Decreased cerebral blood flow causes brain ischemia and plays an important role in the pathophysiology of many neurodegenerative diseases, including Alzheimer’s disease and vascular dementia. In this study, we photomodulated astrocytes in the live animal by a combination of two-photon calcium uncaging in the astrocyte endfoot and in vivo imaging of neurovasculature and astrocytes by intravital two-photon microscopy after labeling with cell type specific fluorescent dyes. Our study demonstrates that photomodulation at the endfoot of a single astrocyte led to a 25% increase in the diameter of a neighboring arteriole, which is a crucial factor regulating cerebral microcirculation in downstream capillaries. Two-photon uncaging in the astrocyte soma or endfoot near veins does not show the same effect on microcirculation. These experimental results suggest that infrared photomodulation on astrocyte endfeet may be a strategy to increase cerebral local microcirculation and thus prevent brain ischemia.
Neurovascular dysfunction in many neurodegenerative diseases, such as Alzheimer’s disease (AD), reduces blood flow to affected brain areas and causes neuronal dysfunction and loss. A new optical imaging technique is developed to activate astrocytes in live animal models in order to investigate the increase of local cerebral blood flow as a potential therapeutic strategy for AD. The technique uses fluorescent labeling of vasculature and astrocytes coupled with intravital 2-photon microscopy to visualize the astrocyte-vasculature interactions in live animals. Using femtosecond laser stimulation, calcium uncaging is applied to specifically target and activate astrocytes in vivo with high spatial and temporal resolutions. Intravital 2-photon microscopy imaging was employed to demonstrate that single endfoot optical activation around an arteriole induced a 25% increase in arteriole diameter, which in turn increased cerebral local blood flow in down-stream capillaries. This quantitative result indicates the potential of using optical activation of astrocytes in afflicted brain areas of neurodegeneration to restore normal neurovascular functions.
Deep brain stimulation (DBS) of the cholinergic nuclei has emerged as a powerful potential treatment for neurodegenerative disease and is currently in a clinical trial for Alzheimer’s therapy. While effective in treatment for a number of conditions from depression to epilepsy, DBS remains somewhat unpredictable due to the heterogeneity of the projection neurons that are activated, including glutamatergic, GABAergic, and cholinergic neurons, leading to unacceptable side effects ranging from apathy to depression or even suicidal behavior. It would be highly advantageous to confine stimulation to specific populations of neurons, particularly in brain diseases involving complex network interactions such as Alzheimer’s. Optogenetics, now firmly established as an effective approach to render genetically-defined populations of cells sensitive to light activation including mice expressing Channelrhodopsin-2 specifically in cholinergic neurons, provides just this opportunity. Here we characterize the light activation properties and cell density of cholinergic neurons in healthy mice and mouse models of Alzheimer’s disease in order to evaluate the feasibility of using optogenetic modulation of cholinergic synaptic activity to slow or reverse neurodegeneration. This paper is one of the very first reports to suggest that, despite the anatomical depth of their cell bodies, cholinergic projection neurons provide a better target for systems level optogenetic modulation than cholinergic interneurons found in various brain regions including striatum and the cerebral cortex. Additionally, basal
forebrain channelrhodopsin-expressing cholinergic neurons are shown to exhibit normal distribution at 60 days and normal light activation at 40 days, the latest timepoints observed. The data collected form the basis of ongoing computational modeling of light stimulation of entire populations of cholinergic neurons.
The advent of molecularly targeted therapies requires effective identification of the various cell types of non-small cell lung carcinomas (NSCLC). Currently, cell type diagnosis is performed using small biopsies or cytology specimens that are often insufficient for molecular testing after morphologic analysis. Thus, the ability to rapidly recognize different cancer cell types, with minimal tissue consumption, would accelerate diagnosis and preserve tissue samples for subsequent molecular testing in targeted therapy. We report a label-free molecular vibrational imaging framework enabling three-dimensional (3-D) image acquisition and quantitative analysis of cellular structures for identification of NSCLC cell types. This diagnostic imaging system employs superpixel-based 3-D nuclear segmentation for extracting such disease-related features as nuclear shape, volume, and cell-cell distance. These features are used to characterize cancer cell types using machine learning. Using fresh unstained tissue samples derived from cell lines grown in a mouse model, the platform showed greater than 97% accuracy for diagnosis of NSCLC cell types within a few minutes. As an adjunct to subsequent histology tests, our novel system would allow fast delineation of cancer cell types with minimum tissue consumption, potentially facilitating on-the-spot diagnosis, while preserving specimens for additional tests. Furthermore, 3-D measurements of cellular structure permit evaluation closer to the native state of cells, creating an alternative to traditional 2-D histology specimen evaluation, potentially increasing accuracy in diagnosing cell type of lung carcinomas.
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