Metallothionein-1 and nitric oxide expression are inversely correlated in a murine model of Chagas disease

Chagas disease, caused by Trypanosoma cruzi, represents an endemic among Latin America countries. The participation of free radicals, especially nitric oxide (NO), has been demonstrated in the pathophysiology of seropositive individuals with T. cruzi. In Chagas disease, increased NO contributes to the development of cardiomyopathy and megacolon. Metallothioneins (MTs) are efficient free radicals scavengers of NO in vitro and in vivo. Here, we developed a murine model of the chronic phase of Chagas disease using endemic T. cruzi RyCH1 in BALB/c mice, which were divided into four groups: infected non-treated (Inf), infected N-monomethyl-L-arginine treated (Inf L-NAME), non-infected L-NAME treated and non-infected vehicle-treated. We determined blood parasitaemia and NO levels, the extent of parasite nests in tissues and liver MT-I expression levels. It was observed that NO levels were increasing in Inf mice in a time-dependent manner. Inf L-NAME mice had fewer T. cruzi nests in cardiac and skeletal muscle with decreased blood NO levels at day 135 post infection. This affect was negatively correlated with an increase of MT-I expression (r = -0.8462, p < 0.0001). In conclusion, we determined that in Chagas disease, an unknown inhibitory mechanism reduces MT-I expression, allowing augmented NO levels.

Do pseudo-absence selection strategies influence species distribution models and their predictions? An information-theoretic approach based on simulated data

Background Multiple logistic regression is precluded from many practical applications in ecology that aim to predict the geographic distributions of species because it requires absence data, which are rarely available or are unreliable. In order to use multiple logistic regression, many studies have simulated "pseudo-absences" through a number of strategies, but it is unknown how the choice of strategy influences models and their geographic predictions of species. In this paper we evaluate the effect of several prevailing pseudo-absence strategies on the predictions of the geographic distribution of a virtual species whose "true" distribution and relationship to three environmental predictors was predefined. We evaluated the effect of using a) real absences b) pseudo-absences selected randomly from the background and c) two-step approaches: pseudo-absences selected from low suitability areas predicted by either Ecological Niche Factor Analysis: (ENFA) or BIOCLIM. We compared how the choice of pseudo-absence strategy affected model fit, predictive power, and information-theoretic model selection results. Results Models built with true absences had the best predictive power, best discriminatory power, and the "true" model (the one that contained the correct predictors) was supported by the data according to AIC, as expected. Models based on random pseudo-absences had among the lowest fit, but yielded the second highest AUC value (0.97), and the "true" model was also supported by the data. Models based on two-step approaches had intermediate fit, the lowest predictive power, and the "true" model was not supported by the data. Conclusion If ecologists wish to build parsimonious GLM models that will allow them to make robust predictions, a reasonable approach is to use a large number of randomly selected pseudo-absences, and perform model selection based on an information theoretic approach. However, the resulting models can be expected to have limited fit.

Severity of chronic experimental Chagas' heart disease parallels tumour necrosis factor and nitric oxide levels in the serum: models of mild and severe disease

Heart tissue inflammation, progressive fibrosis and electrocardiographic alterations occur in approximately 30% of patients infected by Trypanosoma cruzi, 10-30 years after infection. Further, plasma levels of tumour necrosis factor (TNF) and nitric oxide (NO) are associated with the degree of heart dysfunction in chronic chagasic cardiomyopathy (CCC). Thus, our aim was to establish experimental models that mimic a range of parasitological, pathological and cardiac alterations described in patients with chronic Chagas’ heart disease and evaluate whether heart disease severity was associated with increased TNF and NO levels in the serum. Our results show that C3H/He mice chronically infected with the Colombian T. cruzi strain have more severe cardiac parasitism and inflammation than C57BL/6 mice. In addition, connexin 43 disorganisation and fibronectin deposition in the heart tissue, increased levels of creatine kinase cardiac MB isoenzyme activity in the serum and more severe electrical abnormalities were observed in T. cruzi-infected C3H/He mice compared to C57BL/6 mice. Therefore, T. cruzi-infected C3H/He and C57BL/6 mice represent severe and mild models of CCC, respectively. Moreover, the CCC severity paralleled the TNF and NO levels in the serum. Therefore, these models are appropriate for studying the pathophysiology and biomarkers of CCC progression, as well as for testing therapeutic agents for patients with Chagas’ heart disease.

