Cell-based computational modeling of vascular morphogenesis using Tissue Simulation Toolkit.

Computational modeling has become a widely used tool for unraveling the mechanisms of higher level cooperative cell behavior during vascular morphogenesis. However, experimenting with published simulation models or adding new assumptions to those models can be daunting for novice and even for experienced computational scientists. Here, we present a step-by-step, practical tutorial for building cell-based simulations of vascular morphogenesis using the Tissue Simulation Toolkit (TST). The TST is a freely available, open-source C++ library for developing simulations with the two-dimensional cellular Potts model, a stochastic, agent-based framework to simulate collective cell behavior. We will show the basic use of the TST to simulate and experiment with published simulations of vascular network formation. Then, we will present step-by-step instructions and explanations for building a recent simulation model of tumor angiogenesis. Demonstrated mechanisms include cell-cell adhesion, chemotaxis, cell elongation, haptotaxis, and haptokinesis.

Evaluating the influence of spatial uncertainty in locality points for species distributional modeling

1. Species distribution modelling is used increasingly in both applied and theoretical research to predict how species are distributed and to understand attributes of species' environmental requirements. In species distribution modelling, various statistical methods are used that combine species occurrence data with environmental spatial data layers to predict the suitability of any site for that species. While the number of data sharing initiatives involving species' occurrences in the scientific community has increased dramatically over the past few years, various data quality and methodological concerns related to using these data for species distribution modelling have not been addressed adequately. 2. We evaluated how uncertainty in georeferences and associated locational error in occurrences influence species distribution modelling using two treatments: (1) a control treatment where models were calibrated with original, accurate data and (2) an error treatment where data were first degraded spatially to simulate locational error. To incorporate error into the coordinates, we moved each coordinate with a random number drawn from the normal distribution with a mean of zero and a standard deviation of 5 km. We evaluated the influence of error on the performance of 10 commonly used distributional modelling techniques applied to 40 species in four distinct geographical regions. 3. Locational error in occurrences reduced model performance in three of these regions; relatively accurate predictions of species distributions were possible for most species, even with degraded occurrences. Two species distribution modelling techniques, boosted regression trees and maximum entropy, were the best performing models in the face of locational errors. The results obtained with boosted regression trees were only slightly degraded by errors in location, and the results obtained with the maximum entropy approach were not affected by such errors. 4. Synthesis and applications. To use the vast array of occurrence data that exists currently for research and management relating to the geographical ranges of species, modellers need to know the influence of locational error on model quality and whether some modelling techniques are particularly robust to error. We show that certain modelling techniques are particularly robust to a moderate level of locational error and that useful predictions of species distributions can be made even when occurrence data include some error.

Dynamical modeling and analysis of large cellular regulatory networks.

The dynamical analysis of large biological regulatory networks requires the development of scalable methods for mathematical modeling. Following the approach initially introduced by Thomas, we formalize the interactions between the components of a network in terms of discrete variables, functions, and parameters. Model simulations result in directed graphs, called state transition graphs. We are particularly interested in reachability properties and asymptotic behaviors, which correspond to terminal strongly connected components (or "attractors") in the state transition graph. A well-known problem is the exponential increase of the size of state transition graphs with the number of network components, in particular when using the biologically realistic asynchronous updating assumption. To address this problem, we have developed several complementary methods enabling the analysis of the behavior of large and complex logical models: (i) the definition of transition priority classes to simplify the dynamics; (ii) a model reduction method preserving essential dynamical properties, (iii) a novel algorithm to compact state transition graphs and directly generate compressed representations, emphasizing relevant transient and asymptotic dynamical properties. The power of an approach combining these different methods is demonstrated by applying them to a recent multilevel logical model for the network controlling CD4+ T helper cell response to antigen presentation and to a dozen cytokines. This model accounts for the differentiation of canonical Th1 and Th2 lymphocytes, as well as of inflammatory Th17 and regulatory T cells, along with many hybrid subtypes. All these methods have been implemented into the software GINsim, which enables the definition, the analysis, and the simulation of logical regulatory graphs.

