Limits on the validity of infinite length assumptions for modelling shallow landslides

The infinite slope method is widely used as the geotechnical component of geomorphic and landscape evolution models. Its assumption that shallow landslides are infinitely long (in a downslope direction) is usually considered valid for natural landslides on the basis that they are generally long relative to their depth. However, this is rarely justified, because the critical length/depth (L/H) ratio below which edge effects become important is unknown. We establish this critical L/H ratio by benchmarking infinite slope stability predictions against finite element predictions for a set of synthetic two-dimensional slopes, assuming that the difference between the predictions is due to error in the infinite slope method. We test the infinite slope method for six different L/H ratios to find the critical ratio at which its predictions fall within 5% of those from the finite element method. We repeat these tests for 5000 synthetic slopes with a range of failure plane depths, pore water pressures, friction angles, soil cohesions, soil unit weights and slope angles characteristic of natural slopes. We find that: (1) infinite slope stability predictions are consistently too conservative for small L/H ratios; (2) the predictions always converge to within 5% of the finite element benchmarks by a L/H ratio of 25 (i.e. the infinite slope assumption is reasonable for landslides 25 times longer than they are deep); but (3) they can converge at much lower ratios depending on slope properties, particularly for low cohesion soils. The implication for catchment scale stability models is that the infinite length assumption is reasonable if their grid resolution is coarse (e.g. >25?m). However, it may also be valid even at much finer grid resolutions (e.g. 1?m), because spatial organization in the predicted pore water pressure field reduces the probability of short landslides and minimizes the risk that predicted landslides will have L/H ratios less than 25. Copyright (c) 2012 John Wiley & Sons, Ltd.

The proteolytic activity of the paracaspase MALT1 is key in T cell activation

The paracaspase MALT1 is pivotal in antigen receptor-mediated lymphocyte activation and lymphomagenesis. MALT1 contains a caspase-like domain, but it is unknown whether this domain is proteolytically active. Here we report that MALT1 had arginine-directed proteolytic activity that was activated after T cell stimulation, and we identify the signaling protein Bcl-10 as a MALT1 substrate. Processing of Bcl-10 after Arg228 was required for T cell receptor-induced cell adhesion to fibronectin. In contrast, MALT1 activity but not Bcl-10 cleavage was essential for optimal activation of transcription factor NF-kappaB and production of interleukin 2. Thus, the proteolytic activity of MALT1 is central to T cell activation, which suggests a possible target for the development of immunomodulatory or anticancer drugs

Experimental and computational approaches to quantitative proteomics: status quo and outlook.

Proteomics has come a long way from the initial qualitative analysis of proteins present in a given sample at a given time ("cataloguing") to large-scale characterization of proteomes, their interactions and dynamic behavior. Originally enabled by breakthroughs in protein separation and visualization (by two-dimensional gels) and protein identification (by mass spectrometry), the discipline now encompasses a large body of protein and peptide separation, labeling, detection and sequencing tools supported by computational data processing. The decisive mass spectrometric developments and most recent instrumentation news are briefly mentioned accompanied by a short review of gel and chromatographic techniques for protein/peptide separation, depletion and enrichment. Special emphasis is placed on quantification techniques: gel-based, and label-free techniques are briefly discussed whereas stable-isotope coding and internal peptide standards are extensively reviewed. Another special chapter is dedicated to software and computing tools for proteomic data processing and validation. A short assessment of the status quo and recommendations for future developments round up this journey through quantitative proteomics.

Evolutionary games on complex networks : the emergence and maintenance of cooperation

