PKC-β exacerbates in vitro brain barrier damage in hyperglycemic settings via regulation of RhoA/Rho-kinase/MLC2 pathway

Stroke patients with hyperglycemia (HG) develop higher volumes of brain edema emerging from disruption of blood-brain barrier (BBB). This study explored whether inductions of protein kinase C-β (PKC-β) and RhoA/Rho-kinase/myosin-regulatory light chain-2 (MLC2) pathway may account for HG-induced barrier damage using an in vitro model of human BBB comprising human brain microvascular endothelial cells (HBMEC) and astrocytes. Hyperglycemia (25 mmol/L D-glucose) markedly increased RhoA/Rho-kinase protein expressions (in-cell westerns), MLC2 phosphorylation (immunoblotting), and PKC-β (PepTag assay) and RhoA (Rhotekin-binding assay) activities in HBMEC while concurrently reducing the expression of tight junction protein occludin. Hyperglycemia-evoked in vitro barrier dysfunction, confirmed by decreases in transendothelial electrical resistance and concomitant increases in paracellular flux of Evan's blue-labeled albumin, was accompanied by malformations of actin cytoskeleton and tight junctions. Suppression of RhoA and Rho-kinase activities by anti-RhoA immunoglobulin G (IgG) electroporation and Y-27632, respectively prevented morphologic changes and restored plasma membrane localization of occludin. Normalization of glucose levels and silencing PKC-β activity neutralized the effects of HG on occludin and RhoA/Rho-kinase/MLC2 expression, localization, and activity and consequently improved in vitro barrier integrity and function. These results suggest that HG-induced exacerbation of the BBB breakdown after an ischemic stroke is mediated in large part by activation of PKC-β.

Abnormal Functional Connectivity of Hippocampus During Episodic Memory Retrieval Processing Network in Amnestic Mild Cognitive Impairment.

BACKGROUND: Functional connectivity magnetic resonance imaging technique has revealed the importance of distributed network structures in higher cognitive processes in the human brain. The hippocampus has a key role in a distributed network supporting memory encoding and retrieval. Hippocampal dysfunction is a recurrent finding in memory disorders of aging such as amnestic mild cognitive impairment (aMCI) in which learning- and memory-related cognitive abilities are the predominant impairment. The functional connectivity method provides a novel approach in our attempts to better understand the changes occurring in this structure in aMCI patients. METHODS: Functional connectivity analysis was used to examine episodic memory retrieval networks in vivo in twenty 28 aMCI patients and 23 well-matched control subjects, specifically between the hippocampal structures and other brain regions. RESULTS: Compared with control subjects, aMCI patients showed significantly lower hippocampus functional connectivity in a network involving prefrontal lobe, temporal lobe, parietal lobe, and cerebellum, and higher functional connectivity to more diffuse areas of the brain than normal aging control subjects. In addition, those regions associated with increased functional connectivity with the hippocampus demonstrated a significantly negative correlation to episodic memory performance. CONCLUSIONS: aMCI patients displayed altered patterns of functional connectivity during memory retrieval. The degree of this disturbance appears to be related to level of impairment of processes involved in memory function. Because aMCI is a putative prodromal syndrome to Alzheimer's disease (AD), these early changes in functional connectivity involving the hippocampus may yield important new data to predict whether a patient will eventually develop AD.

Imaging the genetics of executive function

Recent advances in neuroimaging technologies have allowed ever more detailed studies of the human brain. The combination of neuroimaging techniques with genetics may provide a more sensitive measure of the influence of genetic variants on cognitive function than behavioural measures alone. Here we present a review of functional magnetic resonance imaging (fMRI) studies of genetic links to executive functions, focusing on sustained attention, working memory and response inhibition. In addition to studies in the normal population, we also address findings from three clinical populations: schizophrenia, ADHD and autism spectrum disorders. While the findings in the populations studied do not always converge, they all point to the usefulness of neuroimaging techniques such as fMRI as potential endophenotypes for parsing the genetic aetiology of executive function. (C) 2007 Elsevier B.V. All rights reserved.

Monkey and humans exhibit similar motion-processing mechanisms

Single cell recording studies have resulted in a detailed understanding of motion-sensitive neurons in non-human primate visual cortex. However, it is not known to what extent response properties of motion-sensitive neurons in the non-human primate brain mirror response characteristics of motion-sensitive neurons in the human brain. Using a motion adaptation paradigm, the direction aftereffect, we show that changes in the activity of human motion-sensitive neurons to moving dot patterns that differ in dot density bear a strong resemblance to data from macaque monkey. We also show a division-like inhibition between neural populations tuned to opposite directions, which also mirrors neural-inhibitory behaviour in macaque. These findings strongly suggest that motion-sensitive neurons in human and non-human primates share common response and inhibitory characteristics.

