EAGER: Mobile-phone based single molecule imaging of DNA and length quantification to analyze copy-number variations in genome

EAGER:基于手机的 DNA 单分子成像和长度定量分析基因组中的拷贝数变异

基本信息

  • 批准号:
    1444240
  • 负责人:
  • 金额:
    $ 30万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2014
  • 资助国家:
    美国
  • 起止时间:
    2014-10-01 至 2016-09-30
  • 项目状态:
    已结题

项目摘要

PI: Ozcan, AydoganInstitution: University of California-Los AngelesProposal number: 1444240Title: EAGER: Mobile-phone based single molecule imaging of DNA and length quantification to analyze copy-number variations in genomeThe aim of this proposal is to create a transformative fluorescent microscopy system that is integrated with next generation mobile-phones for imaging single DNA molecules. This field-portable imaging interface running on a smartphone will have the sensitivity and contrast to image single molecule DNA fragments over a large field of view. Demonstrating DNA imaging on a state-of-the-art mobile-phone would serve as a stepping stone to next-generation mobile micro-analysis, sensing and diagnostic tools and could lead to single molecule DNA sequencing on a smartphone.The proposed design will have the capability to be broadly used in various clinical applications including early detection of cancers (e.g. stomach and brain), nervous system disorders and drug resistance in infectious diseases. This cellphone based single molecule imaging, DNA platform could also assist health-care professionals, epidemiologists and policy makers to track emerging trends and shed more light on cause-effect relationships.Intellectual Description:Single molecule imaging and DNA length quantification, both of which are currently not feasible using mobile-phone based imaging systems; require extreme detection sensitivity, signal-to-noise ratio (SNR), spatial resolution and automated sample handling and processing interfaces. To provide a transformative solution to these important tasks, the PI will design a multifunctional portable imaging device installed on a smartphone which will allow sample preparation and single molecule imaging within the same opto-mechanical attachment. This fluorescence microscope on a smartphone will be designed by integrating a laser diode, a disposable nano-channel chip, an external lens and a thin-film based emission filter in a robust attachment created by 3D printing techniques. High SNR fluorescence signal detection will be achieved by implementing high-angle/oblique illumination so that the direct excitation beam will not enter the low NA collection lens. They will also develop a compressive sampling based DNA length-estimation method which will utilize (i) the measured point spread function of the fluorescent microscope on the mobile-phone; (ii) the spatial sparsity of the objects (fluorescently labeled DNA molecules); and (iii) the linearity of the stretched DNA molecules within the field of view as a-priori constraints to estimate the length of the DNA fragment of interest with an accuracy that is significantly better than the resolution of their initial imaging system.
PI:Ozcan,Aydogan研究所:加州大学洛杉矶分校建议编号:1444240标题:Eagle:基于移动电话的DNA单分子成像和长度量化,以分析基因组中的拷贝数变化这项建议的目的是创建一种变革性的荧光显微镜系统,该系统与下一代移动电话集成,用于对单DNA分子进行成像。这种在智能手机上运行的现场便携式成像界面将具有在大视野内对单分子DNA片段进行成像的灵敏度和对比度。在最先进的手机上演示DNA成像将成为下一代移动微观分析、传感和诊断工具的垫脚石,并可能导致在智能手机上进行单分子DNA测序。拟议的设计将有能力广泛应用于各种临床应用,包括癌症(如胃和脑)的早期检测、神经系统疾病和传染病中的耐药性。这个基于手机的单分子成像、DNA平台还可以帮助医疗保健专业人员、流行病学家和政策制定者跟踪新出现的趋势,并更多地阐明因果关系。智能描述:单分子成像和DNA长度量化,目前使用基于手机的成像系统都不可行;需要极高的检测灵敏度、信噪比(SNR)、空间分辨率以及自动样本处理和处理接口。为了为这些重要任务提供变革性的解决方案,PI将设计一种安装在智能手机上的多功能便携式成像设备,该设备将允许在同一光学机械附件中进行样品制备和单分子成像。这款智能手机上的荧光显微镜将通过将激光二极管、一次性纳米通道芯片、外部透镜和基于薄膜的发射滤光器集成到一个坚固的附件中来设计,该附件由3D打印技术创造。通过实现高角/斜照明,实现高信噪比的荧光信号检测,使直接激发光不会进入低NA采集透镜。他们还将开发一种基于压缩抽样的DNA长度估计方法,该方法将利用(I)移动电话上荧光显微镜的测量点扩散函数;(Ii)物体(荧光标记的DNA分子)的空间稀疏性;以及(Iii)视野内拉伸的DNA分子的线性作为先验约束来估计感兴趣的DNA片段的长度,其精度明显好于其初始成像系统的分辨率。

