Computer Assisted Self Interviewing in a Sexual Health Clinic as Part of Routine Clinical Care; Impact on Service and Patient and Clinician Views

Written by on March 31, 2011 – 7:00 am -

Background

Computer assisted self interviewing (CASI) has been used at the Melbourne Sexual Health Centre (MSHC) since 2008 for obtaining sexual history and identifying patients' risk factors for sexually transmitted infections (STIs). We aimed to evaluate the impact of CASI operating at MSHC.

Methodology/Principal Findings

The proportion of patients who decline to answer questions using CASI was determined. We then compared consultation times and STI-testing rates during comparable CASI and non-CASI operating periods. Patients and staff completed anonymous questionnaires about their experience with CASI. 14,190 patients completed CASI during the audit period. Men were more likely than women to decline questions about the number of partners they had of the opposite sex (4.4% v 3.6%, p = 0.05) and same sex (8.9% v 0%, p<0.001). One third (34%) of HIV-positive men declined the number of partners they had and 11–17% declined questions about condom use. Women were more likely than men to decline to answer questions about condom use (2.9% v 2.3%, p = 0.05). There was no difference in the mean consultation times during CASI and non-CASI operating periods (p≥0.17). Only the proportion of women tested for chlamydia differed between the CASI and non-CASI period (84% v 88% respectively, p<0.01). 267 patients completed the survey about CASI. Most (72% men and 69% women) were comfortable using the computer and reported that all their answers were accurate (76% men and 71% women). Half preferred CASI but 18% would have preferred a clinician to have asked the questions. 39 clinicians completed the staff survey. Clinicians felt that for some STI risk factors (range 11%–44%), face-to-face questioning was more accurate than CASI. Only 5% were unsatisfied with CASI.

Conclusions

We have demonstrated that CASI is acceptable to both patients and clinicians in a sexual health setting and does not adversely affect various measures of clinical output.


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Minding Impacting Events in a Model of Stochastic Variance

Written by on March 31, 2011 – 7:00 am -

We introduce a generalization of the well-known ARCH process, widely used for generating uncorrelated stochastic time series with long-term non-Gaussian distributions and long-lasting correlations in the (instantaneous) standard deviation exhibiting a clustering profile. Specifically, inspired by the fact that in a variety of systems impacting events are hardly forgot, we split the process into two different regimes: a first one for regular periods where the average volatility of the fluctuations within a certain period of time is below a certain threshold, , and another one when the local standard deviation outnumbers . In the former situation we use standard rules for heteroscedastic processes whereas in the latter case the system starts recalling past values that surpassed the threshold. Our results show that for appropriate parameter values the model is able to provide fat tailed probability density functions and strong persistence of the instantaneous variance characterized by large values of the Hurst exponent (), which are ubiquitous features in complex systems.


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Warming Can Boost Denitrification Disproportionately Due to Altered Oxygen Dynamics

Written by on March 31, 2011 – 7:00 am -

Background

Global warming and the alteration of the global nitrogen cycle are major anthropogenic threats to the environment. Denitrification, the biological conversion of nitrate to gaseous nitrogen, removes a substantial fraction of the nitrogen from aquatic ecosystems, and can therefore help to reduce eutrophication effects. However, potential responses of denitrification to warming are poorly understood. Although several studies have reported increased denitrification rates with rising temperature, the impact of temperature on denitrification seems to vary widely between systems.

Methodology/Principal Findings

We explored the effects of warming on denitrification rates using microcosm experiments, field measurements and a simple model approach. Our results suggest that a three degree temperature rise will double denitrification rates. By performing experiments at fixed oxygen concentrations as well as with oxygen concentrations varying freely with temperature, we demonstrate that this strong temperature dependence of denitrification can be explained by a systematic decrease of oxygen concentrations with rising temperature. Warming decreases oxygen concentrations due to reduced solubility, and more importantly, because respiration rates rise more steeply with temperature than photosynthesis.

Conclusions/Significance

Our results show that denitrification rates in aquatic ecosystems are strongly temperature dependent, and that this is amplified by the temperature dependencies of photosynthesis and respiration. Our results illustrate the broader phenomenon that coupling of temperature dependent reactions may in some situations strongly alter overall effects of temperature on ecological processes.