Intercepting the First Pass:Rapid Categorization is Suppressed for Unseen Stimuli

The operations and processes that the human brain employs to achieve fast visual categorization remain a matter of debate. A first issue concerns the timing and place of rapid visual categorization and to what extent it can be performed with an early feed-forward pass of information through the visual system. A second issue involves the categorization of stimuli that do not reach visual awareness. There is disagreement over the degree to which these stimuli activate the same early mechanisms as stimuli that are consciously perceived. We employed continuous flash suppression (CFS), EEG recordings, and machine learning techniques to study visual categorization of seen and unseen stimuli. Our classifiers were able to predict from the EEG recordings the category of stimuli on seen trials but not on unseen trials. Rapid categorization of conscious images could be detected around 100?ms on the occipital electrodes, consistent with a fast, feed-forward mechanism of target detection. For the invisible stimuli, however, CFS eliminated all traces of early processing. Our results support the idea of a fast mechanism of categorization and suggest that this early categorization process plays an important role in later, more subtle categorizations, and perceptual processes.

Algorithms for Self-Healing Networks

Many modern networks are \emph{reconfigurable}, in the sense that the topology of the network can be changed by the nodes in the network. For example, peer-to-peer, wireless and ad-hoc networks are reconfigurable. More generally, many social networks, such as a company's organizational chart; infrastructure networks, such as an airline's transportation network; and biological networks, such as the human brain, are also reconfigurable. Modern reconfigurable networks have a complexity unprecedented in the history of engineering, resembling more a dynamic and evolving living animal rather than a structure of steel designed from a blueprint. Unfortunately, our mathematical and algorithmic tools have not yet developed enough to handle this complexity and fully exploit the flexibility of these networks. We believe that it is no longer possible to build networks that are scalable and never have node failures. Instead, these networks should be able to admit small, and maybe, periodic failures and still recover like skin heals from a cut. This process, where the network can recover itself by maintaining key invariants in response to attack by a powerful adversary is what we call \emph{self-healing}. Here, we present several fast and provably good distributed algorithms for self-healing in reconfigurable dynamic networks. Each of these algorithms have different properties, a different set of gaurantees and limitations. We also discuss future directions and theoretical questions we would like to answer. %in the final dissertation that this document is proposed to lead to.

Use of SLAM and PVRL4 and Identification of Pro-HB-EGF as Cell Entry Receptors for Wild Type Phocine Distemper Virus

Signalling lymphocyte activation molecule (SLAM) has been identified as an immune cell receptor for the morbilliviruses, measles (MV), canine distemper (CDV), rinderpest and peste des petits ruminants (PPRV) viruses, while CD46 is a receptor for vaccine strains of MV. More recently poliovirus like receptor 4 (PVRL4), also known as nectin 4, has been identified as a receptor for MV, CDV and PPRV on the basolateral surface of polarised epithelial cells. PVRL4 is also up-regulated by MV in human brain endothelial cells. Utilisation of PVRL4 as a receptor by phocine distemper virus (PDV) remains to be demonstrated as well as confirmation of use of SLAM. We have observed that unlike wild type (wt) MV or wtCDV, wtPDV strains replicate in African green monkey kidney Vero cells without prior adaptation, suggesting the use of a further receptor. We therefore examined candidate molecules, glycosaminoglycans (GAG) and the tetraspan proteins, integrin β and the membrane bound form of heparin binding epithelial growth factor (proHB-EGF),for receptor usage by wtPDV in Vero cells. We show that wtPDV replicates in Chinese hamster ovary (CHO) cells expressing SLAM and PVRL4. Similar wtPDV titres are produced in Vero and VeroSLAM cells but more limited fusion occurs in the latter. Infection of Vero cells was not inhibited by anti-CD46 antibody. Removal/disruption of GAG decreased fusion but not the titre of virus. Treatment with anti-integrin β antibody increased rather than decreased infection of Vero cells by wtPDV. However, infection was inhibited by antibody to HB-EGF and the virus replicated in CHO-proHB-EGF cells, indicating use of this molecule as a receptor. Common use of SLAM and PVRL4 by morbilliviruses increases the possibility of cross-species infection. Lack of a requirement for wtPDV adaptation to Vero cells raises the possibility of usage of proHB-EGF as a receptor in vivo but requires further investigation.

