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Imaging Cells and Tissues with Super-Resolution Structured Illumination Microscopy

Imaging Cells and Tissues with Super-Resolution Structured Illumination Microscopy
使用超分辨率结构化照明显微镜对细胞和组织进行成像
批准号:
10796461
负责人:
Guy Hagen
金额:
$9.99万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2018
资助国家:
美国
项目状态:
未结题
起止时间:
2018-07-01 至 2025-08-31

项目摘要

项目成果

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中文摘要
翻译
用超分辨率结构照明显微镜成像细胞和组织-项目
英文摘要
Imaging Cells and Tissues with Super-Resolution Structured Illumination Microscopy - Project Summary Fluorescence optical microscopy is one of the most important tools available for the study of biological systems at the cellular level. Unfortunately, due to diffraction phenomena the resolution of fluorescence microscopes in the lateral dimension is limited to about 250 nm. As many biological structures within cells are much smaller than this, increasing resolution is of prime importance. Although several methods are now available which are able to extend the resolution of optical microscopes beyond the diffraction limit, imaging cells and tissues with these methods remains a challenge. Super-resolution structured illumination microscopy (SIM), which can achieve a resolution of approximately 100 nm, is a suitable super-resolution method for cells and tissues. However, adoption of this technique by biologists is hindered by the inflexible equipment and artifact- prone image analysis algorithms which are currently available. The solution to this problem demands innovations in both optical design and in data processing methods which are used in SIM. In particular, imaging deeper into tissues with SIM has not been realized so far. The goal of this interdisciplinary project is to develop, improve, and utilize super-resolution microscopy with a focus on imaging both cells and tissues. In Aim 1 we will develop alternative illumination approaches for SIM using economical components, and we will develop and implement improved SIM reconstruction algorithms which produce results with higher resolution, quality, and more reliable results than are available with current methods. These methods will allow imaging into tissues up to 500 micrometers, about 10-fold better than current technology allows. In Aim 2, we will develop new algorithms based on machine learning for optical sectioning microscopy and for denoising of microscopy images. In Aim 3, we will use the newly developed suite of methods for studies of the molecular basis of allergic responses. We will use structured illumination microscopy to study the relationship between cell surface receptors and the morphology of the plasma membrane, and we will develop a reaction-diffusion model to better understand the biophysics of the cell membrane.
期刊论文(16)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1088/1361-6528/ac622e
发表时间: 2022-05-13
期刊: Nanotechnology
影响因子: 3.5
作者: []
通讯作者:
DOI: 10.3390/bioengineering10091081
发表时间: 2023-09-13
期刊: BIOENGINEERING-BASEL
影响因子: 4.6
作者: [Paul, Tristan C., Johnson, Karl A., Hagen, Guy M.]
通讯作者: Hagen, Guy M.
DOI: 10.3389/frai.2021.642731
发表时间: 2021
期刊: Frontiers in artificial intelligence
影响因子: 4
作者: [Moreno López M, Frederick JM, Ventura J]
通讯作者: Ventura J
DOI: 10.1021/acsphotonics.1c00151
发表时间: 2021-04-21
期刊: ACS photonics
影响因子: 7
作者: [Melnyk O, Jones R, Macêdo R, Garbovskiy Y, Hagen G, Glushchenko AV, Spendier K, Camley RE]
通讯作者: Camley RE
13
    Imaging Cells and Tissues with Super-Resolution Structured Illumination Microscopy
    • 批准号:
      10515036
    • 项目类别:
    • 资助金额:
      $41.3万
    • 财政年份:
      2018
    • 负责人:
      Guy Hagen
    • 依托单位:
    海外基金