Заболевания печени

by Geert-Jan Geersing, Walter Bouwmeester, Peter Zuithoff, Rene Spijker, Mariska Leeflang, Karel Moons

Background

The interest in prognostic reviews is increasing, but to properly review existing evidence an accurate search filer for finding prediction research is needed. The aim of this paper was to validate and update two previously introduced search filters for finding prediction research in Medline: the Ingui filter and the Haynes Broad filter.

Methodology/Principal Findings

Based on a hand search of 6 general journals in 2008 we constructed two sets of papers. Set 1 consisted of prediction research papers (n = 71), and set 2 consisted of the remaining papers (n = 1133). Both search filters were validated in two ways, using diagnostic accuracy measures as performance measures. First, we compared studies in set 1 (reference) with studies retrieved by the search strategies as applied in Medline. Second, we compared studies from 4 published systematic reviews (reference) with studies retrieved by the search filter as applied in Medline. Next – using word frequency methods – we constructed an additional search string for finding prediction research. Both search filters were good in identifying clinical prediction models: sensitivity ranged from 0.94 to 1.0 using our hand search as reference, and 0.78 to 0.89 using the systematic reviews as reference. This latter performance measure even increased to around 0.95 (range 0.90 to 0.97) when either search filter was combined with the additional string that we developed. Retrieval rate of explorative prediction research was poor, both using our hand search or our systematic review as reference, and even combined with our additional search string: sensitivity ranged from 0.44 to 0.85.

Conclusions/Significance

Explorative prediction research is difficult to find in Medline, using any of the currently available search filters. Yet, application of either the Ingui filter or the Haynes broad filter results in a very low number missed clinical prediction model studies.

by Matthias Dehmer, Martin Grabner, Kurt Varmuza

In this paper, we evaluate the uniqueness of several information-theoretic measures for graphs based on so-called information functionals and compare the results with other information indices and non-information-theoretic measures such as the well-known Balaban index. We show that, by employing an information functional based on degree-degree associations, the resulting information index outperforms the Balaban index tremendously. These results have been obtained by using nearly 12 million exhaustively generated, non-isomorphic and unweighted graphs. Also, we obtain deeper insights on these and other topological descriptors when exploring their uniqueness by using exhaustively generated sets of alkane trees representing connected and acyclic graphs in which the degree of a vertex is at most four.

by Dong Dong, Ke Jin, Xiaoli Wu, Yang Zhong

Chemosensory receptors (CR) are crucial for animals to sense the environmental changes and survive on earth. The emergence of whole-genome sequences provides us an opportunity to identify the entire CR gene repertoires. To completely gain more insight into the evolution of CR genes in vertebrates, we identified the nearly all CR genes in 25 vertebrates using homology-based approaches. Among these CR gene repertoires, nearly half of them were identified for the first time in those previously uncharacterized species, such as the guinea pig, giant panda and elephant, etc. Consistent with previous findings, we found that the numbers of CR genes vary extensively among different species, suggesting an extreme form of ‘birth-and-death’ evolution. For the purpose of facilitating CR gene analysis, we constructed a database with the goals to provide a resource for CR genes annotation and a web tool for exploring their evolutionary patterns. Besides a search engine for the gene extraction from a specific chromosome region, an easy-to-use phylogenetic analysis tool was also provided to facilitate online phylogeny study of CR genes. Our work can provide a rigorous platform for further study on the evolution of CR genes in vertebrates.

by Liqin Zhao, Todd E. Morgan, Zisu Mao, Sharon Lin, Enrique Cadenas, Caleb E. Finch, Christian J. Pike, Wendy J. Mack, Roberta D. Brinton