Attenuation of urokinase activity during experimental ischaemia protects the cerebral barrier from damage through regulation of matrix metalloproteinase-2 and NAD(P)H oxidase

Ischaemic injury impairs the integrity of the blood-brain barrier (BBB). In this study, we investigated the molecular causes of this defect with regard to the putative correlations among NAD(P)H oxidase, plasminogen-plasmin system components, and matrix metalloproteinases. Hence, the activities of NAD(P)H oxidase, matrix metalloproteinase-2, urokinase-type plasminogen activator (uPA), and tissue-type plasminogen activator (tPA), and superoxide anion levels, were assessed in human brain microvascular endothelial cells (HBMECs) exposed to oxygen-glucose deprivation (OGD) alone or OGD followed by reperfusion (OGD + R). The integrity of an in vitro model of BBB comprising HBMECs and astrocytes was studied by measuring transendothelial electrical resistance and the paracellular flux of albumin. OGD with or without reperfusion (OGD ± R) radically perturbed barrier function while concurrently enhancing uPA, tPA and NAD(P)H oxidase activities and superoxide anion release in HBMECs. Pharmacological inactivation of NAD(P)H oxidase attenuated OGD ± R-mediated BBB damage through modulation of matrix metalloproteinase-2 and tPA, but not uPA activity. Overactivation of NAD(P)H oxidase in HBMECs via cDNA electroporation of its p22-phox subunit confirmed the involvement of tPA in oxidase-mediated BBB disruption. Interestingly, blockade of uPA or uPA receptor preserved normal BBB function by neutralizing both NAD(P)H oxidase and matrix metalloproteinase-2 activities. Hence, selective targeting of uPA after ischaemic strokes may protect cerebral barrier integrity and function by concomitantly attenuating basement membrane degradation and oxidative stress.

Small GTPase RhoA and its effector rho kinase mediate oxygen glucose deprivation-evoked in vitro cerebral barrier dysfunction

BACKGROUND AND PURPOSE: Enhanced vascular permeability attributable to disruption of blood-brain barrier results in the development of cerebral edema after stroke. Using an in vitro model of the brain barrier composed of human brain microvascular endothelial cells and human astrocytes, this study explored whether small GTPase RhoA and its effector protein Rho kinase were involved in permeability changes mediated by oxygen-glucose deprivation (OGD), key pathological phenomena during ischemic stroke.

METHODS: OGD increased RhoA and Rho kinase protein expressions in human brain microvascular endothelial cells and human astrocytes while increasing or unaffecting that of endothelial nitric oxide synthase in respective cells. Reperfusion attenuated the expression and activity of RhoA and Rho kinase in both cell types compared to their counterparts exposed to equal periods of OGD alone while selectively increasing human brain microvascular endothelial cells endothelial nitric oxide synthase protein levels. OGD compromised the barrier integrity as confirmed by decreases in transendothelial electric resistance and concomitant increases in flux of permeability markers sodium fluorescein and Evan's blue albumin across cocultures. Transfection of cells with constitutively active RhoA also increased flux and reduced transendothelial electric resistance, whereas inactivation of RhoA by anti-RhoA Ig electroporation exerted opposite effects. In vitro cerebral barrier dysfunction was accompanied by myosin light chain overphosphorylation and stress fiber formation. Reperfusion and treatments with a Rho kinase inhibitor Y-27632 significantly attenuated barrier breakdown without profoundly altering actin structure.

CONCLUSIONS: Increased RhoA/Rho kinase/myosin light chain pathway activity coupled with changes in actin cytoskeleton account for OGD-induced endothelial barrier breakdown.

Turbo-smt: Accelerating coupled sparse matrix-tensor factorizations by 200x

How can we correlate the neural activity in the human brain as it responds to typed words, with properties of these terms (like ‘edible’, ‘fits in hand’)? In short, we want to find latent variables, that jointly explain both the brain activity, as well as the behavioral responses. This is one of many settings of the Coupled Matrix-Tensor Factorization (CMTF) problem.

Can we accelerate any CMTF solver, so that it runs within a few minutes instead of tens of hours to a day, while maintaining good accuracy? We introduce Turbo-SMT, a meta-method capable of doing exactly that: it boosts the performance of any CMTF algorithm, by up to 200x, along with an up to 65 fold increase in sparsity, with comparable accuracy to the baseline.

We apply Turbo-SMT to BrainQ, a dataset consisting of a (nouns, brain voxels, human subjects) tensor and a (nouns, properties) matrix, with coupling along the nouns dimension. Turbo-SMT is able to find meaningful latent variables, as well as to predict brain activity with competitive accuracy.

Convergent genetic and expression data implicate immunity in Alzheimer's disease

Background: Late-onset Alzheimer's disease (AD) is heritable with 20 genes showing genome-wide association in the International Genomics of Alzheimer's Project (IGAP). To identify the biology underlying the disease, we extended these genetic data in a pathway analysis.

