Quantifying rates of landscape evolution and tectonic processes by thermochronology and numerical modeling of crustal heat transport using PECUBE

PECUBE is a three-dimensional thermal-kinematic code capable of solving the heat production-diffusion-advection equation under a temporally varying surface boundary condition. It was initially developed to assess the effects of time-varying surface topography (relief) on low-temperature thermochronological datasets. Thermochronometric ages are predicted by tracking the time-temperature histories of rock-particles ending up at the surface and by combining these with various age-prediction models. In the decade since its inception, the PECUBE code has been under continuous development as its use became wider and addressed different tectonic-geomorphic problems. This paper describes several major recent improvements in the code, including its integration with an inverse-modeling package based on the Neighborhood Algorithm, the incorporation of fault-controlled kinematics, several different ways to address topographic and drainage change through time, the ability to predict subsurface (tunnel or borehole) data, prediction of detrital thermochronology data and a method to compare these with observations, and the coupling with landscape-evolution (or surface-process) models. Each new development is described together with one or several applications, so that the reader and potential user can clearly assess and make use of the capabilities of PECUBE. We end with describing some developments that are currently underway or should take place in the foreseeable future. (C) 2012 Elsevier B.V. All rights reserved.

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.

Autosomal-Recessive Posterior Microphthalmos Is Caused by Mutations in PRSS56, a Gene Encoding a Trypsin-Like Serine Protease.

Posterior microphthalmos (MCOP) is a rare isolated developmental anomaly of the eye characterized by extreme hyperopia due to short axial length. The population of the Faroe Islands shows a high prevalence of an autosomal-recessive form (arMCOP) of the disease. Based on published linkage data, we refined the position of the disease locus (MCOP6) in an interval of 250 kb in chromosome 2q37.1 in two large Faroese families. We detected three different mutations in PRSS56. Patients of the Faroese families were either homozygous for c.926G>C (p.Trp309Ser) or compound heterozygous for c.926G>C and c.526C>G (p.Arg176Gly), whereas a homozygous 1 bp duplication (c.1066dupC) was identified in five patients with arMCOP from a consanguineous Tunisian family. In one patient with MCOP from the Faroe Islands and in another one from Turkey, no PRSS56 mutation was detected, suggesting nonallelic heterogeneity of the trait. Using RT-PCR, PRSS56 transcripts were detected in samples derived from the human adult retina, cornea, sclera, and optic nerve. The expression of the mouse ortholog could be first detected in the eye at E17 and was maintained into adulthood. The predicted PRSS56 protein is a 603 amino acid long secreted trypsin-like serine peptidase. The c.1066dupC is likely to result in a functional null allele, whereas the two point mutations predict the replacement of evolutionary conserved and functionally important residues. Molecular modeling of the p.Trp309Ser mutant suggests that both the affinity and reactivity of the enzyme toward in vivo protein substrates are likely to be substantially reduced.

Optic perineuritis secondary to Wegener's granulomatosis.

BACKGROUND: Optic perineuritis (OPN) is an inflammatory condition involving the optic nerve sheath because of a variety of causes. We describe three patients in whom OPN was secondary to Wegener's granulomatosis (WG) and compare the clinical findings in these cases with those of idiopathic OPN. METHODS: This is a retrospective small case series derived from patients with OPN seen in an outpatient neuro-ophthalmology clinic. Medical records and imaging studies of these patients were reviewed. RESULTS: These patients shared clinical similarities with idiopathic OPN including age, sex, symptoms, radiographic findings and steroid responsiveness. However, recurrence of symptoms on lowering the prednisone dose below 40 mg distinguished these patients from those with idiopathic OPN. CONCLUSIONS: Steroid dependency in idiopathic OPN should raise suspicion of WG. Patients with OPN should be specifically questioned regarding pre-existing upper respiratory tract disorders and rheumatic symptoms and laboratory testing should include acute phase reactants, anti-neutrophil cytoplasmic antibodies and tests of renal function.

Anomalies et complications vasculaires dans les drusen du nerf optique [Vascular anomalies and complications of optic nerve drusen]

BACKGROUND: Drusen of the optic disc are associated with slowly progressive optic neuropathy, characterized by accumulation of acellular laminated concretions in the prelaminar portion of the optic nerve. Papillary hemorrhages and vascular shunts have been reported with disc drusen but their frequency and clinical significance is not well known. METHODS: Retrospective study of fundus photographs of 116 patients with disc drusen referred to the National Hospital for Neurology and Neurosurgery, London, between 1965 and 1991. RESULTS: Hemorrhages were found in 23 eyes from 16/116 (13.8%) patients. Most cases (68.8%, 11/16 cases) occurred in patients with buried drusen, and most hemorrhages were deeply located. Vascular shunts were present in 6.9% (8/116 cases), most frequently in patients with exposed drusen (6/8 cases), most being of the venous type (7/8 cases). DISCUSSION: Vascular anomalies are not rare in disc drusen, as 20.7% (24/116 cases) of our patients presented either disc hemorrhages or shunt vessels. Their presence supports the hypothesis of the slowly progressive nature of disc drusen and the more advanced stage of optic neuropathy in such eyes.

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.

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.

Preliminary regional rockfall hazard mapping using LIDAR-based slope frequency distribution and CONEFALL modeling

A factor limiting preliminary rockfall hazard mapping at regional scale is often the lack of knowledge of potential source areas. Nowadays, high resolution topographic data (LiDAR) can account for realistic landscape details even at large scale. With such fine-scale morphological variability, quantitative geomorphometric analyses become a relevant approach for delineating potential rockfall instabilities. Using digital elevation model (DEM)-based ?slope families? concept over areas of similar lithology and cliffs and screes zones available from the 1:25,000 topographic map, a susceptibility rockfall hazard map was drawn up in the canton of Vaud, Switzerland, in order to provide a relevant hazard overview. Slope surfaces over morphometrically-defined thresholds angles were considered as rockfall source zones. 3D modelling (CONEFALL) was then applied on each of the estimated source zones in order to assess the maximum runout length. Comparison with known events and other rockfall hazard assessments are in good agreement, showing that it is possible to assess rockfall activities over large areas from DEM-based parameters and topographical elements.