Abstract The object of game theory lies in the analysis of situations where different social actors have conflicting requirements and where their individual decisions will all influence the global outcome. In this framework, several games have been invented to capture the essence of various dilemmas encountered in many common important socio-economic situations. Even though these games often succeed in helping us understand human or animal behavior in interactive settings, some experiments have shown that people tend to cooperate with each other in situations for which classical game theory strongly recommends them to do the exact opposite. Several mechanisms have been invoked to try to explain the emergence of this unexpected cooperative attitude. Among them, repeated interaction, reputation, and belonging to a recognizable group have often been mentioned. However, the work of Nowak and May (1992) showed that the simple fact of arranging the players according to a spatial structure and only allowing them to interact with their immediate neighbors is sufficient to sustain a certain amount of cooperation even when the game is played anonymously and without repetition. Nowak and May's study and much of the following work was based on regular structures such as two-dimensional grids. Axelrod et al. (2002) showed that by randomizing the choice of neighbors, i.e. by actually giving up a strictly local geographical structure, cooperation can still emerge, provided that the interaction patterns remain stable in time. This is a first step towards a social network structure. However, following pioneering work by sociologists in the sixties such as that of Milgram (1967), in the last few years it has become apparent that many social and biological interaction networks, and even some technological networks, have particular, and partly unexpected, properties that set them apart from regular or random graphs. Among other things, they usually display broad degree distributions, and show small-world topological structure. Roughly speaking, a small-world graph is a network where any individual is relatively close, in terms of social ties, to any other individual, a property also found in random graphs but not in regular lattices. However, in contrast with random graphs, small-world networks also have a certain amount of local structure, as measured, for instance, by a quantity called the clustering coefficient. In the same vein, many real conflicting situations in economy and sociology are not well described neither by a fixed geographical position of the individuals in a regular lattice, nor by a random graph. Furthermore, it is a known fact that network structure can highly influence dynamical phenomena such as the way diseases spread across a population and ideas or information get transmitted. Therefore, in the last decade, research attention has naturally shifted from random and regular graphs towards better models of social interaction structures. The primary goal of this work is to discover whether or not the underlying graph structure of real social networks could give explanations as to why one finds higher levels of cooperation in populations of human beings or animals than what is prescribed by classical game theory. To meet this objective, I start by thoroughly studying a real scientific coauthorship network and showing how it differs from biological or technological networks using divers statistical measurements. Furthermore, I extract and describe its community structure taking into account the intensity of a collaboration. Finally, I investigate the temporal evolution of the network, from its inception to its state at the time of the study in 2006, suggesting also an effective view of it as opposed to a historical one. Thereafter, I combine evolutionary game theory with several network models along with the studied coauthorship network in order to highlight which specific network properties foster cooperation and shed some light on the various mechanisms responsible for the maintenance of this same cooperation. I point out the fact that, to resist defection, cooperators take advantage, whenever possible, of the degree-heterogeneity of social networks and their underlying community structure. Finally, I show that cooperation level and stability depend not only on the game played, but also on the evolutionary dynamic rules used and the individual payoff calculations. Synopsis Le but de la théorie des jeux réside dans l'analyse de situations dans lesquelles différents acteurs sociaux, avec des objectifs souvent conflictuels, doivent individuellement prendre des décisions qui influenceront toutes le résultat global. Dans ce cadre, plusieurs jeux ont été inventés afin de saisir l'essence de