Trabecular bone score (TBS) the new parameter of 2D texture analysis for the evaluation of 3D bone micro architecture status

X-ray is a technology that is used for numerous applications in the medical field. The process of X-ray projection gives a 2-dimension (2D) grey-level texture from a 3- dimension (3D) object. Until now no clear demonstration or correlation has positioned the 2D texture analysis as a valid indirect evaluation of the 3D microarchitecture. TBS is a new texture parameter based on the measure of the experimental variogram. TBS evaluates the variation between 2D image grey-levels. The aim of this study was to evaluate existing correlations between 3D bone microarchitecture parameters - evaluated from μCT reconstructions - and the TBS value, calculated on 2D projected images. 30 dried human cadaveric vertebrae were acquired on a micro-scanner (eXplorer Locus, GE) at isotropic resolution of 93 μm. 3D vertebral body models were used. The following 3D microarchitecture parameters were used: Bone volume fraction (BV/TV), Trabecular thickness (TbTh), trabecular space (TbSp), trabecular number (TbN) and connectivity density (ConnD). 3D/2D projections has been done by taking into account the Beer-Lambert Law at X-ray energy of 50, 100, 150 KeV. TBS was assessed on 2D projected images. Correlations between TBS and the 3D microarchitecture parameters were evaluated using a linear regression analysis. Paired T-test is used to assess the X-ray energy effects on TBS. Multiple linear regressions (backward) were used to evaluate relationships between TBS and 3D microarchitecture parameters using a bootstrap process. BV/TV of the sample ranged from 18.5 to 37.6% with an average value at 28.8%. Correlations' analysis showedthat TBSwere strongly correlatedwith ConnD(0.856≤r≤0.862; p<0.001),with TbN (0.805≤r≤0.810; p<0.001) and negatively with TbSp (−0.714≤r≤−0.726; p<0.001), regardless X-ray energy. Results show that lower TBS values are related to "degraded" microarchitecture, with low ConnD, low TbN and a high TbSp. The opposite is also true. X-ray energy has no effect onTBS neither on the correlations betweenTBS and the 3Dmicroarchitecture parameters. In this study, we demonstrated that TBS was significantly correlated with 3D microarchitecture parameters ConnD and TbN, and negatively with TbSp, no matter what X-ray energy has been used. This article is part of a Special Issue entitled ECTS 2011. Disclosure of interest: None declared.

Glutathione Precursor, N-Acetyl-Cysteine, Modulates EEG Synchronization in Schizophrenia Patients

Background: Glutathione (GSH) dysregulation at the gene, protein and functional levels observed in schizophrenia patients, and schizophrenia-like anomalies in GSH deficit experimental models, suggest that genetic glutathione synthesis impairments represent one major risk factor for the disease (Do et al., 2009). In a randomized, double blind, placebo controlled, add-on clinical trial of 140 patients, the GSH precursor N-Acetyl-Cysteine (NAC, 2g/day, 6 months) significantly improved the negative symptoms and reduced sideeffects due to antipsychotics (Berk et al., 2008). In a subset of patients (n=7), NAC (2g/day, 2 months, cross-over design) also improved auditory evoked potentials, the NMDA-dependent mismatch negativity (Lavoie et al, 2008). Methods: To determine whether increased GSH levels would modulate the topography of functional brain connectivity, we applied a multivariate phase synchronization (MPS) estimator (Knyazeva et al, 2008) to dense-array EEGs recorded during rest with eyes closed at the protocol onset, the point of crossover, and at its end. Results: The whole-head imaging revealed a specific synchronization landscape in NAC compared to placebo condition. In particular, NAC increased MPS over frontal and left temporal regions in a frequency-specific manner. The topography and direction of MPS changes were similar and robust in all 7 patients. Moreover, these changes correlated with the changes in the Liddle's score of disorganization, thus linking EEG synchronization to the improvement of the clinical picture. Conclusions: The data suggest an important pathway towards new therapeutic strategies that target GSH dysregulation in schizophrenia. They also show the utility of MPS mapping as a marker of treatment efficacy.