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Impact of the Topology of Global Macroeconomic Network on the Spreading of Economic Crises

Written by on March 31, 2011 – 7:00 am -

Throughout economic history, the global economy has experienced recurring crises. The persistent recurrence of such economic crises calls for an understanding of their generic features rather than treating them as singular events. The global economic system is a highly complex system and can best be viewed in terms of a network of interacting macroeconomic agents. In this regard, from the perspective of collective network dynamics, here we explore how the topology of the global macroeconomic network affects the patterns of spreading of economic crises. Using a simple toy model of crisis spreading, we demonstrate that an individual country's role in crisis spreading is not only dependent on its gross macroeconomic capacities, but also on its local and global connectivity profile in the context of the world economic network. We find that on one hand clustering of weak links at the regional scale can significantly aggravate the spread of crises, but on the other hand the current network structure at the global scale harbors higher tolerance of extreme crises compared to more “globalized” random networks. These results suggest that there can be a potential hidden cost in the ongoing globalization movement towards establishing less-constrained, trans-regional economic links between countries, by increasing vulnerability of the global economic system to extreme crises.


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The Cell Cycle Regulated Transcriptome of Trypanosoma brucei

Written by on March 31, 2011 – 7:00 am -

Progression of the eukaryotic cell cycle requires the regulation of hundreds of genes to ensure that they are expressed at the required times. Integral to cell cycle progression in yeast and animal cells are temporally controlled, progressive waves of transcription mediated by cell cycle-regulated transcription factors. However, in the kinetoplastids, a group of early-branching eukaryotes including many important pathogens, transcriptional regulation is almost completely absent, raising questions about the extent of cell-cycle regulation in these organisms and the mechanisms whereby regulation is achieved. Here, we analyse gene expression over the Trypanosoma brucei cell cycle, measuring changes in mRNA abundance on a transcriptome-wide scale. We developed a “double-cut” elutriation procedure to select unperturbed, highly synchronous cell populations from log-phase cultures, and compared this to synchronization by starvation. Transcriptome profiling over the cell cycle revealed the regulation of at least 430 genes. While only a minority were homologous to known cell cycle regulated transcripts in yeast or human, their functions correlated with the cellular processes occurring at the time of peak expression. We searched for potential target sites of RNA-binding proteins in these transcripts, which might earmark them for selective degradation or stabilization. Over-represented sequence motifs were found in several co-regulated transcript groups and were conserved in other kinetoplastids. Furthermore, we found evidence for cell-cycle regulation of a flagellar protein regulon with a highly conserved sequence motif, bearing similarity to consensus PUF-protein binding motifs. RNA sequence motifs that are functional in cell-cycle regulation were more widespread than previously expected and conserved within kinetoplastids. These findings highlight the central importance of post-transcriptional regulation in the proliferation of parasitic kinetoplastids.


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Assignment of PolyProline II Conformation and Analysis of Sequence – Structure Relationship

Written by on March 31, 2011 – 7:00 am -

Background

Secondary structures are elements of great importance in structural biology, biochemistry and bioinformatics. They are broadly composed of two repetitive structures namely α-helices and β-sheets, apart from turns, and the rest is associated to coil. These repetitive secondary structures have specific and conserved biophysical and geometric properties. PolyProline II (PPII) helix is yet another interesting repetitive structure which is less frequent and not usually associated with stabilizing interactions. Recent studies have shown that PPII frequency is higher than expected, and they could have an important role in protein – protein interactions.

Methodology/Principal Findings

A major factor that limits the study of PPII is that its assignment cannot be carried out with the most commonly used secondary structure assignment methods (SSAMs). The purpose of this work is to propose a PPII assignment methodology that can be defined in the frame of DSSP secondary structure assignment. Considering the ambiguity in PPII assignments by different methods, a consensus assignment strategy was utilized. To define the most consensual rule of PPII assignment, three SSAMs that can assign PPII, were compared and analyzed. The assignment rule was defined to have a maximum coverage of all assignments made by these SSAMs. Not many constraints were added to the assignment and only PPII helices of at least 2 residues length are defined.