This study investigated the impact of chronic exposure to continuous (CoP4) versus cyclic progesterone (CyP4) alone or in combination with 17β-estradiol (E2) on gene expression profiles targeting bioenergetics, metabolism and inflammation in the adult female rat hippocampus. High-throughput qRT-PCR analyses revealed that ovarian hormonal depletion induced by ovariectomy (OVX) led to multiple significant gene expression alterations, which were to a great extent reversed by co-administration of E2 and CyP4. In contrast, co-administration of E2 and CoP4 induced a pattern highly resembling OVX. Bioinformatics analyses further revealed clear disparities in functional profiles associated with E2+CoP4 and E2+CyP4. Genes involved in mitochondrial energy (ATP synthase α subunit; Atp5a1), redox homeostasis (peroxiredoxin 5; Prdx5), insulin signaling (insulin-like growth factor I; Igf1), and cholesterol trafficking (liver X receptor α subtype; Nr1h3), differed in direction of regulation by E2+CoP4 (down-regulation relative to OVX) and E2+CyP4 (up-regulation relative to OVX). In contrast, genes involved in amyloid metabolism (β-secretase; Bace1) differed only in degree of regulation, as both E2+CoP4 and E2+CyP4 induced down-regulation at different efficacy. E2+CyP4-induced changes could be associated with regulation of progesterone receptor membrane component 1(Pgrmc1). In summary, results from this study provide evidence at the molecular level that differing regimens of hormone therapy (HT) can induce disparate gene expression profiles in brain. From a translational perspective, confirmation of these results in a model of natural menopause, would imply that the common regimen of continuous combined HT may have adverse consequences whereas a cyclic combined regimen, which is more physiological, could be an effective strategy to maintain neurological health and function throughout menopausal aging.

by Ildefonso M. De la Fuente, Jesus M. Cortes

The understanding of the effective functionality that governs the enzymatic self-organized processes in cellular conditions is a crucial topic in the post-genomic era. In recent studies, Transfer Entropy has been proposed as a rigorous, robust and self-consistent method for the causal quantification of the functional information flow among nonlinear processes. Here, in order to quantify the functional connectivity for the glycolytic enzymes in dissipative conditions we have analyzed different catalytic patterns using the technique of Transfer Entropy. The data were obtained by means of a yeast glycolytic model formed by three delay differential equations where the enzymatic rate equations of the irreversible stages have been explicitly considered. These enzymatic activity functions were previously modeled and tested experimentally by other different groups. The results show the emergence of a new kind of dynamical functional structure, characterized by changing connectivity flows and a metabolic invariant that constrains the activity of the irreversible enzymes. In addition to the classical topological structure characterized by the specific location of enzymes, substrates, products and feedback-regulatory metabolites, an effective functional structure emerges in the modeled glycolytic system, which is dynamical and characterized by notable variations of the functional interactions. The dynamical structure also exhibits a metabolic invariant which constrains the functional attributes of the enzymes. Finally, in accordance with the classical biochemical studies, our numerical analysis reveals in a quantitative manner that the enzyme phosphofructokinase is the key-core of the metabolic system, behaving for all conditions as the main source of the effective causal flows in yeast glycolysis.

by Yongrui Wu, Joachim Messing

Background

One of the goals of plant breeding is to create crops to provide better nutrition for humans and livestock. Insufficient intake of protein is one of the most severe factors affecting the growth and development of children in developing countries. More than a century ago, in 1896, Hopkins initiated the well-known Illinois long-term selection for maize seed protein concentration, yielding four protein strains. By continuously accumulating QTLs, Illinois High Protein (IHP) reached a protein level 2.5-fold higher than normal maize, with the most increased fraction being the zein protein, which was shown to contain no lysine soon after the long-term selection program initiated. Therefore, IHP is of little value for feeding humans and monogastric animals. Although high-lysine lines of non-vitreous mutants were based on reduced zeins, the kernel soft texture precluded their practical use. Kernel hardness in opaque 2 (o2) could be restored in quality protein maize (QPM) with quantitative trait loci called o2 modifiers (Mo2s), but those did not increase total protein levels.

Methods

The most predominant zeins are the 22- and 19-kDa α-zeins. To achieve a combination of desired traits, we used RNA interference (RNAi) against both α-zeins in IHP and evaluated the silencing effect by SDS-PAGE. Total protein, amino acid composition and kernel texture were analyzed.

