Late chronic local inflammation, synaptic alterations, vascular remodeling and arteriovenous malformations in the brains of male rats exposed to repetitive low-level blast overpressures.

In the course of military operations in modern war theaters, blast exposures are associated with the development of a variety of mental health disorders associated with a post-traumatic stress disorder-related features, including anxiety, impulsivity, insomnia, suicidality, depression, and cognitive decline. Several lines of evidence indicate that acute and chronic cerebral vascular alterations are involved in the development of these blast-induced neuropsychiatric changes. In the present study, we investigated late occurring neuropathological events associated with cerebrovascular alterations in a rat model of repetitive low-level blast-exposures (3 × 74.5 kPa). The observed events included hippocampal hypoperfusion associated with late-onset inflammation, vascular extracellular matrix degeneration, synaptic structural changes and neuronal loss. We also demonstrate that arteriovenous malformations in exposed animals are a direct consequence of blast-induced tissue tears. Overall, our results further identify the cerebral vasculature as a main target for blast-induced damage and support the urgent need to develop early therapeutic approaches for the prevention of blast-induced late-onset neurovascular degenerative processes.

Low-level blast exposure induces chronic vascular remodeling, perivascular astrocytic degeneration and vascular-associated neuroinflammation.

Cerebral vascular injury as a consequence of blast-induced traumatic brain injury is primarily the result of blast wave-induced mechanical disruptions within the neurovascular unit. In rodent models of blast-induced traumatic brain injury, chronic vascular degenerative processes are associated with the development of an age-dependent post-traumatic stress disorder-like phenotype. To investigate the evolution of blast-induced chronic vascular degenerative changes, Long-Evans rats were blast-exposed (3 × 74.5 kPa) and their brains analyzed at different times post-exposure by X-ray microcomputed tomography, immunohistochemistry and electron microscopy. On microcomputed tomography scans, regional cerebral vascular attenuation or occlusion was observed as early as 48 h post-blast, and cerebral vascular disorganization was visible at 6 weeks and more accentuated at 13 months post-blast. Progression of the late-onset pathology was characterized by detachment of the endothelial and smooth muscle cellular elements from the neuropil due to degeneration and loss of arteriolar perivascular astrocytes. Development of this pathology was associated with vascular remodeling and neuroinflammation as increased levels of matrix metalloproteinases (MMP-2 and MMP-9), collagen type IV loss, and microglial activation were observed in the affected vasculature. Blast-induced chronic alterations within the neurovascular unit should affect cerebral blood circulation, glymphatic flow and intramural periarterial drainage, all of which may contribute to development of the blast-induced behavioral phenotype. Our results also identify astrocytic degeneration as a potential target for the development of therapies to treat blast-induced brain injury.

Low-level blast exposure disrupts gliovascular and neurovascular connections and induces a chronic vascular pathology in rat brain.

Much concern exists over the role of blast-induced traumatic brain injury (TBI) in the chronic cognitive and mental health problems that develop in veterans and active duty military personnel. The brain vasculature is particularly sensitive to blast injury. The aim of this study was to characterize the evolving molecular and histologic alterations in the neurovascular unit induced by three repetitive low-energy blast exposures (3 × 74.5 kPa) in a rat model mimicking human mild TBI or subclinical blast exposure. High-resolution two-dimensional differential gel electrophoresis (2D-DIGE) and matrix-assisted laser desorption/ionization (MALDI) mass spectrometry of purified brain vascular fractions from blast-exposed animals 6 weeks post-exposure showed decreased levels of vascular-associated glial fibrillary acidic protein (GFAP) and several neuronal intermediate filament proteins (α-internexin and the low, middle, and high molecular weight neurofilament subunits). Loss of these proteins suggested that blast exposure disrupts gliovascular and neurovascular interactions. Electron microscopy confirmed blast-induced effects on perivascular astrocytes including swelling and degeneration of astrocytic endfeet in the brain cortical vasculature. Because the astrocyte is a major sensor of neuronal activity and regulator of cerebral blood flow, structural disruption of gliovascular integrity within the neurovascular unit should impair cerebral autoregulation. Disrupted neurovascular connections to pial and parenchymal blood vessels might also affect brain circulation. Blast exposures also induced structural and functional alterations in the arterial smooth muscle layer. Interestingly, by 8 months after blast exposure, GFAP and neuronal intermediate filament expression had recovered to control levels in isolated brain vascular fractions. However, despite this recovery, a widespread vascular pathology was still apparent at 10 months after blast exposure histologically and on micro-computed tomography scanning. Thus, low-level blast exposure disrupts gliovascular and neurovascular connections while inducing a chronic vascular pathology.

Automatic navigation system for the mouse brain.

