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.

Influence of sodium intake on circulating levels of neuropeptide Y.

Neuropeptide Y (NPY) is present in the adrenal medulla, in sympathetic neurons as well as in the circulation. This peptide not only exerts a direct vasoconstrictor effect, but also potentiates the vasoconstriction evoked by norepinephrine and sympathetic nerve stimulation. The vasoconstrictor effect of norepinephrine is also enhanced by salt loading and reduced by salt depletion. The purpose of this study was therefore to assess whether there exists a relationship between dietary sodium intake and the levels of circulating NPY. Uninephrectomized normotensive rats were maintained for 3 weeks either on a low, a regular or a high sodium intake. On the day of the experiment, plasma levels of NPY and catecholamines were measured in the unanesthetized animals. There was no significant difference in plasma norepinephrine and epinephrine levels between the 3 groups of rats. Plasma NPY levels were the lowest (65.4 +/- 8.8 fmol/ml, n-10, Mean +/- SEM) in salt-restricted and the highest (151.2 +/- 25 fmol/ml, n-14, p less than 0.02) in salt-loaded animals. Intermediate values were obtained in rats kept on a regular sodium intake (117.6 +/- 20.1 fmol/ml). These findings are therefore compatible with the hypothesis that sodium balance might to some extent influence blood pressure regulation via changes in circulating NPY levels which in turn modify blood pressure responsiveness.

Prevalence of and risk factors for biliary carriage of bacteria showing worrisome and unexpected resistance traits.

Data on biliary carriage of bacteria and, specifically, of bacteria with worrisome and unexpected resistance traits (URB) are lacking. A prospective study (April 2010 to December 2011) was performed that included all patients admitted for <48 h for elective laparoscopic cholecystectomy in a Spanish hospital. Bile samples were cultured and epidemiological/clinical data recorded. Logistic regression models (stepwise) were performed using bactobilia or bactobilia by URB as dependent variables. Models (P < 0.001) showing the highest R(2) values were considered. A total of 198 patients (40.4% males; age, 55.3 ± 17.3 years) were included. Bactobilia was found in 44 of them (22.2%). The presence of bactobilia was associated (R(2) Cox, 0.30) with previous biliary endoscopic retrograde cholangiopancreatography (ERCP) (odds ratio [OR], 8.95; 95% confidence interval [CI], 2.96 to 27.06; P < 0.001), previous admission (OR, 2.82; 95% CI, 1.10 to 7.24; P = 0.031), and age (OR, 1.09 per year; 95% CI, 1.05 to 1.12; P < 0.001). Ten out of the 44 (22.7%) patients with bactobilia carried URB: 1 Escherichia coli isolate (CTX-M), 1 Klebsiella pneumoniae isolate (OXA-48), 3 high-level gentamicin-resistant enterococci, 1 vancomycin-resistant Enterococcus isolate, 3 Enterobacter cloacae strains, and 1 imipenem-resistant Pseudomonas aeruginosa strain. Bactobilia by URB (versus those by non-URB) was only associated (R(2) Cox, 0.19) with previous ERCP (OR, 11.11; 95% CI, 1.98 to 62.47; P = 0.006). For analyses of patients with bactobilia by URB versus the remaining patients, previous ERCP (OR, 35.284; 95% CI, 5.320 to 234.016; P < 0.001), previous intake of antibiotics (OR, 7.200; 95% CI, 0.962 to 53.906; P = 0.050), and age (OR, 1.113 per year of age; 95% CI, 1.028 to 1.206; P = 0.009) were associated with bactobilia by URB (R(2) Cox, 0.19; P < 0.001). Previous antibiotic exposure (in addition to age and previous ERCP) was a risk driver for bactobilia by URB. This may have implications in prophylactic/therapeutic measures.

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.

Integrating human indoor air pollutant exposure within Life Cycle Impact Assessment.

Neglecting health effects from indoor pollutant emissions and exposure, as currently done in Life Cycle Assessment (LCA), may result in product or process optimizations at the expense of workers' or consumers' health. To close this gap, methods for considering indoor exposure to chemicals are needed to complement the methods for outdoor human exposure assessment already in use. This paper summarizes the work of an international expert group on the integration of human indoor and outdoor exposure in LCA, within the UNEP/ SETAC Life Cycle Initiative. A new methodological framework is proposed for a general procedure to include human-health effects from indoor exposure in LCA. Exposure models from occupational hygiene and household indoor air quality studies and practices are critically reviewed and recommendations are provided on the appropriateness of various model alternatives in the context of LCA. A single-compartment box model is recommended for use as a default in LCA, enabling one to screen occupational and household exposures consistent with the existing models to assess outdoor emission in a multimedia environment. An initial set of model parameter values was collected. The comparison between indoor and outdoor human exposure per unit of emission shows that for many pollutants, intake per unit of indoor emission may be several orders of magnitude higher than for outdoor emissions. It is concluded that indoor exposure should be routinely addressed within LCA.