Conclusions

The α-zeins were dramatically reduced, but the high total seed protein level remained unchanged by complementary increase of non-zein proteins. Moreover, the residual zein levels still allowed for a vitreous hard seed. Such dramatic rebalancing of the nitrogen sink could have a major impact in world food supply.

by Hee Kuk Park, Myung-Ho Ha, Sang-Gue Park, Myeung Nam Kim, Beom Joon Kim, Wonyong Kim

The human scalp harbors a vast community of microbial mutualists, the composition of which is difficult to elucidate as many of the microorganisms are not culturable using current culture techniques. Dandruff, a common scalp disorder, is known as a causative factor of a mild seborrheic dermatitis as well as pityriasis versicolor, seborrheic dermatitis, and atopic dermatitis. Lipophilic yeast Malassezia is widely accepted to play a role in dandruff, but relatively few comprehensive studies have been reported. In order to investigate fungal biota and genetic resources of dandruff, we amplified the 26S rRNA gene from samples of healthy scalps and dandruff-afflicted scalps. The sequences were analyzed by a high throughput method using a GS-FLX 454 pyrosequencer. Of the 74,811 total sequence reads, Basidiomycota (Filobasidium spp.) was the most common phylum associated with dandruff. In contrast, Ascomycota (Acremonium spp.) was common in the healthy scalps. Our results elucidate the distribution of fungal communities associated with dandruff and provide new avenues for the potential prevention and treatment of dandruff.

by Mu-Yan Cai, Rong-Zhen Luo, Jie-Wei Chen, Xiao-Qing Pei, Jia-Bin Lu, Jing-Hui Hou, Jing-Ping Yun

Background

ZEB2 has been suggested to mediate EMT and disease aggressiveness in several types of human cancers. However, the expression patterns of ZEB2 in hepatocellular carcinoma (HCC) and its effect on prognosis of HCC patients treated with hepatectomy are unclear.

Methodology/Principal Findings

In this study, the methods of tissue microarray and immunohistochemistry (IHC) were utilized to investigate ZEB2 expression in HCC and peritumoral liver tissue (PLT). Receiver operating characteristic (ROC), spearman's rank correlation, Kaplan-Meier plots and Cox proportional hazards regression model were used to analyze the data. Up-regulated expression of cytoplasmic/nuclear ZEB2 protein was observed in the majority of PLTs, when compared to HCCs. Further analysis showed that overexpression of cytoplasmic ZEB2 in HCCs was inversely correlated with AFP level, tumor size and differentiation (P<0.05). Also, overexpression of cytoplasmic ZEB2 in PLTs correlated with lower AFP level (P<0.05). In univariate survival analysis, a significant association between overexpression of cytoplasmic ZEB2 by HCCs/PLTs and longer patients' survival was found (P<0.05). Importantly, cytoplasmic ZEB2 expression in PLTs was evaluated as an independent prognostic factor in multivariate analysis (P<0.05). Consequently, a new clinicopathologic prognostic model with cytoplasmic ZEB2 expression (including HCCs and PLTs) was constructed. The model could significantly stratify risk (low, intermediate and high) for overall survival (P = 0.002).

Conclusions/Significance

Our findings provide a basis for the concept that cytoplasmic ZEB2 expressed by PLTs can predict the postoperative survival of patients with HCC. The combined cytoplasmic ZEB2 prognostic model may become a useful tool for identifying patients with different clinical outcomes.

