成果

期刊论文数量(6)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Mechanistic modeling of redox balance effects on the fermentation of eucalyptus wood-derived xylose to acetone-butanol-ethanol
  • DOI:
    10.1016/j.bej.2022.108738
  • 发表时间:
    2022-11
  • 期刊:
  • 影响因子:
    3.9
  • 作者:
    E. C. Rivera;Daniel C. Assumpção;H. Kwon;C. Okonkwo;T. Ezeji;R. M. Filho;A. Mariano
  • 通讯作者:
    E. C. Rivera;Daniel C. Assumpção;H. Kwon;C. Okonkwo;T. Ezeji;R. M. Filho;A. Mariano
Development of smartphone-based ECL sensor for dopamine detection: Practical approaches
  • DOI:
    10.1016/j.rechem.2020.100029
  • 发表时间:
    2020-01-01
  • 期刊:
  • 影响因子:
    2.3
  • 作者:
    Kwon, Hyun J.;Rivera, Elmer Ccopa;Uppala, Padma P. Tadi
  • 通讯作者:
    Uppala, Padma P. Tadi
Data-Driven Modeling of Smartphone-Based Electrochemiluminescence Sensor Data Using Artificial Intelligence
  • DOI:
    10.3390/s20030625
  • 发表时间:
    2020-02-01
  • 期刊:
  • 影响因子:
    3.9
  • 作者:
    Rivera, Elmer Ccopa;Swerdlow, Jonathan J.;Kwon, Hyun J.
  • 通讯作者:
    Kwon, Hyun J.
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Hyun Kwon其他文献

Vision Control Unit in Fully Self Driving Vehicles using Xilinx MPSoC and Opensource Stack
使用 Xilinx MPSoC 和开源堆栈的全自动驾驶车辆中的视觉控制单元
357: Pulsed mode radiofrequency lesioning of the mental nerve for the treatment of trigeminal neuralgia
357:颏神经脉冲模式射频损伤治疗三叉神经痛
  • DOI:
  • 发表时间:
    2007
  • 期刊:
  • 影响因子:
    0
  • 作者:
    S. Sim;Youlim Kim;Hyun Kwon;Y. O. Park
  • 通讯作者:
    Y. O. Park
Dual-Targeted adversarial example in evasion attack on graph neural networks
图神经网络规避攻击中的双目标对抗示例
  • DOI:
    10.1038/s41598-025-85493-2
  • 发表时间:
    2025-01-31
  • 期刊:
  • 影响因子:
    3.900
  • 作者:
    Hyun Kwon;Dae-Jin Kim
  • 通讯作者:
    Dae-Jin Kim
Detecting Backdoor Attacks via Class Difference in Deep Neural Networks
  • DOI:
    10.1109/access.2020.3032411
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    3.9
  • 作者:
    Hyun Kwon
  • 通讯作者:
    Hyun Kwon
Genetically Predicted Body Selenium Concentration and estimated GFR: A Mendelian Randomization Study.
基因预测的体内硒浓度和估计的 GFR:孟德尔随机研究。
  • DOI:
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    6
  • 作者:
    Sehoon Park;S. Kim;S. Lee;Yaerim Kim;Semin Cho;Kwangsoo Kim;Hyun Kwon;S. Han;Hajeong Lee;J. P. Lee;K. Joo;C. Lim;Y. S. Kim;D. K. Kim
  • 通讯作者:
    D. K. Kim

Hyun Kwon的其他文献

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