Parental heart rate variability during pediatric consultation

OBJECTIVE: Research regarding communication between pediatricians and parents in pediatric consultation has mainly focused on parental satisfaction, on its influence on compliance and on communication techniques used by pediatricians. However, there is paucity in research regarding parental stress levels during pediatric consultation. Therefore, the aim of our study was to measure parental heart rate variability related as a measure of stress levels during pediatric consultation. METHODS: Video recordings with simultaneous monitoring and recording of parental heart rate were obtained from 38 pediatric consultations in the ambulatory or hospital setting of the department of pediatrics (HFR, Fribourg, Switzerland). Pulse variation was measured every 5 seconds and heart rate variability (increase or decrease were analyzed) in relation to various sections of the consultation. RESULTS: Heart rate significantly decreased at the end of the consultation compared to the beginning of the consultation (p= 0.0567). In addition, heart rate significantly decreased at the beginning of clinical examination (p= 0.0476) compared to psychosocial history taking. During the discussion of laboratory findings and diagnosis, heart rate was significantly elevated compared to the discussion of the prognosis (p=0.0505). CONCLUSION: We conclude that pediatric consultation has a significant impact on parental stress levels shown by parental heart variability. In general, it can be shown that stress levels significantly decrease at the end of the consultation compared to the beginning of the consultation. In addition, stress levels decrease at the beginning of clinical examination and increase during psychosocial history taking and discussion of laboratory findings and diagnosis. Therefore, our findings highlight the importance of a thorough consultation which include a comprehensive clinical examination with special care taken regarding psychosocial issues and information given regarding the diagnosis.

Screening for elevated blood pressure in children and adolescents: a critical appraisal.

Although screening for elevated blood pressure (BP) in adults is beneficial, evidence of its beneficial effects in children is not clear. Elevated BP in children is associated with atherosclerosis early in life and tracks across the life course. However, because of the high variability in BP, tracking is weak, and having an elevated BP in childhood has a low predictive value for having elevated BP later in life. The absolute risk of cardiovascular diseases associated with a given level of BP in childhood and the long-term effect of treatment beginning in childhood are not known. No study has experimentally evaluated the benefits and harm of BP screening in children. One modeling study indicates that BP screen-and-treat strategies in adolescents are moderately cost-effective but less cost-effective than population-wide interventions to decrease BP for the reduction of coronary heart diseases. The US National Heart, Lung, and Blood Institute and the European Society of Hypertension recommend that children 3 years of age and older have their BP measured during every health care visit. According to the US Preventive Services Task Force, there is no sufficient evidence to recommend for or against screening, but their recommendations have to be updated. Whether the benefits of universal BP screening in children outweigh the harm has to be determined. Studies are needed to assess the absolute risk of cardiovascular diseases associated with elevated BP in childhood, to evaluate how to simplify the identification of elevated BP, to evaluate the long-term benefits and harm of treatment beginning in childhood, and to compare universal and targeted screening strategies.

Multimodel inference and multimodel averaging in empirical modeling of occupational exposure levels.

Empirical modeling of exposure levels has been popular for identifying exposure determinants in occupational hygiene. Traditional data-driven methods used to choose a model on which to base inferences have typically not accounted for the uncertainty linked to the process of selecting the final model. Several new approaches propose making statistical inferences from a set of plausible models rather than from a single model regarded as 'best'. This paper introduces the multimodel averaging approach described in the monograph by Burnham and Anderson. In their approach, a set of plausible models are defined a priori by taking into account the sample size and previous knowledge of variables influent on exposure levels. The Akaike information criterion is then calculated to evaluate the relative support of the data for each model, expressed as Akaike weight, to be interpreted as the probability of the model being the best approximating model given the model set. The model weights can then be used to rank models, quantify the evidence favoring one over another, perform multimodel prediction, estimate the relative influence of the potential predictors and estimate multimodel-averaged effects of determinants. The whole approach is illustrated with the analysis of a data set of 1500 volatile organic compound exposure levels collected by the Institute for work and health (Lausanne, Switzerland) over 20 years, each concentration having been divided by the relevant Swiss occupational exposure limit and log-transformed before analysis. Multimodel inference represents a promising procedure for modeling exposure levels that incorporates the notion that several models can be supported by the data and permits to evaluate to a certain extent model selection uncertainty, which is seldom mentioned in current practice.

Intraobserver and interobserver variability of ascending aorta diameter as assessed with ECG-gated MDCT: automatic versus manual measurements