by Marc Parisien, Karl F. Freed, Tobin R. Sosnick

We consider the identification of interacting protein-nucleic acid partners using the rigid body docking method FTdock, which is systematic and exhaustive in the exploration of docking conformations. The accuracy of rigid body docking methods is tested using known protein-DNA complexes for which the docked and undocked structures are both available. Additional tests with large decoy sets probe the efficacy of two published statistically derived scoring functions that contain a huge number of parameters. In contrast, we demonstrate that state-of-the-art machine learning techniques can enormously reduce the number of parameters required, thereby identifying the relevant docking features using a miniscule fraction of the number of parameters in the prior works. The present machine learning study considers a 300 dimensional vector (dependent on only 15 parameters), termed the Chemical Context Profile (CCP), where each dimension reflects a specific type of protein amino acid-nucleic acid base interaction. The CCP is designed to capture the chemical complementarities of the interface and is well suited for machine learning techniques. Our objective function is the Chemical Context Discrepancy (CCD), which is defined as the angle between the native system's CCP vector and the decoy's vector and which serves as a substitute for the more commonly used root mean squared deviation (RMSD). We demonstrate that the CCP provides a useful scoring function when certain dimensions are properly weighted. Finally, we explore how the amino acids on a protein's surface can help guide DNA binding, first through long-range interactions, followed by direct contacts, according to specific preferences for either the major or minor grooves of the DNA.

by Nico J. M. van Beveren, Gabrielle H. S. Buitendijk, Sigrid Swagemakers, Lianne C. Krab, Christian Röder, Lieuwe de Haan, Peter van der Spek, Ype Elgersma

Background

Recent studies have suggested that deregulated AKT1 signaling is associated with schizophrenia. We hypothesized that if this is indeed the case, we should observe both decreased AKT1 expression as well as deregulation of AKT1 regulated pathways in Peripheral Blood Mononuclear Cells (PBMCs) of schizophrenia patients.

Objectives

To examine PBMC expression levels of AKT1 in schizophrenia patients versus controls, and to examine whether functional biological processes in which AKT1 plays an important role are deregulated in schizophrenia patients.

Methods/Results

A case-control study, investigating whole-genome PBMC gene expression in male, recent onset (<5 years) schizophrenia patients (N = 41) as compared to controls (N = 29). Genes, differentially expressed between patients and controls were identified using ANOVA with Benjamini-Hochberg correction (false discovery rate (FDR) = 0.05). Functional aspects of the deregulated set of genes were investigated with the Ingenuity Pathway Analysis (IPA) Software Tool. We found significantly decreased PBMC expression of AKT1 (p<0.001, t = −4.25) in the patients. AKT1 expression was decreased in antipsychotic-free or -naive patients (N = 11), in florid psychotic (N = 20) and in remitted (N = 21) patients. A total of 1224 genes were differentially expressed between patients and controls (FDR = 0.05). Functional analysis of the entire deregulated gene set indicated deregulated canonical pathways involved in a large number of cellular processes: immune system, cell adhesion and neuronal guidance, neurotrophins and (neural) growth factors, oxidative stress and glucose metabolism, and apoptosis and cell-cycle regulation. Many of these processes are associated with AKT1.

Conclusions

We show significantly decreased PBMC gene expression of AKT1 in male, recent-onset schizophrenia patients. Our observations suggest that decreased PBMC AKT1 expression is a stable trait in recent onset, male schizophrenia patients. We identified several AKT related cellular processes which are potentially affected in these patients, a majority of which play a prominent role in current schizophrenia hypotheses.

by Cédric Sueur, Jean-Louis Deneubourg, Odile Petit

Relationships we have with our friends, family, or colleagues influence our personal decisions, as well as decisions we make together with others. As in human beings, despotism and egalitarian societies seem to also exist in animals. While studies have shown that social networks constrain many phenomena from amoebae to primates, we still do not know how consensus emerges from the properties of social networks in many biological systems. We created artificial social networks that represent the continuum from centralized to decentralized organization and used an agent-based model to make predictions about the patterns of consensus and collective movements we observed according to the social network. These theoretical results showed that different social networks and especially contrasted ones – star network vs. equal network - led to totally different patterns. Our model showed that, by moving from a centralized network to a decentralized one, the central individual seemed to lose its leadership in the collective movement's decisions. We, therefore, showed a link between the type of social network and the resulting consensus. By comparing our theoretical data with data on five groups of primates, we confirmed that this relationship between social network and consensus also appears to exist in animal societies.