Pròtesi invertida d’espatlla: estudi retrospectiu del conflicte escapular en 2 models diferents de pròtesis

Aquest és un estudi retrospectiu que compara la mobilitat i el conflicto escàpulo-humeral entre 2 models diferents de pròtesi invertida d’espatlla. Aquestes pròtesis s’han implantat en pacients amb ruptures del manegot dels rotadors irreparables. Aquesta cirugía no està exenta de complicacions, i una de les més habituals és el conflicto escàpulo-humeral o notch.

Suicidal ideation and the risk of suicide in patients with fibromyalgia: a comparison with non-pain controls and patients suffering from low-back pain.

Fibromyalgia is associated with an increased rate of mortality from suicide. In fact, this disease is associated with several characteristics that are linked to an increased risk of suicidal behaviors, such as being female and experiencing chronic pain, psychological distress, and sleep disturbances. However, the literature concerning suicidal behaviors and their risk factors in fibromyalgia is sparse. The objectives of the present study were to evaluate the prevalence of suicidal ideation and the risk of suicide in a sample of patients with fibromyalgia compared with a sample of healthy subjects and a sample of patients with chronic low-back pain. We also aimed to evaluate the relevance of pain intensity, depression, and sleep quality as variables related to suicidal ideation and risks. Logistic regression was applied to estimate the likelihood of suicidal ideation and the risk of suicide adjusted by age and sex. We also used two logistic regression models using age, sex, pain severity score, depression severity, sleep quality, and disease state as independent variables and using the control group as a reference. Forty-four patients with fibromyalgia, 32 patients with low-back pain, and 50 controls were included. Suicidal ideation, measured with item 9 of the Beck Depression Inventory, was almost absent among the controls and was low among patients with low-back pain; however, suicidal ideation was prominent among patients with fibromyalgia (P<0.0001). The risk of suicide, measured with the Plutchik Suicide Risk Scale, was also higher among patients with fibromyalgia than in patients with low-back pain or in controls (P<0.0001). The likelihood for suicidal ideation and the risk of suicide were higher among patients with fibromyalgia (odds ratios of 26.9 and 48.0, respectively) than in patients with low-back pain (odds ratios 4.6 and 4.7, respectively). Depression was the only factor associated with suicidal ideation or the risk of suicide.

Designing business models of cloud platforms

Cloud computing and its three facets (Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS)) are terms that denote new developments in the software industry. In particular, PaaS solutions, also referred to as cloud platforms, are changing the way software is being produced, distributed, consumed, and priced. Software vendors have started considering cloud platforms as a strategic option but are battling to redefine their offerings to embrace PaaS. In contrast to SaaS and IaaS, PaaS allows for value co-creation with partners to develop complementary components and applications. It thus requires multisided business models that bring together two or more distinct customer segments. Understanding how to design PaaS business models to establish a flourishing ecosystem is crucial for software vendors. This doctoral thesis aims to address this issue in three interrelated research parts. First, based on case study research, the thesis provides a deeper understanding of current PaaS business models and their evolution. Second, it analyses and simulates consumers' preferences regarding PaaS business models, using a conjoint approach to find out what determines the choice of cloud platforms. Finally, building on the previous research outcomes, the third part introduces a design theory for the emerging class of PaaS business models, which is grounded on an extensive action design research study with a large European software vendor. Understanding PaaS business models from a market as well as a consumer perspective will, together with the design theory, inform and guide decision makers in their business model innovation plans. It also closes gaps in the research related to PaaS business model design and more generally related to platform business models.

Genetic consequences of the ice ages on nurseries of the bat Myotis myotis: a mitochondrial and nuclear survey.

Analyses of mitochondrial DNA (mtDNA) control region polymorphism and of variation at 10 nuclear microsatellite loci were used to investigate the mechanisms and genetic consequences of postglacial expansion of Myotis myotis in Europe. Initial sampling consisted of 480 bats genotyped in 24 nursery colonies arranged along a transect of approximately 3000 km. The phylogeographical survey based on mtDNA sequences revealed the existence of major genetic subdivisions across this area, with several suture zones between haplogroups. Such zones of secondary contact were found in the Alps and Rhodopes, whereas other potential barriers to gene flow, like the Pyrenees, did not coincide with genetic discontinuities. Areas of population admixture increased locally the genetic diversity of colonies, which confounded the northward decrease in nucleotide diversity predicted using classical models of postglacial range expansion. However, when analyses were restricted to a subset of 15 nurseries originating from a single presumed glacial refugium, mtDNA polymorphism did indeed support a northwards decrease in diversity. Populations were also highly structured (PhiST = 0.384). Conversely, the same subset of colonies showed no significant latitudinal decrease in microsatellite diversity and much less population structure (FST = 0.010), but pairwise genetic differentiation at these nuclear markers was strongly correlated with increasing geographical distance. Together, this evidence suggests that alleles carried via male bats have maintained enough nuclear gene flow to counteract the effects of recurrent bottlenecks generally associated with recolonization processes. As females are highly philopatric, we argue that the maternally transmitted mtDNA marker better reflects the situation of past, historical gene flow, whereas current levels of gene flow are better reflected by microsatellite markers.

Additive functions in boolean models of gene regulatory network modules.

Gene-on-gene regulations are key components of every living organism. Dynamical abstract models of genetic regulatory networks help explain the genome's evolvability and robustness. These properties can be attributed to the structural topology of the graph formed by genes, as vertices, and regulatory interactions, as edges. Moreover, the actual gene interaction of each gene is believed to play a key role in the stability of the structure. With advances in biology, some effort was deployed to develop update functions in Boolean models that include recent knowledge. We combine real-life gene interaction networks with novel update functions in a Boolean model. We use two sub-networks of biological organisms, the yeast cell-cycle and the mouse embryonic stem cell, as topological support for our system. On these structures, we substitute the original random update functions by a novel threshold-based dynamic function in which the promoting and repressing effect of each interaction is considered. We use a third real-life regulatory network, along with its inferred Boolean update functions to validate the proposed update function. Results of this validation hint to increased biological plausibility of the threshold-based function. To investigate the dynamical behavior of this new model, we visualized the phase transition between order and chaos into the critical regime using Derrida plots. We complement the qualitative nature of Derrida plots with an alternative measure, the criticality distance, that also allows to discriminate between regimes in a quantitative way. Simulation on both real-life genetic regulatory networks show that there exists a set of parameters that allows the systems to operate in the critical region. This new model includes experimentally derived biological information and recent discoveries, which makes it potentially useful to guide experimental research. The update function confers additional realism to the model, while reducing the complexity and solution space, thus making it easier to investigate.