divers dilemmes rencontrés dans d'importantes situations socio-économiques. Bien que ces jeux nous permettent souvent de comprendre le comportement d'êtres humains ou d'animaux en interactions, des expériences ont montré que les individus ont parfois tendance à coopérer dans des situations pour lesquelles la théorie classique des jeux prescrit de faire le contraire. Plusieurs mécanismes ont été invoqués pour tenter d'expliquer l'émergence de ce comportement coopératif inattendu. Parmi ceux-ci, la répétition des interactions, la réputation ou encore l'appartenance à des groupes reconnaissables ont souvent été mentionnés. Toutefois, les travaux de Nowak et May (1992) ont montré que le simple fait de disposer les joueurs selon une structure spatiale en leur permettant d'interagir uniquement avec leurs voisins directs est suffisant pour maintenir un certain niveau de coopération même si le jeu est joué de manière anonyme et sans répétitions. L'étude de Nowak et May, ainsi qu'un nombre substantiel de travaux qui ont suivi, étaient basés sur des structures régulières telles que des grilles à deux dimensions. Axelrod et al. (2002) ont montré qu'en randomisant le choix des voisins, i.e. en abandonnant une localisation géographique stricte, la coopération peut malgré tout émerger, pour autant que les schémas d'interactions restent stables au cours du temps. Ceci est un premier pas en direction d'une structure de réseau social. Toutefois, suite aux travaux précurseurs de sociologues des années soixante, tels que ceux de Milgram (1967), il est devenu clair ces dernières années qu'une grande partie des réseaux d'interactions sociaux et biologiques, et même quelques réseaux technologiques, possèdent des propriétés particulières, et partiellement inattendues, qui les distinguent de graphes réguliers ou aléatoires. Entre autres, ils affichent en général une distribution du degré relativement large ainsi qu'une structure de "petit-monde". Grossièrement parlant, un graphe "petit-monde" est un réseau où tout individu se trouve relativement près de tout autre individu en termes de distance sociale, une propriété également présente dans les graphes aléatoires mais absente des grilles régulières. Par contre, les réseaux "petit-monde" ont, contrairement aux graphes aléatoires, une certaine structure de localité, mesurée par exemple par une quantité appelée le "coefficient de clustering". Dans le même esprit, plusieurs situations réelles de conflit en économie et sociologie ne sont pas bien décrites ni par des positions géographiquement fixes des individus en grilles régulières, ni par des graphes aléatoires. De plus, il est bien connu que la structure même d'un réseau peut passablement influencer des phénomènes dynamiques tels que la manière qu'a une maladie de se répandre à travers une population, ou encore la façon dont des idées ou une information s'y propagent. Ainsi, durant cette dernière décennie, l'attention de la recherche s'est tout naturellement déplacée des graphes aléatoires et réguliers vers de meilleurs modèles de structure d'interactions sociales. L'objectif principal de ce travail est de découvrir si la structure sous-jacente de graphe de vrais réseaux sociaux peut fournir des explications quant aux raisons pour lesquelles on trouve, chez certains groupes d'êtres humains ou d'animaux, des niveaux de coopération supérieurs à ce qui est prescrit par la théorie classique des jeux. Dans l'optique d'atteindre ce but, je commence par étudier un véritable réseau de collaborations scientifiques et, en utilisant diverses mesures statistiques, je mets en évidence la manière dont il diffère de réseaux biologiques ou technologiques. De plus, j'extrais et je décris sa structure de communautés en tenant compte de l'intensité d'une collaboration. Finalement, j'examine l'évolution temporelle du réseau depuis son origine jusqu'à son état en 2006, date à laquelle l'étude a été effectuée, en suggérant également une vue effective du réseau par opposition à une vue historique. Par la suite, je combine la théorie évolutionnaire des jeux avec des réseaux comprenant plusieurs modèles et le réseau de collaboration susmentionné, afin de déterminer les propriétés structurelles utiles à la promotion de la coopération et les mécanismes responsables du maintien de celle-ci. Je mets en évidence le fait que, pour ne pas succomber à la défection, les coopérateurs exploitent dans la mesure du possible l'hétérogénéité des réseaux sociaux en termes de degré ainsi que la structure de communautés sous-jacente de ces mêmes réseaux. Finalement, je montre que le niveau de coopération et sa stabilité dépendent non seulement du jeu joué, mais aussi des règles de la dynamique évolutionnaire utilisées et du calcul du bénéfice d'un individu.

