Faculty Bibliography

BACKGROUND: The choroid plexuses are the interface between the blood and the cerebrospinal fluid (CSF) contained within the ventricular spaces of the central nervous system. The tight junctions linking adjacent cells of the choroidal epithelium create a physical barrier to paracellular movement of molecules. Multispecific efflux transporters as well as drug-metabolizing and antioxidant enzymes functioning in these cells contribute to a metabolic barrier. These barrier properties reflect a neuroprotective function of the choroid plexus. The choroid plexuses develop early during embryogenesis and provide pivotal control of the internal environment throughout development when the brain is especially vulnerable to toxic insults. Perinatal injuries like hypoxia and trauma, and exposure to drugs or toxic xenobiotics can have serious consequences on neurogenesis and long-term development. The present study describes the developmental expression pattern of genes involved in the neuroprotective functions of the blood-CSF barrier. METHODS: The transcriptome of rat lateral ventricular choroid plexuses isolated from fifteen-day-old embryos, nineteen-day old fetuses, two-day old pups, and adults was analyzed by a combination of Affymetrix microarrays, Illumina RNA-Sequencing, and quantitative RT-PCR. RESULTS: Genes coding for proteins involved in junction formation are expressed early during development. Overall perinatal expression levels of genes involved in drug metabolism and antioxidant mechanisms are similar to, or higher than levels measured in adults. A similar developmental pattern was observed for multispecific efflux transporter genes of the Abc and Slc superfamilies. Expression of all these genes was more variable in choroid plexus from fifteen-day-old embryos. A large panel of transcription factors involved in the xenobiotic- or cell stress-mediated induction of detoxifying enzymes and transporters is also expressed throughout development. CONCLUSIONS: This transcriptomic analysis suggests relatively well-established neuroprotective mechanisms at the blood-CSF barrier throughout development of the rat. The expression of many transcription factors early in development raises the possibility of additional protection for the vulnerable developing brain, should the fetus or newborn be exposed to drugs or other xenobiotics.

For a long time the brain has been considered an immune-privileged site due to a muted inflammatory response and the presence of protective brain barriers. It is now recognized that neuroinflammation may play an important role in almost all neurological disorders and that the brain barriers may be contributing through either normal immune signaling or disruption of their basic physiological mechanisms. The distinction between normal function and dysfunction at the barriers is difficult to dissect, partly due to a lack of understanding of normal barrier function and partly because of physiological changes that occur as part of normal development and ageing. Brain barriers consist of a number of interacting structural and physiological elements including tight junctions between adjacent barrier cells and an array of influx and efflux transporters. Despite these protective mechanisms, the capacity for immune-surveillance of the brain is maintained, and there is evidence of inflammatory signaling at the brain barriers that may be an important part of the body's response to damage or infection. This signaling system appears to change both with normal ageing, and during disease. Changes may affect diapedesis of immune cells and active molecular transfer, or cause rearrangement of the tight junctions and an increase in passive permeability across barrier interfaces. Here we review the many elements that contribute to brain barrier functions and how they respond to inflammation, particularly during development and aging. The implications of inflammation-induced barrier dysfunction for brain development and subsequent neurological function are also discussed.

Neural spike train analysis is an important task in computational neuroscience which aims to understand neural mechanisms and gain insights into neural circuits. With the advancement of multielectrode recording and imaging technologies, it has become increasingly demanding to develop statistical tools for analyzing large neuronal ensemble spike activity. Here we present a tutorial overview of Bayesian methods and their representative applications in neural spike train analysis, at both single neuron and population levels. On the theoretical side, we focus on various approximate Bayesian inference techniques as applied to latent state and parameter estimation. On the application side, the topics include spike sorting, tuning curve estimation, neural encoding and decoding, deconvolution of spike trains from calcium imaging signals, and inference of neuronal functional connectivity and synchrony. Some research challenges and opportunities for neural spike train analysis are discussed.

The purpose of this study is to determine the accuracy with which a non-Gaussian measure of diffusion, mean kurtosis (MK), predicts the histologic grade of pediatric brain tumors. After institutional review board approval, 21 World Health Organization (WHO) grade I, 7 WHO grade II, and 7 WHO grade IV pathologically-proven intracranial pediatric malignancies were retrospectively reviewed for preoperative diffusional kurtosis imaging. Multiple diffusion metrics of the tumors including MK, mean diffusivity (MD) and fractional anisotropy (FA) were determined. Comparisons between groups were performed using the Mann-Whitney test (p < .05). Receiver operating characteristics analysis was done to assess accuracy of each metric in predicting histologic grade. MK was significantly higher for grade IV neoplasms (0.97, p < 0.0004) than grade I (0.62) or grade II (0.67) tumors. MD was significantly higher for grade I (1.43) compared with grade IV neoplasms (1.07, p < 0.018), however not for grade II (1.43) compared with grade IV (p < 0.08) tumors. FA did not differ significantly between grades. Area under the receiver operating characteristic curve was highest for MK (0.94) and lower for MD (0.89). FA performed only slightly better than chance (0.54). MK is an accurate diffusion metric for predicting histologic grade of pediatric brain tumors, consistent with conclusions from prior studies demonstrating similar results in adult populations

Multiphoton microscopy is a powerful imaging modality that enables structural and functional imaging with cellular and sub-cellular resolution, deep within biological tissues. Yet, its main contrast mechanism relies on extrinsically administered fluorescent indicators. Here we developed a system for simultaneous multimodal optoacoustic and multiphoton fluorescence 3D imaging, which attains both absorption and fluorescence-based contrast by integrating an ultrasonic transducer into a two-photon laser scanning microscope. The system is readily shown to enable acquisition of multimodal microscopic images of fluorescently labeled targets and cell cultures as well as intrinsic absorption-based images of pigmented biological tissue. During initial experiments, it was further observed that that detected optoacoustically-induced response contains low frequency signal variations, presumably due to cavitation-mediated signal generation by the high repetition rate (80MHz) near IR femtosecond laser. The multimodal system may provide complementary structural and functional information to the fluorescently labeled tissue, by superimposing optoacoustic images of intrinsic tissue chromophores, such as melanin deposits, pigmentation, and hemoglobin or other extrinsic particle or dye-based markers highly absorptive in the NIR spectrum.

Parallel excitation and 'light-sheet' optical methods, such as multifocal multiphoton microscopy, selective plane illumination microscopy, and temporal focusing microscopy offer significant enhancement of data acquisition rates compared to the relabtively slow serial-scanning rate of two photon laser scanning microscopy (TPLSM). However, since these methods typically rely on detecting the fluorescence signal using a camera, they are sensitive to tissue scattering effects, which blur the images, reduce the spatial resolution, and eventually limit the maximal imaging depth. Therefore, an efficient method for de-scattering of the acquired data is needed in order to maximize parallel excitation methods' utility for imaging neuronal activity inside tissues. Here, we present a simple algorithmic approach for data extraction from blurred images acquired by a dual-modality microscope, which offers additional information regarding the cells' geometrical location. Simulations predict that the new approach is capable of extracting functional information for depths that may potentially exceed 700 mu m in cortical tissues, even in the presence of severe additive noise corruption.