by Gunjan Sharma, Rakesh Tamang, Ruchira Chaudhary, Vipin Kumar Singh, Anish M. Shah, Sharath Anugula, Deepa Selvi Rani, Alla G. Reddy, Muthukrishnan Eaaswarkhanth, Gyaneshwer Chaubey, Lalji Singh, Kumarasamy Thangaraj

Background

The central Indian state Madhya Pradesh is often called as ‘heart of India’ and has always been an important region functioning as a trinexus belt for three major language families (Indo-European, Dravidian and Austroasiatic). There are less detailed genetic studies on the populations inhabited in this region. Therefore, this study is an attempt for extensive characterization of genetic ancestries of three tribal populations, namely; Bharia, Bhil and Sahariya, inhabiting this region using haploid and diploid DNA markers.

Methodology/Principal Findings

Mitochondrial DNA analysis showed high diversity, including some of the older sublineages of M haplogroup and prominent R lineages in all the three tribes. Y-chromosomal biallelic markers revealed high frequency of Austroasiatic-specific M95-O2a haplogroup in Bharia and Sahariya, M82-H1a in Bhil and M17-R1a in Bhil and Sahariya. The results obtained by haploid as well as diploid genetic markers revealed strong genetic affinity of Bharia (a Dravidian speaking tribe) with the Austroasiatic (Munda) group. The gene flow from Austroasiatic group is further confirmed by their Y-STRs haplotype sharing analysis, where we determined their founder haplotype from the North Munda speaking tribe, while, autosomal analysis was largely in concordant with the haploid DNA results.

Conclusions/Significance

Bhil exhibited largely Indo-European specific ancestry, while Sahariya and Bharia showed admixed genetic package of Indo-European and Austroasiatic populations. Hence, in a landscape like India, linguistic label doesn't unequivocally follow the genetic footprints.

by Monica Totir, Nathaniel Echols, Max Nanao, Christine L. Gee, Alisa Moskaleva, Scott Gradia, Anthony T. Iavarone, James M. Berger, Andrew P. May, Chloe Zubieta, Tom Alber

Structural biology and structural genomics projects routinely rely on recombinantly expressed proteins, but many proteins and complexes are difficult to obtain by this approach. We investigated native source proteins for high-throughput protein crystallography applications. The Escherichia coli proteome was fractionated, purified, crystallized, and structurally characterized. Macro-scale fermentation and fractionation were used to subdivide the soluble proteome into 408 unique fractions of which 295 fractions yielded crystals in microfluidic crystallization chips. Of the 295 crystals, 152 were selected for optimization, diffraction screening, and data collection. Twenty-three structures were determined, four of which were novel. This study demonstrates the utility of native source proteins for high-throughput crystallography.

by Matti Myllykoski, Arne Raasakka, Huijong Han, Petri Kursula

The 2′,3′-cyclic nucleotide 3′-phosphodiesterase (CNPase) is a highly abundant membrane-associated enzyme in the myelin sheath of the vertebrate nervous system. CNPase is a member of the 2H phosphoesterase family and catalyzes the formation of 2′-nucleotide products from 2′,3′-cyclic substrates; however, its physiological substrate and function remain unknown. It is likely that CNPase participates in RNA metabolism in the myelinating cell. We solved crystal structures of the phosphodiesterase domain of mouse CNPase, showing the binding mode of nucleotide ligands in the active site. The binding mode of the product 2′-AMP provides a detailed view of the reaction mechanism. Comparisons of CNPase crystal structures highlight flexible loops, which could play roles in substrate recognition; large differences in the active-site vicinity are observed when comparing more distant members of the 2H family. We also studied the full-length CNPase, showing its N-terminal domain is involved in RNA binding and dimerization. Our results provide a detailed picture of the CNPase active site during its catalytic cycle, and suggest a specific function for the previously uncharacterized N-terminal domain.

by Karin M. Verspoor, Judith D. Cohn, Komandur E. Ravikumar, Michael E. Wall

We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites). The structure analysis was carried out using Dynamics Perturbation Analysis (DPA), which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites) in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions.