Ammonia produces pathological changes in human hepatic stellate cells and is a target for therapy of portal hypertension

BACKGROUND AND AIMS: Hepatic stellate cells (HSCs) are vital to hepatocellular function and the liver response to injury. They share a phenotypic homology with astrocytes that are central in the pathogenesis of hepatic encephalopathy, a condition in which hyperammonemia plays a pathogenic role. This study tested the hypothesis that ammonia modulates human HSC activation in vitro and in vivo, and evaluated whether ammonia lowering, by using l-ornithine phenylacetate (OP), modifies HSC activation in vivo and reduces portal pressure in a bile duct ligation (BDL) model. METHODS: Primary human HSCs were isolated and cultured. Proliferation (BrdU), metabolic activity (MTS), morphology (transmission electron, light and immunofluorescence microscopy), HSC activation markers, ability to contract, changes in oxidative status (ROS) and endoplasmic reticulum (ER) were evaluated to identify effects of ammonia challenge (50 μM, 100 μM, 300 μM) over 24–72 h. Changes in plasma ammonia levels, markers of HSC activation, portal pressure and hepatic eNOS activity were quantified in hyperammonemic BDL animals, and after OP treatment. RESULTS: Pathophysiological ammonia concentrations caused significant and reversible changes in cell proliferation, metabolic activity and activation markers of hHSC in vitro. Ammonia also induced significant alterations in cellular morphology, characterised by cytoplasmic vacuolisation, ER enlargement, ROS production, hHSC contraction and changes in pro-inflammatory gene expression together with HSC-related activation markers such as α-SMA, myosin IIa, IIb, and PDGF-Rβ. Treatment with OP significantly reduced plasma ammonia (BDL 199.1 μmol/L ± 43.65 vs. BDL + OP 149.27 μmol/L ± 51.1, p <0.05) and portal pressure (BDL 14 ± 0.6 vs. BDL + OP 11 ± 0.3 mmHg, p <0.01), which was associated with increased eNOS activity and abrogation of HSC activation markers. CONCLUSIONS: The results show for the first time that ammonia produces deleterious morphological and functional effects on HSCs in vitro. Targeting ammonia with the ammonia lowering drug OP reduces portal pressure and deactivates hHSC in vivo, highlighting the opportunity for evaluating ammonia lowering as a potential therapy in cirrhotic patients with portal hypertension

Listen to genes : dealing with microarray data in the frequency domain

Background: We present a novel and systematic approach to analyze temporal microarray data. The approach includes normalization, clustering and network analysis of genes. Methodology: Genes are normalized using an error model based uniform normalization method aimed at identifying and estimating the sources of variations. The model minimizes the correlation among error terms across replicates. The normalized gene expressions are then clustered in terms of their power spectrum density. The method of complex Granger causality is introduced to reveal interactions between sets of genes. Complex Granger causality along with partial Granger causality is applied in both time and frequency domains to selected as well as all the genes to reveal the interesting networks of interactions. The approach is successfully applied to Arabidopsis leaf microarray data generated from 31,000 genes observed over 22 time points over 22 days. Three circuits: a circadian gene circuit, an ethylene circuit and a new global circuit showing a hierarchical structure to determine the initiators of leaf senescence are analyzed in detail. Conclusions: We use a totally data-driven approach to form biological hypothesis. Clustering using the power-spectrum analysis helps us identify genes of potential interest. Their dynamics can be captured accurately in the time and frequency domain using the methods of complex and partial Granger causality. With the rise in availability of temporal microarray data, such methods can be useful tools in uncovering the hidden biological interactions. We show our method in a step by step manner with help of toy models as well as a real biological dataset. We also analyse three distinct gene circuits of potential interest to Arabidopsis researchers

Role of CYP27A in cholesterol and bile acid metabolism

The CYP27A gene encodes a mitochondrial cytochrome P450 enzyme, sterol 27-hydroxylase, that is expressed in many different tissues and plays an important role in cholesterol and bile acid metabolism. In humans, CYP27A deficiency leads to cerebrotendinous xanthomatosis. To gain insight into the roles of CYP27A in the regulation of cholesterol and bile acid metabolism, cyp27A gene knockout heterozygous, homozygous, and wild-type littermate mice were studied. In contrast to homozygotes, heterozygotes had increased body weight and were mildly hypercholesterolemic, with increased numbers of lipoprotein particles in the low density lipoprotein size range. Cyp7A expression was not increased in heterozygotes but was in homozygotes, suggesting that parts of the homozygous phenotype are secondary to increased cyp7A expression and activity. Homozygotes exhibited pronounced hepatomegaly and dysregulation in hepatic cholesterol, bile acid, and fatty acid metabolism. Hepatic cholesterol synthesis and synthesis of bile acid intermediates were increased; however, side chain cleavage was impaired, leading to decreased bile salt concentrations in gallbladder bile. Expression of Na-taurocholate cotransporting polypeptide, the major sinusoidal bile salt transporter, was increased, and that of bile salt export pump, the major canalicular bile salt transporter, was decreased. Gender played a modifying role in the homozygous response to cyp27A deficiency, with females being gen

A biclustering algorithm based on a Bicluster Enumeration Tree: application to DNA microarray data

<p>Abstract</p> <p>Background</p> <p>In a number of domains, like in DNA microarray data analysis, we need to cluster simultaneously rows (genes) and columns (conditions) of a data matrix to identify groups of rows coherent with groups of columns. This kind of clustering is called <it>biclustering</it>. Biclustering algorithms are extensively used in DNA microarray data analysis. More effective biclustering algorithms are highly desirable and needed.</p> <p>Methods</p> <p>We introduce <it>BiMine</it>, a new enumeration algorithm for biclustering of DNA microarray data. The proposed algorithm is based on three original features. First, <it>BiMine </it>relies on a new evaluation function called <it>Average Spearman's rho </it>(ASR). Second, <it>BiMine </it>uses a new tree structure, called <it>Bicluster Enumeration Tree </it>(BET), to represent the different biclusters discovered during the enumeration process. Third, to avoid the combinatorial explosion of the search tree, <it>BiMine </it>introduces a parametric rule that allows the enumeration process to cut tree branches that cannot lead to good biclusters.</p> <p>Results</p> <p>The performance of the proposed algorithm is assessed using both synthetic and real DNA microarray data. The experimental results show that <it>BiMine </it>competes well with several other biclustering methods. Moreover, we test the biological significance using a gene annotation web-tool to show that our proposed method is able to produce biologically relevant biclusters. The software is available upon request from the authors to academic users.</p

Altering the trajectory of early postnatal cortical development can lead to structural and behavioural features of autism

<p>Abstract</p> <p>Background</p> <p>Autism is a behaviourally defined neurodevelopmental disorder with unknown etiology. Recent studies in autistic children consistently point to neuropathological and functional abnormalities in the temporal association cortex (TeA) and its associated structures. It has been proposed that the trajectory of postnatal development in these regions may undergo accelerated maturational alterations that predominantly affect sensory recognition and social interaction. Indeed, the temporal association regions that are important for sensory recognition and social interaction are one of the last regions to mature suggesting a potential vulnerability to early maturation. However, direct evaluation of the emerging hypothesis that an altered time course of early postnatal development can lead to an ASD phenotype remains lacking.</p> <p>Results</p> <p>We used electrophysiological, histological, and behavioural techniques to investigate if the known neuronal maturational promoter valproate, similar to that in culture systems, can influence the normal developmental trajectory of TeA <it>in vivo</it>. Brain sections obtained from postnatal rat pups treated with VPA <it>in vivo </it>revealed that almost 40% of cortical cells in TeA prematurely exhibited adult-like intrinsic electrophysiological properties and that this was often associated with gross cortical hypertrophy and a reduced predisposition for social play behaviour.</p> <p>Conclusions</p> <p>The co-manifestation of these functional, structural and behavioural features suggests that alteration of the developmental time course in certain high-order cortical networks may play an important role in the neurophysiological basis of autism.</p

Trichosanthes dioica root extract induces tumor proliferation and attenuation of antioxidant system in albino mice bearing Ehrlich ascites carcinoma