项目成果

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Aydogan Ozcan其他文献

All-optical object classification through unknown phase diffusers using a single-pixel diffractive machine vision system
使用单像素衍射机器视觉系统通过未知相位漫射器进行全光学物体分类
Deep Learning-designed Diffractive Materials for Optical Computing and Computational Imaging
用于光学计算和计算成像的深度学习设计的衍射材料
Automated HER2 Scoring in Breast Cancer Images Using Deep Learning and Pyramid Sampling
使用深度学习和金字塔采样对乳腺癌图像进行自动 HER2 评分
  • DOI:
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Şahan Yoruç Selçuk;Xilin Yang;Bijie Bai;Yijie Zhang;Yuzhu Li;Musa Aydin;Aras Firat Unal;Aditya Gomatam;Zhen Guo;Morgan Angus Darrow;Goren Kolodney;Karine Atlan;T. Haran;N. Pillar;Aydogan Ozcan
  • 通讯作者:
    Aydogan Ozcan
Super-Resolution Terahertz Imaging Through a Plasmonic Photoconductive Focal-Plane Array
通过等离子体光电导焦平面阵列进行超分辨率太赫兹成像
  • DOI:
    10.1364/cleo_si.2023.sm1n.2
  • 发表时间:
    2023
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Xurong Li;Deniz Mengu;Aydogan Ozcan;M. Jarrahi
  • 通讯作者:
    M. Jarrahi
Volumetric fluorescence microscopy using convolutional recurrent neural networks
使用卷积循环神经网络的体积荧光显微镜

Aydogan Ozcan的其他文献

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{{ truncateString('Aydogan Ozcan', 18)}}的其他基金

PFI-TT: A Rapid Multiplexed Diagnostic Tool for Serology of Tick-Borne Diseases
PFI-TT:蜱传疾病血清学快速多重诊断工具
  • 批准号:
    2345816
  • 财政年份:
    2024
  • 资助金额:
    $ 30万
  • 项目类别:
    Continuing Grant
Biopsy-free, label-free 3D virtual histology of intact skin
完整皮肤的免活检、免标记 3D 虚拟组织学
  • 批准号:
    2141157
  • 财政年份:
    2022
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
Deep learning-based serological test for point-of-care analysis of COVID-19 immunity with a paper-based multiplexed sensor
基于深度学习的血清学测试,使用纸基多重传感器对 COVID-19 免疫力进行即时分析
  • 批准号:
    2149551
  • 财政年份:
    2022
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
I-Corps: Multiplexed paper-based test for rapid diagnosis of early-stage Lyme Disease
I-Corps:用于快速诊断早期莱姆病的多重纸质测试
  • 批准号:
    2055749
  • 财政年份:
    2021
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
EAGER: High-throughput early detection and analysis of COVID-19 plaque formation using time-lapse coherent imaging and deep learning
EAGER:使用延时相干成像和深度学习对 COVID-19 斑块形成​​进行高通量早期检测和分析
  • 批准号:
    2034234
  • 财政年份:
    2020
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
EAGER: All-Optical Information Processing Device for Seeing Through Diffusers at the Speed of Light
EAGER:以光速透过漫射器的全光学信息处理装置
  • 批准号:
    2054102
  • 财政年份:
    2020
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
NSF EAGER: DEEP LEARNING-BASED VIRTUAL HISTOLOGY STAINING OF TISSUE SAMPLES
NSF EAGER:基于深度学习的组织样本虚拟组织学染色
  • 批准号:
    1926371
  • 财政年份:
    2019
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
PFI:BIC Human-Centered Smart-Integration of Mobile Imaging and Sensing Tools with Machine Learning for Ubiquitous Quantification of Waterborne and Airborne Nanoparticles
PFI:BIC 以人为中心的移动成像和传感工具与机器学习的智能集成,可实现水性和空气性纳米粒子的普遍定量
  • 批准号:
    1533983
  • 财政年份:
    2015
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
EFRI-BioFlex: Cellphone-based Digital Immunoassay Platform for High-throughput Sensitive and Multiplexed Detection and Distributed Spatio-Temporal Analysis of Influenza
EFRI-BioFlex:基于手机的数字免疫分析平台,用于流感的高通量灵敏多重检测和分布式时空分析
  • 批准号:
    1332275
  • 财政年份:
    2013
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant
CAREER: A new Telemedicine Platform using Incoherent Lensfree Cell Holography and Microscopy On a Chip
事业:使用非相干无透镜细胞全息术和芯片显微镜的新型远程医疗平台
  • 批准号:
    0954482
  • 财政年份:
    2010
  • 资助金额:
    $ 30万
  • 项目类别:
    Standard Grant

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