Purpose: Recently morphometric measurements of the ascending aorta have been done with ECG-gated MDCT to help the development of future endovascular therapies (TCT) [1]. However, the variability of these measurements remains unknown. It will be interesting to know the impact of CAD (computer aided diagnosis) with automated segmentation of the vessel and automatic measurements of diameter on the management of ascending aorta aneurysms. Methods and Materials: Thirty patients referred for ECG-gated CT thoracic angiography (64-row CT scanner) were evaluated. Measurements of the maximum and minimum ascending aorta diameters were obtained automatically with a commercially available CAD and semi-manually by two observers separately. The CAD algorithms segment the iv-enhanced lumen of the ascending aorta into perpendicular planes along the centreline. The CAD then determines the largest and the smallest diameters. Both observers repeated the automatic measurements and the semimanual measurements during a different session at least one month after the first measurements. The Bland and Altman method was used to study the inter/intraobserver variability. A Wilcoxon signed-rank test was also used to analyse differences between observers. Results: Interobserver variability for semi-manual measurements between the first and second observers was between 1.2 to 1.0 mm for maximal and minimal diameter, respectively. Intraobserver variability of each observer ranged from 0.8 to 1.2 mm, the lowest variability being produced by the more experienced observer. CAD variability could be as low as 0.3 mm, showing that it can perform better than human observers. However, when used in nonoptimal conditions (streak artefacts from contrast in the superior vena cava or weak lumen enhancement), CAD has a variability that can be as high as 0.9 mm, reaching variability of semi-manual measurements. Furthermore, there were significant differences between both observers for maximal and minimal diameter measurements (p<0.001). There was also a significant difference between the first observer and CAD for maximal diameter measurements with the former underestimating the diameter compared to the latter (p<0.001). As for minimal diameters, they were higher when measured by the second observer than when measured by CAD (p<0.001). Neither the difference of mean minimal diameter between the first observer and CAD nor the difference of mean maximal diameter between the second observer and CAD was significant (p=0.20 and 0.06, respectively). Conclusion: CAD algorithms can lessen the variability of diameter measurements in the follow-up of ascending aorta aneurysms. Nevertheless, in non-optimal conditions, it may be necessary to correct manually the measurements. Improvements of the algorithms will help to avoid such a situation.

Population pharmacokinetics and clinical response for artemether-lumefantrine in pregnant and nonpregnant women with uncomplicated Plasmodium falciparum malaria in Tanzania.

Artemether-lumefantrine (AL) is the first-line treatment for uncomplicated malaria in the second and third trimesters of pregnancy. Its efficacy during pregnancy has recently been challenged due to altered pharmacokinetic (PK) properties in this vulnerable group. The aim of this study was to determine the PK profile of AL in pregnant and nonpregnant women and assess their therapeutic outcome. Thirty-three pregnant women and 22 nonpregnant women with malaria were treated with AL (80/480 mg) twice daily for 3 days. All patients provided five venous plasma samples for drug quantification at random times over 7 days. Inter- and intraindividual variability was assessed, and the effects of covariates were quantified using a nonlinear mixed-effects modeling approach (NONMEM). A one-compartment model with first-order absorption and elimination with linear metabolism from drug to metabolite fitted the data best for both arthemether (AM) and lumefantrine (LF) and their metabolites. Pregnancy status and diarrhea showed a significant influence on LF PK. The relative bioavailability of lumefantrine and its metabolism rate into desmethyl-lumefantrine were, respectively, 34% lower and 78% higher in pregnant women than in nonpregnant patients. The overall PCR-uncorrected treatment failure rates were 18% in pregnant women and 5% in nonpregnant women (odds ratio [OR] = 4.04; P value of 0.22). A high median day 7 lumefantrine concentration was significantly associated with adequate clinical and parasitological response (P = 0.03). The observed reduction in the relative bioavailability of lumefantrine in pregnant women may explain the higher treatment failure in this group, mostly due to lower posttreatment prophylaxis. Hence, a modified treatment regimen of malaria in pregnancy should be considered.

Variability of gait patterns during unconstrained walking assessed by satellite positioning (GPS).

It is established that the ratio between step length (SL) and step frequency (SF) is constant over a large range of walking speed. However, few data are available about the spontaneous variability of this ratio during unconstrained outdoor walking, in particular over a sufficient number of steps. The purpose of the present study was to assess the inter- and intra-subject variability of spatio-temporal gait characteristics [SL, SF and walk ratio (WR=SL/SF)] while walking at different freely selected speeds. Twelve healthy subjects walked three times along a 100-m athletic track at: (1). a slower than preferred speed, (2). preferred speed and (3). a faster than preferred speed. Two professional GPS receivers providing 3D positions assessed the walking speed and SF with high precision (less than 0.5% error). Intra-subject variability was calculated as the variation among eight consecutive 5-s samples. WR was found to be constant at preferred and fast speeds [0.41 (0.04) m.s and 0.41 (0.05) m.s respectively] but was higher at slow speeds [0.44 (0.05) m.s]. In other words, between slow and preferred speed, the speed increase was mediated more by a change in SF than SL. The intra-subject variability of WR was low under preferred [CV, coefficient of variation = 1.9 (0.6)%] and fast [CV=1.8 (0.5)%] speed conditions, but higher under low speed condition [CV=4.1 (1.5)%]. On the other hand, the inter-subject variability of WR was 11%, 10% and 12% at slow, preferred and fast walking speeds respectively. It is concluded that the GPS method is able to capture basic gait parameters over a short period of time (5 s). A specific gait pattern for slow walking was observed. Furthermore, it seems that the walking patterns in free-living conditions exhibit low intra-individual variability, but that there is substantial variability between subjects.