Selective changes in the neurofilament and microtubule cytoskeleton of NF-H/LacZ mice.

This study focused mainly on changes in the microtubule cytoskeleton in a transgenic mouse where beta-galactosidase fused to a truncated neurofilament subunit led to a decrease in neurofilament triplet protein expression and a loss in neurofilament assembly and abolished transport into neuronal processes in spinal cord and brain. Although all neurofilament subunits accumulated in neuronal cell bodies, our data suggest an increased solubility of all three subunits, rather than increased precipitation, and point to a perturbed filament assembly. In addition, reduced neurofilament phosphorylation may favor an increased filament degradation. The function of microtubules seemed largely unaffected, in that tubulin and microtubule-associated proteins (MAP) expression and their distribution were largely unchanged in transgenic animals. MAP1A was the only MAP with a reduced signal in spinal cord tissue, and differences in immunostaining in various brain regions corroborate a relationship between MAP1A and neurofilaments.

Trabecular bone score: a noninvasive analytical method based upon the DXA image.

The trabecular bone score (TBS) is a gray-level textural metric that can be extracted from the two-dimensional lumbar spine dual-energy X-ray absorptiometry (DXA) image. TBS is related to bone microarchitecture and provides skeletal information that is not captured from the standard bone mineral density (BMD) measurement. Based on experimental variograms of the projected DXA image, TBS has the potential to discern differences between DXA scans that show similar BMD measurements. An elevated TBS value correlates with better skeletal microstructure; a low TBS value correlates with weaker skeletal microstructure. Lumbar spine TBS has been evaluated in cross-sectional and longitudinal studies. The following conclusions are based upon publications reviewed in this article: 1) TBS gives lower values in postmenopausal women and in men with previous fragility fractures than their nonfractured counterparts; 2) TBS is complementary to data available by lumbar spine DXA measurements; 3) TBS results are lower in women who have sustained a fragility fracture but in whom DXA does not indicate osteoporosis or even osteopenia; 4) TBS predicts fracture risk as well as lumbar spine BMD measurements in postmenopausal women; 5) efficacious therapies for osteoporosis differ in the extent to which they influence the TBS; 6) TBS is associated with fracture risk in individuals with conditions related to reduced bone mass or bone quality. Based on these data, lumbar spine TBS holds promise as an emerging technology that could well become a valuable clinical tool in the diagnosis of osteoporosis and in fracture risk assessment.

Supercoiling, knotting and replication fork reversal in partially replicated plasmids.

To study the structure of partially replicated plasmids, we cloned the Escherichia coli polar replication terminator TerE in its active orientation at different locations in the ColE1 vector pBR18. The resulting plasmids, pBR18-TerE@StyI and pBR18-TerE@EcoRI, were analyzed by neutral/neutral two-dimensional agarose gel electrophoresis and electron microscopy. Replication forks stop at the Ter-TUS complex, leading to the accumulation of specific replication intermediates with a mass 1.26 times the mass of non-replicating plasmids for pBR18-TerE@StyI and 1.57 times for pBR18-TerE@EcoRI. The number of knotted bubbles detected after digestion with ScaI and the number and electrophoretic mobility of undigested partially replicated topoisomers reflect the changes in plasmid topology that occur in DNA molecules replicated to different extents. Exposure to increasing concentrations of chloroquine or ethidium bromide revealed that partially replicated topoisomers (CCCRIs) do not sustain positive supercoiling as efficiently as their non-replicating counterparts. It was suggested that this occurs because in partially replicated plasmids a positive DeltaLk is absorbed by regression of the replication fork. Indeed, we showed by electron microscopy that, at least in the presence of chloroquine, some of the CCCRIs of pBR18-Ter@StyI formed Holliday-like junction structures characteristic of reversed forks. However, not all the positive supercoiling was absorbed by fork reversal in the presence of high concentrations of ethidium bromide.

Genes mirror geography within Europe.

Understanding the genetic structure of human populations is of fundamental interest to medical, forensic and anthropological sciences. Advances in high-throughput genotyping technology have markedly improved our understanding of global patterns of human genetic variation and suggest the potential to use large samples to uncover variation among closely spaced populations. Here we characterize genetic variation in a sample of 3,000 European individuals genotyped at over half a million variable DNA sites in the human genome. Despite low average levels of genetic differentiation among Europeans, we find a close correspondence between genetic and geographic distances; indeed, a geographical map of Europe arises naturally as an efficient two-dimensional summary of genetic variation in Europeans. The results emphasize that when mapping the genetic basis of a disease phenotype, spurious associations can arise if genetic structure is not properly accounted for. In addition, the results are relevant to the prospects of genetic ancestry testing; an individual's DNA can be used to infer their geographic origin with surprising accuracy-often to within a few hundred kilometres.

Assignment strategies for large proteins by magic-angle spinning NMR: the 21-kDa disulfide-bond-forming enzyme DsbA.