Trichosanthes dioica Roxb. (Cucurbitaceae), called pointed gourd in English, is a dioecious climber grown widely in the Indian subcontinent. The present study assessed the influence of treatment of hydroalcoholic extract of Trichosanthes dioica root (TDA) on Ehrlich ascites carcinoma (EAC) in Swiss albino mice with effects on antioxidant systems. Twenty-four hours after intraperitoneal inoculation of tumor (EAC) cells in mice, TDA was administered at 25 and 50 mg/kg for 8 consecutive days. On the 9th day, half of the mice were sacrificed for estimation of tumor proliferation, hematological, and hepatic antioxidative parameters. The rest were kept for assessment of survival parameters. TDA exhibited dose dependent and significant increase in tumor weight, tumor volume, packed cell volume and viable cells and reduced non-viable cells and life span of EAC bearing animals. Hematological parameters were significantly worsened in TDA-treated mice. TDA treatment significantly aggravated the hepatic antioxidative parameters. The present study demonstrated that T. dioica root possessed tumor promoting activity in EAC bearing albino mice, plausibly mediated by attenuation of endogenous antioxidant systems

Post hoc pattern matching: assigning significance to statistically defined expression patterns in single channel microarray data

<p>Abstract</p> <p>Background</p> <p>Researchers using RNA expression microarrays in experimental designs with more than two treatment groups often identify statistically significant genes with ANOVA approaches. However, the ANOVA test does not discriminate which of the multiple treatment groups differ from one another. Thus, <it>post hoc </it>tests, such as linear contrasts, template correlations, and pairwise comparisons are used. Linear contrasts and template correlations work extremely well, especially when the researcher has <it>a priori </it>information pointing to a particular pattern/template among the different treatment groups. Further, all pairwise comparisons can be used to identify particular, treatment group-dependent patterns of gene expression. However, these approaches are biased by the researcher's assumptions, and some treatment-based patterns may fail to be detected using these approaches. Finally, different patterns may have different probabilities of occurring by chance, importantly influencing researchers' conclusions about a pattern and its constituent genes.</p> <p>Results</p> <p>We developed a four step, <it>post hoc </it>pattern matching (PPM) algorithm to automate single channel gene expression pattern identification/significance. First, 1-Way Analysis of Variance (ANOVA), coupled with <it>post hoc </it>'all pairwise' comparisons are calculated for all genes. Second, for each ANOVA-significant gene, all pairwise contrast results are encoded to create unique pattern ID numbers. The # genes found in each pattern in the data is identified as that pattern's 'actual' frequency. Third, using Monte Carlo simulations, those patterns' frequencies are estimated in random data ('random' gene pattern frequency). Fourth, a Z-score for overrepresentation of the pattern is calculated ('actual' against 'random' gene pattern frequencies). We wrote a Visual Basic program (StatiGen) that automates PPM procedure, constructs an Excel workbook with standardized graphs of overrepresented patterns, and lists of the genes comprising each pattern. The visual basic code, installation files for StatiGen, and sample data are available as supplementary material.</p> <p>Conclusion</p> <p>The PPM procedure is designed to augment current microarray analysis procedures by allowing researchers to incorporate all of the information from post hoc tests to establish unique, overarching gene expression patterns in which there is no overlap in gene membership. In our hands, PPM works well for studies using from three to six treatment groups in which the researcher is interested in treatment-related patterns of gene expression. Hardware/software limitations and extreme number of theoretical expression patterns limit utility for larger numbers of treatment groups. Applied to a published microarray experiment, the StatiGen program successfully flagged patterns that had been manually assigned in prior work, and further identified other gene expression patterns that may be of interest. Thus, over a moderate range of treatment groups, PPM appears to work well. It allows researchers to assign statistical probabilities to patterns of gene expression that fit <it>a priori </it>expectations/hypotheses, it preserves the data's ability to show the researcher interesting, yet unanticipated gene expression patterns, and assigns the majority of ANOVA-significant genes to non-overlapping patterns.</p

Targeting Huntington’s disease through histone deacetylases

Huntington’s disease (HD) is a debilitating neurodegenerative condition with significant burdens on both patient and healthcare costs. Despite extensive research, treatment options for patients with this condition remain limited. Aberrant post-translational modification (PTM) of proteins is emerging as an important element in the pathogenesis of HD. These PTMs include acetylation, phosphorylation, methylation, sumoylation and ubiquitination. Several families of proteins are involved with the regulation of these PTMs. In this review, I discuss the current evidence linking aberrant PTMs and/or aberrant regulation of the cellular machinery regulating these PTMs to HD pathogenesis. Finally, I discuss the evidence suggesting that pharmacologically targeting one of these protein families the histone deacetylases may be of potential therapeutic benefit in the treatment of HD