Conclusions/Significance

The simple rules designed in this study for characterizing PPII conformation, lead to the assignment of 5% of all amino as PPII. Sequence – structure relationships associated with PPII, defined by the different SSAMs, underline few striking differences. A specific study of amino acid preferences in their N and C-cap regions was carried out as their solvent accessibility and contact patterns. Thus the assignment of PPII can be coupled with DSSP and thus opens a simple way for further analysis in this field.


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Global Gene Expression Profiling of Endothelium Exposed to Heme Reveals an Organ-Specific Induction of Cytoprotective Enzymes in Sickle Cell Disease

Written by on March 31, 2011 – 7:00 am -

Background

Sickle cell disease (SCD) is characterized by hemolysis, vaso-occlusion and ischemia reperfusion injury. These events cause endothelial dysfunction and vasculopathies in multiple systems. However, the lack of atherosclerotic lesions has led to the idea that there are adaptive mechanisms that protect the endothelium from major vascular insults in SCD patients. The molecular bases for this phenomenon are poorly defined. This study was designed to identify the global profile of genes induced by heme in the endothelium, and assess expression of the heme-inducible cytoprotective enzymes in major organs impacted by SCD.

Methods and Findings

Total RNA isolated from heme-treated endothelial monolayers was screened with the Affymetrix U133 Plus 2.0 chip, and the microarray data analyzed using multiple bioinformatics software. Hierarchical cluster analysis of significantly differentially expressed genes successfully segregated heme and vehicle-treated endothelium. Validation studies showed that the induction of cytoprotective enzymes by heme was influenced by the origin of endothelial cells, the duration of treatment, as well as the magnitude of induction of individual enzymes. In agreement with these heterogeneities, we found that induction of two major Nrf2-regulated cytoprotective enzymes, heme oxygenase-1 and NAD(P)H:quinone oxidoreductase-1 is organ-specific in two transgenic mouse models of SCD. This data was confirmed in the endothelium of post-mortem lung tissues of SCD patients.

Conclusions

Individual organ systems induce unique profiles of cytoprotective enzymes to neutralize heme in SCD. Understanding this heterogeneity may help to develop effective therapies to manage vasculopathies of individual systems.


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Generalized Theorems for Nonlinear State Space Reconstruction

Written by on March 31, 2011 – 7:00 am -

Takens' theorem (1981) shows how lagged variables of a single time series can be used as proxy variables to reconstruct an attractor for an underlying dynamic process. State space reconstruction (SSR) from single time series has been a powerful approach for the analysis of the complex, non-linear systems that appear ubiquitous in the natural and human world. The main shortcoming of these methods is the phenomenological nature of attractor reconstructions. Moreover, applied studies show that these single time series reconstructions can often be improved ad hoc by including multiple dynamically coupled time series in the reconstructions, to provide a more mechanistic model. Here we provide three analytical proofs that add to the growing literature to generalize Takens' work and that demonstrate how multiple time series can be used in attractor reconstructions. These expanded results (Takens' theorem is a special case) apply to a wide variety of natural systems having parallel time series observations for variables believed to be related to the same dynamic manifold. The potential information leverage provided by multiple embeddings created from different combinations of variables (and their lags) can pave the way for new applied techniques to exploit the time-limited, but parallel observations of natural systems, such as coupled ecological systems, geophysical systems, and financial systems. This paper aims to justify and help open this potential growth area for SSR applications in the natural sciences.