Methods: The ALIGATOR and GSEA algorithms were used in the IGAP data to identify associated functional pathways and correlated gene expression networks in human brain.

Results: ALIGATOR identified an excess of curated biological pathways showing enrichment of association. Enriched areas of biology included the immune response (P = 3.27 X 10(-12) after multiple testing correction for pathways), regulation of endocytosis (P = 1.31 X 10(-11)), cholesterol transport (P = 2.96 X 10(-9)), and proteasome-ubiquitin activity (P = 1.34 X 10(-6)). Correlated gene expression analysis identified four significant network modules, all related to the immune response (corrected P = .002-.05).

Conclusions: The immime response, regulation of endocytosis, cholesterol transport, and protein ubiquitination represent prime targets for AD therapeutics. (C) 2015 Published by Elsevier Inc. on behalf of The Alzheimer's Association.

Using Graph Components Derived from an Associative Concept Dictionary to Predict fMRI Neural Activation Patterns that Represent the Meaning of Nouns

In this study, we introduce an original distance definition for graphs, called the Markov-inverse-F measure (MiF). This measure enables the integration of classical graph theory indices with new knowledge pertaining to structural feature extraction from semantic networks. MiF improves the conventional Jaccard and/or Simpson indices, and reconciles both the geodesic information (random walk) and co-occurrence adjustment (degree balance and distribution). We measure the effectiveness of graph-based coefficients through the application of linguistic graph information for a neural activity recorded during conceptual processing in the human brain. Specifically, the MiF distance is computed between each of the nouns used in a previous neural experiment and each of the in-between words in a subgraph derived from the Edinburgh Word Association Thesaurus of English. From the MiF-based information matrix, a machine learning model can accurately obtain a scalar parameter that specifies the degree to which each voxel in (the MRI image of) the brain is activated by each word or each principal component of the intermediate semantic features. Furthermore, correlating the voxel information with the MiF-based principal components, a new computational neurolinguistics model with a network connectivity paradigm is created. This allows two dimensions of context space to be incorporated with both semantic and neural distributional representations.

Scoup-SMT: Scalable Coupled Sparse Matrix-Tensor Factorization

How can we correlate neural activity in the human brain as it responds to words, with behavioral data expressed as answers to questions about these same words? In short, we want to find latent variables, that explain both the brain activity, as well as the behavioral responses. We show that this is an instance of the Coupled Matrix-Tensor Factorization (CMTF) problem. We propose Scoup-SMT, a novel, fast, and parallel algorithm that solves the CMTF problem and produces a sparse latent low-rank subspace of the data. In our experiments, we find that Scoup-SMT is 50-100 times faster than a state-of-the-art algorithm for CMTF, along with a 5 fold increase in sparsity. Moreover, we extend Scoup-SMT to handle missing data without degradation of performance. We apply Scoup-SMT to BrainQ, a dataset consisting of a (nouns, brain voxels, human subjects) tensor and a (nouns, properties) matrix, with coupling along the nouns dimension. Scoup-SMT is able to find meaningful latent variables, as well as to predict brain activity with competitive accuracy. Finally, we demonstrate the generality of Scoup-SMT, by applying it on a Facebook dataset (users, friends, wall-postings); there, Scoup-SMT spots spammer-like anomalies.

Metabolic signatures of human Alzheimer's disease (AD): H-1 NMR analysis of the polar metabolome of post-mortem brain tissue

Brain tissue from so-called Alzheimer's disease (AD) mouse models has previously been examined using H-1 NMR-metabolomics, but comparable information concerning human AD is negligible. Since no animal model recapitulates all the features of human AD we undertook the first H-1 NMR-metabolomics investigation of human AD brain tissue. Human post-mortem tissue from 15 AD subjects and 15 age-matched controls was prepared for analysis through a series of lyophilised, milling, extraction and randomisation steps and samples were analysed using H-1 NMR. Using partial least squares discriminant analysis, a model was built using data obtained from brain extracts. Analysis of brain extracts led to the elucidation of 24 metabolites. Significant elevations in brain alanine (15.4 %) and taurine (18.9 %) were observed in AD patients (p ≤ 0.05). Pathway topology analysis implicated either dysregulation of taurine and hypotaurine metabolism or alanine, aspartate and glutamate metabolism. Furthermore, screening of metabolites for AD biomarkers demonstrated that individual metabolites weakly discriminated cases of AD [receiver operating characteristic (ROC) AUC <0.67; p < 0.05]. However, paired metabolites ratios (e.g. alanine/carnitine) were more powerful discriminating tools (ROC AUC = 0.76; p < 0.01). This study further demonstrates the potential of metabolomics for elucidating the underlying biochemistry and to help identify AD in patients attending the memory clinic