Synchronous versus asynchronous modeling of gene regulatory networks.

MOTIVATION: In silico modeling of gene regulatory networks has gained some momentum recently due to increased interest in analyzing the dynamics of biological systems. This has been further facilitated by the increasing availability of experimental data on gene-gene, protein-protein and gene-protein interactions. The two dynamical properties that are often experimentally testable are perturbations and stable steady states. Although a lot of work has been done on the identification of steady states, not much work has been reported on in silico modeling of cellular differentiation processes. RESULTS: In this manuscript, we provide algorithms based on reduced ordered binary decision diagrams (ROBDDs) for Boolean modeling of gene regulatory networks. Algorithms for synchronous and asynchronous transition models have been proposed and their corresponding computational properties have been analyzed. These algorithms allow users to compute cyclic attractors of large networks that are currently not feasible using existing software. Hereby we provide a framework to analyze the effect of multiple gene perturbation protocols, and their effect on cell differentiation processes. These algorithms were validated on the T-helper model showing the correct steady state identification and Th1-Th2 cellular differentiation process. AVAILABILITY: The software binaries for Windows and Linux platforms can be downloaded from http://si2.epfl.ch/~garg/genysis.html.

Magnetic resonance imaging determinants of intraindividual variability in the elderly: combined analysis of grey and white matter.

Elderly individuals display a rapid age-related increase in intraindividual variability (IIV) of their performances. This phenomenon could reflect subtle changes in frontal lobe integrity. However, structural studies in this field are still missing. To address this issue, we computed an IIV index for a simple reaction time (RT) task and performed magnetic resonance imaging (MRI) including voxel based morphometry (VBM) and the tract based spatial statistics (TBSS) analysis of diffusion tensor imaging (DTI) in 61 adults aged from 22 to 88 years. The age-related IIV increase was associated with decreased fractional anisotropy (FA) as well as increased radial (RD) and mean (MD) diffusion in the main white matter (WM) fiber tracts. In contrast, axial diffusion (AD) and grey matter (GM) densities did not show any significant correlation with IIV. In multivariate models, only FA has an age-independent effect on IIV. These results revealed that WM but not GM changes partly mediated the age-related increase of IIV. They also revealed that the association between WM and IIV could not be only attributed to the damage of frontal lobe circuits but concerned the majority of interhemispheric and intrahemispheric corticocortical connections.

Functional analysis and structural modeling of human APOBEC3G reveal the role of evolutionarily conserved elements in the inhibition of human immunodeficiency virus type 1 infection and Alu transposition.

Retroelements are important evolutionary forces but can be deleterious if left uncontrolled. Members of the human APOBEC3 family of cytidine deaminases can inhibit a wide range of endogenous, as well as exogenous, retroelements. These enzymes are structurally organized in one or two domains comprising a zinc-coordinating motif. APOBEC3G contains two such domains, only the C terminal of which is endowed with editing activity, while its N-terminal counterpart binds RNA, promotes homo-oligomerization, and is necessary for packaging into human immunodeficiency virus type 1 (HIV-1) virions. Here, we performed a large-scale mutagenesis-based analysis of the APOBEC3G N terminus, testing mutants for (i) inhibition of vif-defective HIV-1 infection and Alu retrotransposition, (ii) RNA binding, and (iii) oligomerization. Furthermore, in the absence of structural information on this domain, we used homology modeling to examine the positions of functionally important residues and of residues found to be under positive selection by phylogenetic analyses of primate APOBEC3G genes. Our results reveal the importance of a predicted RNA binding dimerization interface both for packaging into HIV-1 virions and inhibition of both HIV-1 infection and Alu transposition. We further found that the HIV-1-blocking activity of APOBEC3G N-terminal mutants defective for packaging can be almost entirely rescued if their virion incorporation is forced by fusion with Vpr, indicating that the corresponding region of APOBEC3G plays little role in other aspects of its action against this pathogen. Interestingly, residues forming the APOBEC3G dimer interface are highly conserved, contrasting with the rapid evolution of two neighboring surface-exposed amino acid patches, one targeted by the Vif protein of primate lentiviruses and the other of yet-undefined function.