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A Comprehensive Benchmark Study of Multiple Sequence Alignment Methods: Current Challenges and Future Perspectives

Written by on March 31, 2011 – 7:00 am -

Multiple comparison or alignmentof protein sequences has become a fundamental tool in many different domains in modern molecular biology, from evolutionary studies to prediction of 2D/3D structure, molecular function and inter-molecular interactions etc. By placing the sequence in the framework of the overall family, multiple alignments can be used to identify conserved features and to highlight differences or specificities. In this paper, we describe a comprehensive evaluation of many of the most popular methods for multiple sequence alignment (MSA), based on a new benchmark test set. The benchmark is designed to represent typical problems encountered when aligning the large protein sequence sets that result from today's high throughput biotechnologies. We show that alignmentmethods have significantly progressed and can now identify most of the shared sequence features that determine the broad molecular function(s) of a protein family, even for divergent sequences. However,we have identified a number of important challenges. First, the locally conserved regions, that reflect functional specificities or that modulate a protein's function in a given cellular context,are less well aligned. Second, motifs in natively disordered regions are often misaligned. Third, the badly predicted or fragmentary protein sequences, which make up a large proportion of today's databases, lead to a significant number of alignment errors. Based on this study, we demonstrate that the existing MSA methods can be exploited in combination to improve alignment accuracy, although novel approaches will still be needed to fully explore the most difficult regions. We then propose knowledge-enabled, dynamic solutions that will hopefully pave the way to enhanced alignment construction and exploitation in future evolutionary systems biology studies.


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Structural Asymmetry of Phosphodiesterase-9, Potential Protonation of a Glutamic Acid, and Role of the Invariant Glutamine

Written by on March 31, 2011 – 7:00 am -

PDE9 inhibitors show potential for treatment of diseases such as diabetes. To help with discovery of PDE9 inhibitors, we performed mutagenesis, kinetic, crystallographic, and molecular dynamics analyses on the active site residues of Gln453 and its stabilizing partner Glu406. The crystal structures of the PDE9 Q453E mutant (PDE9Q453E) in complex with inhibitors IBMX and (S)-BAY73-6691 showed asymmetric binding of the inhibitors in two subunits of the PDE9Q453E dimer and also the significant positional change of the M-loop at the active site. The kinetic analysis of the Q453E and E406A mutants suggested that the invariant glutamine is critical for binding of substrates and inhibitors, but is unlikely to play a key role in the differentiation between substrates of cGMP and cAMP. The molecular dynamics simulations suggest that residue Glu406 may be protonated and may thus explain the hydrogen bond distance between two side chain oxygens of Glu453 and Glu406 in the crystal structure of the PDE9Q453E mutant. The information from these studies may be useful for design of PDE9 inhibitors.


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Statistically Validated Networks in Bipartite Complex Systems

Written by on March 31, 2011 – 7:00 am -

Many complex systems present an intrinsic bipartite structure where elements of one set link to elements of the second set. In these complex systems, such as the system of actors and movies, elements of one set are qualitatively different than elements of the other set. The properties of these complex systems are typically investigated by constructing and analyzing a projected network on one of the two sets (for example the actor network or the movie network). Complex systems are often very heterogeneous in the number of relationships that the elements of one set establish with the elements of the other set, and this heterogeneity makes it very difficult to discriminate links of the projected network that are just reflecting system's heterogeneity from links relevant to unveil the properties of the system. Here we introduce an unsupervised method to statistically validate each link of a projected network against a null hypothesis that takes into account system heterogeneity. We apply the method to a biological, an economic and a social complex system. The method we propose is able to detect network structures which are very informative about the organization and specialization of the investigated systems, and identifies those relationships between elements of the projected network that cannot be explained simply by system heterogeneity. We also show that our method applies to bipartite systems in which different relationships might have different qualitative nature, generating statistically validated networks in which such difference is preserved.


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Inhibitors of Helicobacter pylori Protease HtrA Found by ‘Virtual Ligand’ Screening Combat Bacterial Invasion of Epithelia

Written by on March 31, 2011 – 7:00 am -

Background

The human pathogen Helicobacter pylori (H. pylori) is a main cause for gastric inflammation and cancer. Increasing bacterial resistance against antibiotics demands for innovative strategies for therapeutic intervention.