We present strategies for chemical shift assignments of large proteins by magic-angle spinning solid-state NMR, using the 21-kDa disulfide-bond-forming enzyme DsbA as prototype. Previous studies have demonstrated that complete de novo assignments are possible for proteins up to approximately 17 kDa, and partial assignments have been performed for several larger proteins. Here we show that combinations of isotopic labeling strategies, high field correlation spectroscopy, and three-dimensional (3D) and four-dimensional (4D) backbone correlation experiments yield highly confident assignments for more than 90% of backbone resonances in DsbA. Samples were prepared as nanocrystalline precipitates by a dialysis procedure, resulting in heterogeneous linewidths below 0.2 ppm. Thus, high magnetic fields, selective decoupling pulse sequences, and sparse isotopic labeling all improved spectral resolution. Assignments by amino acid type were facilitated by particular combinations of pulse sequences and isotopic labeling; for example, transferred echo double resonance experiments enhanced sensitivity for Pro and Gly residues; [2-(13)C]glycerol labeling clarified Val, Ile, and Leu assignments; in-phase anti-phase correlation spectra enabled interpretation of otherwise crowded Glx/Asx side-chain regions; and 3D NCACX experiments on [2-(13)C]glycerol samples provided unique sets of aromatic (Phe, Tyr, and Trp) correlations. Together with high-sensitivity CANCOCA 4D experiments and CANCOCX 3D experiments, unambiguous backbone walks could be performed throughout the majority of the sequence. At 189 residues, DsbA represents the largest monomeric unit for which essentially complete solid-state NMR assignments have so far been achieved. These results will facilitate studies of nanocrystalline DsbA structure and dynamics and will enable analysis of its 41-kDa covalent complex with the membrane protein DsbB, for which we demonstrate a high-resolution two-dimensional (13)C-(13)C spectrum.

Impact of biocontrol strain Pseudomonas fluorescens CHA0 on rhizosphere bacteria isolated from barley (Hordeum vulgare L.) with special reference to Cytophaga-like bacteria.

AIMS: To assess the impact of the biocontrol strain Pseudomonas fluorescens CHA0 on a collection of barley rhizosphere bacteria using an agar plate inhibition assay and a plant microcosm, focusing on a CHA0-sensitive member of the Cytophaga-like bacteria (CLB). METHODS AND RESULTS: The effect of strain CHA0 on a collection of barley rhizosphere bacteria, in particular CLB and fluorescent pseudomonads sampled during a growth season, was assessed by a growth inhibition assay. On average, 85% of the bacteria were sensitive in the May sample, while the effect was reduced to around 68% in the July and August samples. In the May sample, around 95% of the CLB and around 45% of the fluorescent pseudomonads were sensitive to strain CHA0. The proportion of CHA0-sensitive CLB and fluorescent pseudomonad isolates decreased during the plant growth season, i.e. in the July and August samples. A particularly sensitive CLB isolate, CLB23, was selected, exposed to strain CHA0 (wild type) and its genetically modified derivatives in the rhizosphere of barley grown in gnotobiotic soil microcosms. Two dry-stress periods were imposed during the experiment. Derivatives of strain CHA0 included antibiotic or exopolysaccharide (EPS) overproducing strains and a dry-stress-sensitive mutant. Despite their inhibitory activity against CLB23 in vitro, neither wild-type strain CHA0, nor any of its derivatives, had a major effect on culturable and total cell numbers of CLB23 during the 23-day microcosm experiment. Populations of all inoculants declined during the two dry-stress periods, with soil water contents below 5% and plants reaching the wilting point, but they recovered after re-wetting the soil. Survival of the dry-stress-sensitive mutant of CHA0 was most affected by the dry periods; however, this did not result in an increased population density of CLB23. CONCLUSIONS: CLB comprise a large fraction of barley rhizosphere bacteria that are sensitive to the biocontrol pseudomonad CHA0 in vitro. However, in plant microcosm experiments with varying soil humidity conditions, CHA0 or its derivatives had no major impact on the survival of the highly sensitive CLB strain, CLB23, during two dry-stress periods and a re-wetting period; all co-existed well in the rhizosphere of barley plants. SIGNIFICANCE AND IMPACT OF THE STUDY: Results indicate a lack of interaction between the biocontrol pseudomonad CHA0 and a sensitive CLB when the complexity increases from agar plate assays to plant microcosm experiments. This suggests the occurrence of low levels of antibiotic production and/or that the two bacterial genera occupy different niches in the rhizosphere.

