12 February 2018 Deep brain two-photon NIR fluorescence imaging for study of Alzheimer’s disease
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Proceedings Volume 10481, Neural Imaging and Sensing 2018; 104810A (2018) https://doi.org/10.1117/12.2286860
Event: SPIE BiOS, 2018, San Francisco, California, United States
Abstract
Amyloid depositions in the brain represent the characteristic hallmarks of Alzheimer’s disease (AD) pathology. The abnormal accumulation of extracellular amyloid-beta (Aβ) and resulting toxic amyloid plaques are considered to be responsible for the clinical deficits including cognitive decline and memory loss. In vivo two-photon fluorescence imaging of amyloid plaques in live AD mouse model through a chronic imaging window (thinned skull or craniotomy) provides a mean to greatly facilitate the study of the pathological mechanism of AD owing to its high spatial resolution and long-term continuous monitoring. However, the imaging depth for amyloid plaques is largely limited to upper cortical layers due to the short-wavelength fluorescence emission of commonly used amyloid probes. In this work, we reported that CRANAD-3, a near-infrared (NIR) probe for amyloid species with excitation wavelength at 900 nm and emission wavelength around 650 nm, has great advantages over conventionally used probes and is well suited for twophoton deep imaging of amyloid plaques in AD mouse brain. Compared with a commonly used MeO-X04 probe, the imaging depth of CRANAD-3 is largely extended for open skull cranial window. Furthermore, by using two-photon excited fluorescence spectroscopic imaging, we characterized the intrinsic fluorescence of the “aging pigment” lipofuscin in vivo, which has distinct spectra from CRANAD-3 labeled plaques. This study reveals the unique potential of NIR probes for in vivo, high-resolution and deep imaging of brain amyloid in Alzheimer’s disease.
Conference Presentation
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Congping Chen, Zhuoyi Liang, Biao Zhou, Nancy Y. Ip, Jianan Y. Qu, "Deep brain two-photon NIR fluorescence imaging for study of Alzheimer’s disease", Proc. SPIE 10481, Neural Imaging and Sensing 2018, 104810A (12 February 2018); doi: 10.1117/12.2286860; https://doi.org/10.1117/12.2286860
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