Oleoylethanolamide enhances β-adrenergic-mediated thermogenesis and white-to-brown adipocyte phenotype in epididymal white adipose tissue in rat.

β-adrenergic receptor activation promotes brown adipose tissue (BAT) β-oxidation and thermogenesis by burning fatty acids during uncoupling respiration. Oleoylethanolamide (OEA) can inhibit feeding and stimulate lipolysis by activating peroxisome proliferator-activating receptor-α (PPARα) in white adipose tissue (WAT). Here we explore whether PPARα activation potentiates the effect of β3-adrenergic stimulation on energy balance mediated by the respective agonists OEA and CL316243. The effect of this pharmacological association on feeding, thermogenesis, β-oxidation, and lipid and cholesterol metabolism in epididymal (e)WAT was monitored. CL316243 (1 mg/kg) and OEA (5 mg/kg) co-administration over 6 days enhanced the reduction of both food intake and body weight gain, increased the energy expenditure and reduced the respiratory quotient (VCO2/VO2). This negative energy balance agreed with decreased fat mass and increased BAT weight and temperature, as well as with lowered plasma levels of triglycerides, cholesterol, nonessential fatty acids (NEFAs), and the adipokines leptin and TNF-α. Regarding eWAT, CL316243 and OEA treatment elevated levels of the thermogenic factors PPARα and UCP1, reduced p38-MAPK phosphorylation, and promoted brown-like features in the white adipocytes: the mitochondrial (Cox4i1, Cox4i2) and BAT (Fgf21, Prdm16) genes were overexpressed in eWAT. The enhancement of the fatty-acid β-oxidation factors Cpt1b and Acox1 in eWAT was accompanied by an upregulation of de novo lipogenesis and reduced expression of the unsaturated-fatty-acid-synthesis enzyme gene, Scd1. We propose that the combination of β-adrenergic and PPARα receptor agonists promotes therapeutic adipocyte remodelling in eWAT, and therefore has a potential clinical utility in the treatment of obesity.

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.

Trends in self-reported past alcoholic beverage consumption and ethanol intake from 1950 to 1995 observed in eight European countries participating in the European Investigation into Cancer and Nutrition (EPIC).

OBJECTIVE To describe the trends of self-reported past consumption of alcoholic beverages and ethanol intake from 1950 to 1995 within the European Prospective Investigation into Cancer and Nutrition (EPIC). DESIGN Data on consumption of beer/cider, wine and liqueur/spirits were obtained retrospectively at age 20, 30 and 40 years to calculate average consumption and ethanol intake for the time periods 1950-1975 (at age 20), 1960-1985 (at age 30) and 1970-1995 (at age 40). Regression analysis was conducted with the time period data to assess trends in past alcoholic beverage consumption and ethanol intake with time. SETTING The EPIC project. SUBJECTS In total, 392 064 EPIC participants (275 249 women and 116 815 men) from 21 study centres in eight European countries. RESULTS Generally, increases in beer/cider consumption were observed for most EPIC centres for 1950-1975, 1960-1985 and 1970-1995. Trends in wine consumption differed according to geographical location: downward trends with time were observed for men in southern European EPIC centres, upward trends for those in middle/northern European study centres. For women, similar but less pronounced trends were observed. Because wine consumption was the major contributor to ethanol intake for both men and women in most study centres, time trends for ethanol intake showed a similar geographical pattern to that of wine consumption. CONCLUSION The different trends in alcoholic beverage consumption and ethanol intake suggest that information depicting lifetime history of ethanol intake should be included in analyses of the relationship between ethanol and chronic diseases, particularly in multi-centre studies such as EPIC.

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

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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.

Large-scale analysis of orthologs and paralogs under covarion-like and constant-but-different models of amino acid evolution.

Functional divergence between homologous proteins is expected to affect amino acid sequences in two main ways, which can be considered as proxies of biochemical divergence: a "covarion-like" pattern of correlated changes in evolutionary rates, and switches in conserved residues ("conserved but different"). Although these patterns have been used in case studies, a large-scale analysis is needed to estimate their frequency and distribution. We use a phylogenomic framework of animal genes to answer three questions: 1) What is the prevalence of such patterns? 2) Can we link such patterns at the amino acid level with selection inferred at the codon level? 3) Are patterns different between paralogs and orthologs? We find that covarion-like patterns are more frequently detected than "constant but different," but that only the latter are correlated with signal for positive selection. Finally, there is no obvious difference in patterns between orthologs and paralogs.