Methodology/Principal Findings

We present a method for structure-based virtual screening that is based on the comprehensive prediction of ligand binding sites on a protein model and automated construction of a ligand-receptor interaction map. Pharmacophoric features of the map are clustered and transformed in a correlation vector (‘virtual ligand’) for rapid virtual screening of compound databases. This computer-based technique was validated for 18 different targets of pharmaceutical interest in a retrospective screening experiment. Prospective screening for inhibitory agents was performed for the protease HtrA from the human pathogen H. pylori using a homology model of the target protein. Among 22 tested compounds six block E-cadherin cleavage by HtrA in vitro and result in reduced scattering and wound healing of gastric epithelial cells, thereby preventing bacterial infiltration of the epithelium.

Conclusions/Significance

This study demonstrates that receptor-based virtual screening with a permissive (‘fuzzy’) pharmacophore model can help identify small bioactive agents for combating bacterial infection.


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A Ten-microRNA Expression Signature Predicts Survival in Glioblastoma

Written by on March 31, 2011 – 7:00 am -

Glioblastoma (GBM) is the most common and aggressive primary brain tumor with very poor patient median survival. To identify a microRNA (miRNA) expression signature that can predict GBM patient survival, we analyzed the miRNA expression data of GBM patients (n = 222) derived from The Cancer Genome Atlas (TCGA) dataset. We divided the patients randomly into training and testing sets with equal number in each group. We identified 10 significant miRNAs using Cox regression analysis on the training set and formulated a risk score based on the expression signature of these miRNAs that segregated the patients into high and low risk groups with significantly different survival times (hazard ratio [HR] = 2.4; 95% CI = 1.4–3.8; p<0.0001). Of these 10 miRNAs, 7 were found to be risky miRNAs and 3 were found to be protective. This signature was independently validated in the testing set (HR = 1.7; 95% CI = 1.1–2.8; p = 0.002). GBM patients with high risk scores had overall poor survival compared to the patients with low risk scores. Overall survival among the entire patient set was 35.0% at 2 years, 21.5% at 3 years, 18.5% at 4 years and 11.8% at 5 years in the low risk group, versus 11.0%, 5.5%, 0.0 and 0.0% respectively in the high risk group (HR = 2.0; 95% CI = 1.4–2.8; p<0.0001). Cox multivariate analysis with patient age as a covariate on the entire patient set identified risk score based on the 10 miRNA expression signature to be an independent predictor of patient survival (HR = 1.120; 95% CI = 1.04–1.20; p = 0.003). Thus we have identified a miRNA expression signature that can predict GBM patient survival. These findings may have implications in the understanding of gliomagenesis, development of targeted therapy and selection of high risk cancer patients for adjuvant therapy.


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A Melanoma Molecular Disease Model

Written by on March 30, 2011 – 7:00 am -

While advanced melanoma remains one of the most challenging cancers, recent developments in our understanding of the molecular drivers of this disease have uncovered exciting opportunities to guide personalized therapeutic decisions. Genetic analyses of melanoma have uncovered several key molecular pathways that are involved in disease onset and progression, as well as prognosis. These advances now make it possible to create a “Molecular Disease Model” (MDM) for melanoma that classifies individual tumors into molecular subtypes (in contrast to traditional histological subtypes), with proposed treatment guidelines for each subtype including specific assays, drugs, and clinical trials. This paper describes such a Melanoma Molecular Disease Model reflecting the latest scientific, clinical, and technological advances.


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Predicting Phenotypic Severity of Uncertain Gene Variants in the RET Proto-Oncogene

Written by on March 30, 2011 – 7:00 am -

Although reported gene variants in the RET oncogene have been directly associated with multiple endocrine neoplasia type 2 and hereditary medullary thyroid carcinoma, other mutations are classified as variants of uncertain significance (VUS) until the associated clinical phenotype is made clear. Currently, some 46 non-synonymous VUS entries exist in curated archives. In the absence of a gold standard method for predicting phenotype outcomes, this follow up study applies feature selected amino acid physical and chemical properties feeding a Bayes classifier to predict disease association of uncertain gene variants into categories of benign and pathogenic. Algorithm performance and VUS predictions were compared to established phylogenetic based mutation prediction algorithms. Curated outcomes and unpublished RET gene variants with known disease association were used to benchmark predictor performance. Reliable classification of RET uncertain gene variants will augment current clinical information of RET mutations and assist in improving prediction algorithms as knowledge increases.


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