EAGER: Establishing Near-Ultraviolet Coherent Anti-Stokes Raman Scattering Microscopy for Highly Sensitive Imaging of Native Biomolecules

EAGER：建立近紫外相干反斯托克斯拉曼散射显微镜，对天然生物分子进行高灵敏成像

• 批准号: 2332594
• 负责人: Fake Lu
• 金额: $ 30万
• 依托单位: SUNY at Binghamton
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2332594&HistoricalAwards=false
• 关键词: EAGER; Establishing; Near; Ultraviolet; Coherent; EAGER; Establishing; Near; Ultraviolet; Coherent

During brain tumor resection, pathologists are often consulted to help guide surgical decisions. However, current surgical pathology procedures are time-consuming and labor-intensive, involving tissue cryosectioning and chemical staining. Coherent Raman microscopy is a promising technology to render label-free pathology-like images of tissue. Current coherent Raman imaging uses visible or near-infrared (NIR) light and has limited sensitivity when imaging native DNA molecules in the nucleus of a cell. This project will leverage near-ultraviolet (NUV) light and coherent anti-Stokes Raman scattering (CARS) imaging to break the sensitivity hurdle. The NUV-CARS imaging system will be applied to develop label-free digital pathology for brain tumor diagnosis. This technology holds the potential to advance the fields of surgical pathology and image-guided surgery. This project will provide training opportunities in biophotonics and data science for undergraduate and graduate students with diverse backgrounds. The goal of this EAGER project is to establish NUV-CARS microscopy for high-resolution, highly sensitive imaging of native biomolecules and apply this imaging tool to develop label-free digital pathology for brain tumor diagnosis. While NIR-CARS is able to perform rapid chemical imaging of live cells and tissue, it suffers from a low detection sensitivity when imaging native biomolecules. NUV-CARS will leverage the electric pre-resonance effect to achieve a significantly enhanced sensitivity for imaging chemical bonds in native biological molecules. Novel nonlinear optical strategies with quartz optics will be implemented to manage the non-resonant background and UV photodamage. With NUV-CARS, the true chemical contrast of DNA molecules will be obtained to render pathological images similar to the images with hematoxylin and eosin (H&E) staining, which will be used for fresh tissue-based brain tumor diagnosis. This research will advance the knowledge in the fields of NUV coherent Raman and multiphoton fluorescence, paving the way for groundbreaking advancements in scientific knowledge and technological applications. NUV-CARS imaging with machine learning algorithms will enable fresh tissue-based digital pathology for brain tumor diagnosis, which can be readily applied to other types of cancer surgeries.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.

在脑肿瘤切除过程中，经常会咨询病理学家，以帮助指导手术决策。但是，当前的手术病理程序是时必的且劳动力密集的，涉及组织冷冻和化学染色。连贯的拉曼显微镜是一项有前途的技术，可提供无标记的组织样图像。当前的相干拉曼成像使用可见的或近红​​外（NIR）的光，当成像细胞核中的天然​​DNA分子成像时具有有限的敏感性。该项目将利用接近粉状的光（NUV）光线和连贯的反stokes拉曼散射（CARS）成像来打破敏感性障碍。 NUV-CARS成像系统将应用于开发无标签的数字病理学用于脑肿瘤诊断。这项技术具有推进手术病理和图像引导手术领域的潜力。该项目将为本科生和研究生提供不同背景的本科生和研究生提供培训机会。这个渴望的项目的目的是建立NUV-CARS显微镜，用于对天然生物分子的高分辨率，高度敏感的成像，并应用此成像工具来开发无标签的数字病理学来用于脑肿瘤诊断。尽管NIR-CARS能够对活细胞和组织进行快速化学成像，但在成像天然生物分子时，它的检测灵敏度低。 NUV-CARS将利用电呼应效应来实现对天然生物分子中化学键的敏感性的显着增强。将实施具有石英光学的新型非线性光学策略，以管理非共振背景和紫外光损伤。使用NUV-CARS，将获得DNA分子的真正化学对比度，以渲染与苏木精和曙红（H＆E）染色图像相似的病理图像，该图像将用于基于新鲜的组织脑肿瘤诊断。这项研究将提高NUV相干拉曼和多光子荧光领域的知识，为科学知识和技术应用的开创性进步铺平了道路。使用机器学习算法进行NUV-CARS成像将使基于组织的数字病理学用于脑肿瘤诊断，可以很容易地将其应用于其他类型的癌症手术。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛的影响审查标准来通过评估来支持的。