Unfolding a symmetric matrix

Graphical displays which show inter--sample distances are importantfor the interpretation and presentation of multivariate data. Except whenthe displays are two--dimensional, however, they are often difficult tovisualize as a whole. A device, based on multidimensional unfolding, isdescribed for presenting some intrinsically high--dimensional displays infewer, usually two, dimensions. This goal is achieved by representing eachsample by a pair of points, say $R_i$ and $r_i$, so that a theoreticaldistance between the $i$-th and $j$-th samples is represented twice, onceby the distance between $R_i$ and $r_j$ and once by the distance between$R_j$ and $r_i$. Self--distances between $R_i$ and $r_i$ need not be zero.The mathematical conditions for unfolding to exhibit symmetry are established.Algorithms for finding approximate fits, not constrained to be symmetric,are discussed and some examples are given.

Power transformations in correspondence analysis

Power transformations of positive data tables, prior to applying the correspondence analysis algorithm, are shown to open up a family of methods with direct connections to the analysis of log-ratios. Two variations of this idea are illustrated. The first approach is simply to power the original data and perform a correspondence analysis this method is shown to converge to unweighted log-ratio analysis as the power parameter tends to zero. The second approach is to apply the power transformation to thecontingency ratios, that is the values in the table relative to expected values based on the marginals this method converges to weighted log-ratio analysis, or the spectral map. Two applications are described: first, a matrix of population genetic data which is inherently two-dimensional, and second, a larger cross-tabulation with higher dimensionality, from a linguistic analysis of several books.

Dynamic perceptual mapping

Perceptual maps have been used for decades by market researchers to illuminatethem about the similarity between brands in terms of a set of attributes, to position consumersrelative to brands in terms of their preferences, or to study how demographic and psychometricvariables relate to consumer choice. Invariably these maps are two-dimensional and static. Aswe enter the era of electronic publishing, the possibilities for dynamic graphics are opening up.We demonstrate the usefulness of introducing motion into perceptual maps through fourexamples. The first example shows how a perceptual map can be viewed in three dimensions,and the second one moves between two analyses of the data that were collected according todifferent protocols. In a third example we move from the best view of the data at the individuallevel to one which focuses on between-group differences in aggregated data. A final exampleconsiders the case when several demographic variables or market segments are available foreach respondent, showing an animation with increasingly detailed demographic comparisons.These examples of dynamic maps use several data sets from marketing and social scienceresearch.

Biased quantitative measurement of interval ordered homothetic preferences

We represent interval ordered homothetic preferences with a quantitative homothetic utility function and a multiplicative bias. When preferences are weakly ordered (i.e. when indifference is transitive), such a bias equals 1. When indifference is intransitive, the biasing factor is a positive function smaller than 1 and measures a threshold of indifference. We show that the bias is constant if and only if preferences are semiordered, and we identify conditions ensuring a linear utility function. We illustrate our approach with indifference sets on a two dimensional commodity space.

Amyloid and non-amyloid forms of 5q31-linked corneal dystrophy resulting from kerato-epithelin mutations at Arg-124 are associated with abnormal turnover of the protein.

Mutations in kerato-epithelin are responsible for a group of hereditary cornea-specific deposition diseases, 5q31-linked corneal dystrophies. These conditions are characterized by progressive accumulation of protein deposits of different ultrastructure. Herein, we studied the corneas with mutations at kerato-epithelin residue Arg-124 resulting in amyloid (R124C), non-amyloid (R124L), and a mixed pattern of deposition (R124H). We found that aggregated kerato-epithelin comprised all types of pathological deposits. Each mutation was associated with characteristic changes of protein turnover in corneal tissue. Amyloidogenesis in R124C corneas was accompanied by the accumulation of N-terminal kerato-epithelin fragments, whereby species of 44 kDa were the major constituents of amyloid fibrils. R124H corneas with prevailing non-amyloid inclusions showed accumulation of a new 66-kDa species altogether with the full-size 68-kDa form. Finally, in R124L cornea with non amyloid deposits, we found only the accumulation of the 68-kDa form. Two-dimensional gels revealed mutation-specific changes in the processing of the full-size protein in all affected corneas. It appears that substitutions at the same residue (Arg-124) result in cornea-specific deposition of kerato-epithelin via distinct aggregation pathways each involving altered turnover of the protein in corneal tissue.