Identification and delineation of brain regions in histologic mouse brain sections is especially pivotal for many neurogenomics, transcriptomics, proteomics, and connectomics studies, yet this process is prone to observer error and bias. Here we present a novel brain navigation system, named NeuroInfo, whose general principle is similar to that of a global positioning system (GPS) in a car. NeuroInfo automatically navigates an investigator through the complex microscopic anatomy of histologic sections of mouse brains (thereafter: "experimental mouse brain sections"). This is achieved by automatically registering a digital image of an experimental mouse brain section with a three-dimensional (3D) digital mouse brain atlas that is essentially based on the third version of the Allen Mouse Brain Common Coordinate Framework (CCF v3), retrieving graphical region delineations and annotations from the 3D digital mouse brain atlas, and superimposing this information onto the digital image of the experimental mouse brain section on a computer screen. By doing so, NeuroInfo helps in solving the long-standing problem faced by researchers investigating experimental mouse brain sections under a light microscope-that of correctly identifying the distinct brain regions contained within the experimental mouse brain sections. Specifically, NeuroInfo provides an intuitive, readily-available computer microscopy tool to enhance researchers' ability to correctly identify specific brain regions in experimental mouse brain sections. Extensive validation studies of NeuroInfo demonstrated that this novel technology performs remarkably well in accurately delineating regions that are large and/or located in the dorsal parts of mouse brains, independent on whether the sections were imaged with fluorescence or bright-field microscopy. This novel navigation system provides a highly efficient way for registering a digital image of an experimental mouse brain section with the 3D digital mouse brain atlas in a minute and accurate delineation of the image in real-time.

Automatic Dendritic Spine Quantification from Confocal Data with Neurolucida 360.

Determining the density and morphology of dendritic spines is of high biological significance given the role of spines in synaptic plasticity and in neurodegenerative and neuropsychiatric disorders. Precise quantification of spines in three dimensions (3D) is essential for understanding the structural determinants of normal and pathological neuronal function. However, this quantification has been restricted to time- and labor-intensive methods such as electron microscopy and manual counting, which have limited throughput and are impractical for studies of large samples. While there have been some automated software packages that quantify spine number, they are limited in terms of their characterization of spine structure. This unit presents methods for objective dendritic spine morphometric analysis by providing image acquisition parameters needed to ensure optimal data series for proper spine detection, characterization, and quantification with Neurolucida 360. These protocols will be a valuable reference for scientists working towards quantifying and characterizing spines. © 2016 by John Wiley & Sons, Inc.

Current automated 3D cell detection methods are not a suitable replacement for manual stereologic cell counting.

Stereologic cell counting has had a major impact on the field of neuroscience. A major bottleneck in stereologic cell counting is that the user must manually decide whether or not each cell is counted according to three-dimensional (3D) stereologic counting rules by visual inspection within hundreds of microscopic fields-of-view per investigated brain or brain region. Reliance on visual inspection forces stereologic cell counting to be very labor-intensive and time-consuming, and is the main reason why biased, non-stereologic two-dimensional (2D) "cell counting" approaches have remained in widespread use. We present an evaluation of the performance of modern automated cell detection and segmentation algorithms as a potential alternative to the manual approach in stereologic cell counting. The image data used in this study were 3D microscopic images of thick brain tissue sections prepared with a variety of commonly used nuclear and cytoplasmic stains. The evaluation compared the numbers and locations of cells identified unambiguously and counted exhaustively by an expert observer with those found by three automated 3D cell detection algorithms: nuclei segmentation from the FARSIGHT toolkit, nuclei segmentation by 3D multiple level set methods, and the 3D object counter plug-in for ImageJ. Of these methods, FARSIGHT performed best, with true-positive detection rates between 38 and 99% and false-positive rates from 3.6 to 82%. The results demonstrate that the current automated methods suffer from lower detection rates and higher false-positive rates than are acceptable for obtaining valid estimates of cell numbers. Thus, at present, stereologic cell counting with manual decision for object inclusion according to unbiased stereologic counting rules remains the only adequate method for unbiased cell quantification in histologic tissue sections.

Robust tracking and quantification of C. elegans body shape and locomotion through coiling, entanglement, and omega bends.

The behavior of the well-characterized nematode, Caenorhabditis elegans (C. elegans), is often used to study the neurologic control of sensory and motor systems in models of health and neurodegenerative disease. To advance the quantification of behaviors to match the progress made in the breakthroughs of genetics, RNA, proteins, and neuronal circuitry, analysis must be able to extract subtle changes in worm locomotion across a population. The analysis of worm crawling motion is complex due to self-overlap, coiling, and entanglement. Using current techniques, the scope of the analysis is typically restricted to worms to their non-occluded, uncoiled state which is incomplete and fundamentally biased. Using a model describing the worm shape and crawling motion, we designed a deformable shape estimation algorithm that is robust to coiling and entanglement. This model-based shape estimation algorithm has been incorporated into a framework where multiple worms can be automatically detected and tracked simultaneously throughout the entire video sequence, thereby increasing throughput as well as data validity. The newly developed algorithms were validated against 10 manually labeled datasets obtained from video sequences comprised of various image resolutions and video frame rates. The data presented demonstrate that tracking methods incorporated in WormLab enable stable and accurate detection of these worms through coiling and entanglement. Such challenging tracking scenarios are common occurrences during normal worm locomotion. The ability for the described approach to provide stable and accurate detection of C. elegans is critical to achieve unbiased locomotory analysis of worm motion.