Stability of cascade networks via fluid models

Vegeu el resum a l'inici del document de l'arxiu adjunt

Study and implementation of some quantitative trading models

Quantitative or algorithmic trading is the automatization of investments decisions obeying a fixed or dynamic sets of rules to determine trading orders. It has increasingly made its way up to 70% of the trading volume of one of the biggest financial markets such as the New York Stock Exchange (NYSE). However, there is not a signi cant amount of academic literature devoted to it due to the private nature of investment banks and hedge funds. This projects aims to review the literature and discuss the models available in a subject that publications are scarce and infrequently. We review the basic and fundamental mathematical concepts needed for modeling financial markets such as: stochastic processes, stochastic integration and basic models for prices and spreads dynamics necessary for building quantitative strategies. We also contrast these models with real market data with minutely sampling frequency from the Dow Jones Industrial Average (DJIA). Quantitative strategies try to exploit two types of behavior: trend following or mean reversion. The former is grouped in the so-called technical models and the later in the so-called pairs trading. Technical models have been discarded by financial theoreticians but we show that they can be properly cast into a well defined scientific predictor if the signal generated by them pass the test of being a Markov time. That is, we can tell if the signal has occurred or not by examining the information up to the current time; or more technically, if the event is F_t-measurable. On the other hand the concept of pairs trading or market neutral strategy is fairly simple. However it can be cast in a variety of mathematical models ranging from a method based on a simple euclidean distance, in a co-integration framework or involving stochastic differential equations such as the well-known Ornstein-Uhlenbeck mean reversal ODE and its variations. A model for forecasting any economic or financial magnitude could be properly defined with scientific rigor but it could also lack of any economical value and be considered useless from a practical point of view. This is why this project could not be complete without a backtesting of the mentioned strategies. Conducting a useful and realistic backtesting is by no means a trivial exercise since the \laws" that govern financial markets are constantly evolving in time. This is the reason because we make emphasis in the calibration process of the strategies' parameters to adapt the given market conditions. We find out that the parameters from technical models are more volatile than their counterpart form market neutral strategies and calibration must be done in a high-frequency sampling manner to constantly track the currently market situation. As a whole, the goal of this project is to provide an overview of a quantitative approach to investment reviewing basic strategies and illustrating them by means of a back-testing with real financial market data. The sources of the data used in this project are Bloomberg for intraday time series and Yahoo! for daily prices. All numeric computations and graphics used and shown in this project were implemented in MATLAB^R scratch from scratch as a part of this thesis. No other mathematical or statistical software was used.

Modelling world investment markets using threshold conditional correlation models

In this paper we propose a parsimonious regime-switching approach to model the correlations between assets, the threshold conditional correlation (TCC) model. This method allows the dynamics of the correlations to change from one state (or regime) to another as a function of observable transition variables. Our model is similar in spirit to Silvennoinen and Teräsvirta (2009) and Pelletier (2006) but with the appealing feature that it does not suffer from the course of dimensionality. In particular, estimation of the parameters of the TCC involves a simple grid search procedure. In addition, it is easy to guarantee a positive definite correlation matrix because the TCC estimator is given by the sample correlation matrix, which is positive definite by construction. The methodology is illustrated by evaluating the behaviour of international equities, govenrment bonds and major exchange rates, first separately and then jointly. We also test and allow for different parts in the correlation matrix to be governed by different transition variables. For this, we estimate a multi-threshold TCC specification. Further, we evaluate the economic performance of the TCC model against a constant conditional correlation (CCC) estimator using a Diebold-Mariano type test. We conclude that threshold correlation modelling gives rise to a significant reduction in portfolio´s variance.

Two functional variants of IRF5 influence the development of macular edema in patients with non-anterior uveitis.

OBJECTIVE Interferon (IFN) signaling plays a crucial role in autoimmunity. Genetic variation in interferon regulatory factor 5 (IRF5), a major regulator of the type I interferon induction, has been associated with risk of developing several autoimmune diseases. In the current study we aimed to evaluate whether three sets of correlated IRF5 genetic variants, independently associated with SLE and with different functional roles, are involved in uveitis susceptibility and its clinical subphenotypes. METHODS Three IRF5 polymorphisms, rs2004640, rs2070197 and rs10954213, representative of each group, were genotyped using TaqMan® allelic discrimination assays in a total of 263 non-anterior uveitis patients and 724 healthy controls of Spanish origin. RESULTS A clear association between two of the three analyzed genetic variants, rs2004640 and rs10954213, and the absence of macular edema was observed in the case/control analysis (P FDR =5.07E-03, OR=1.48, CI 95%=1.14-1.92 and P FDR =3.37E-03, OR=1.54, CI 95%=1.19-2.01, respectively). Consistently, the subphenotype analysis accordingly with the presence/absence of this clinical condition also reached statistical significance (rs2004640: P=0.037, OR=0.69, CI 95%=0.48-0.98; rs10954213: P=0.030, OR=0.67, CI 95%=0.47-0.96), thus suggesting that both IRF5 genetic variants are specifically associated with the lack of macular edema in uveitis patients. CONCLUSION Our results clearly showed for the first time that two functional genetic variants of IRF5 may play a role in the development of macular edema in non-anterior uveitis patients. Identifying genetic markers for macular edema could lead to the possibility of developing novel treatments or preventive therapies.