Influence of structural heterogeneities and of large scale topography on imbricate gravitational rock slope failures: New insights from 3-D physical modeling and geomorphological analysis

Initial topography and inherited structural discontinuities are known to play a dominant role in rock slope stability. Previous 2-D physical modeling results demonstrated that even if few preexisting fractures are activated/propagated during gravitational failure all of those heterogeneities had a great influence on mobilized volume and its kinematics. The question we address in the present study is to determine if such a result is also observed in 3-D. As in 2-D previous models we examine geologically stable model configuration, based upon the well documented landslide at Randa, Switzerland. The 3-D models consisted of a homogeneous material in which several fracture zones were introduced in order to study simplified but realistic configurations of discontinuities (e.g. based on natural example rather than a parametric study). Results showed that the type of gravitational failure (deep-seated landslide or sequential failure) and resulting slope morphology evolution are the result of the interplay of initial topography and inherited preexisting fractures (orientation and density). The three main results are i) the initial topography exerts a strong control on gravitational slope failure. Indeed in each tested configuration (even in the isotropic one without fractures) the model is affected by a rock slide, ii) the number of simulated fracture sets greatly influences the volume mobilized and its kinematics, and iii) the failure zone involved in the 1991 event is smaller than the results produced by the analog modeling. This failure may indicate that the zone mobilized in 1991 is potentially only a part of a larger deep-seated landslide and/or wider deep seated gravitational slope deformation.

Neuroprotection in cerebral ischemia with XG-102, a new peptide inhibitor of JNK

Abstract Stroke or cerebrovascular accident, whose great majority is of ischemic nature, is the third leading cause of mortality and long lasting disability in industrialised countries. Resulting from the loss of blood supply to the brain depriving cerebral tissues of oxygen and glucose, it induces irreversible neuronal damages. Despite the large amount of research carried out into the causes and pathogenic features of cerebral ischemia the progress toward effective treatments has been poor. Apart the clot-busting drug tissue-type plasminogen activator (tPA) as effective therapy for acute stroke (reperfusion by thrombolysis) but limited to a low percentage of patients, there are currently no other approved medical treatments. The need for new therapy strategies is therefore imperative. Neuronal death in cerebral ischemia is among others due to excitotoxic mechanisms very early after stroke onset. One of the main involved molecular pathways leading to excitotoxic cell death is the c-Jun NH2-terminal kinase (JNK) pathway. Several studies have already shown the efficacy of a neuroprotective agent of a new type, a dextrogyre peptide synthesized in the retro inverso form (XG102, formerly D-JNKI1), which is protease-resistant and cell-penetrating and that selectively and strongly blocks the access of JNK to many of its targets. A powerful protection was observed with this compound in several models of ischemia (Borsello et al. 2003;Hirt et al. 2004). This chimeric compound, made up of a 10 amino acid TAT transporter sequence followed by a 20 amino acids JNK binding domain (JBD) sequence from JNK inhibitor protein (JIP) molecule, induced both a major reduction in lesion size and improved functional outcome. Moreover it presents a wide therapeutic window. XG-102 has proved its powerful efficacy in an occlusion model of middle cerebral artery in mice with intracérebroventricular (i.c.v.) injection but in order to be able to consider the development of this drug for human ischemic stroke it was therefore necessary to determine the feasibility of its systemic administration. The studies being the subject of this thesis made it possible to show a successful neuroprotection with XG-102 administered systemically after transient mouse middle cerebral artery occlusion (MCAo). Moreover our data. provided information about the feasibility to combine XG-102 with tPA without detrimental action on cell survival. By combining the benefits from a reperfusion treatment with the effects of a neuroprotective compound, it would represent the advantage of bringing better chances to protect the cerebral tissue. Résumé L'attaque cérébrale ou accident vasculaire cérébral, dont la grande majorité est de nature ischémique, constitue la troisième cause de mortalité et d'infirmité dans les pays industrialisés. Résultant de la perte d'approvisionnement de sang au cerveau privant les tissus cérébraux d'oxygène et de glucose, elle induit des dommages neuronaux irréversibles. En dépit du nombre élevé de recherches effectuées pour caractériser les mécanismes pathogènes de l'ischémie. cérébrale, les progrès vers des traitements efficaces restent pauvres. Excepté l'activateur tissulaire du plasminogène (tPA) dont le rôle est de désagréger les caillots sanguins et employé comme thérapie efficace contre l'attaque cérébrale aiguë (reperfusion par thrombolyse) mais limité à un faible pourcentage de patients, il n'y a actuellement aucun autre traitement médical approuvé. Le besoin de nouvelles stratégies thérapeutiques est par conséquent impératif. La mort neuronale dans l'ischémie cérébrale est entre autres due à des mécanismes excitotoxiques survenant rapidement après le début de l'attaque cérébrale. Une des principales voies moléculaires impliquée conduisant à la mort excitotoxique des cellules est la voie de la c-Jun NH2terminal kinase (JNK). Plusieurs études ont déjà montré l'efficacité d'un agent neuroprotecteur d'un nouveau type, un peptide dextrogyre synthétisé sous la forme retro inverso (XG-102, précédemment D-JNKI1) résistant aux protéases, capable de pénétrer dans les cellules et de bloquer sélectivement et fortement l'accès de JNK à plusieurs de ses cibles. Une puissante protection a été observée avec ce composé dans plusieurs modèles d'ischémie (Borsello et al. 2003;Hirt et al. 2004). Ce composé chimérique, construit à partir d'une séquence TAT de 10 acides aminés suivie par une séquence de 20 acides aminés d'un domaine liant JNK (JBD) issu de la molécule JNK protéine inhibitrice. (JIP), induit à la fois une réduction importante de la taille de lésion et un comportement fonctionnel amélioré. De plus il présente une fenêtre thérapeutique étendue. XG-102 a prouvé sa puissante efficacité dans un modèle d'occlusion de l'artère cérébrale moyenne chez la souris avec injection intracerebroventriculaire (i.c.v.) mais afin de pouvoir envisager le développement de ce composé pour l'attaque cérébrale chez l'homme, il était donc nécessaire de déterminer la faisabilité de son administration systémique. Les études faisant l'objet de cette thèse ont permis de montrer une neuroprotection importante avec XG-102 administré de façon systémique après l'occlusion transitoire de l'artère cérébrale moyenne chez la souris (MCAo). De plus nos données ont fourni des informations quant à la faisabilité de combiner XG-102 et tPA, démontrant une protection efficace par XG-102 malgré l'action nuisible du tPA sur la survie des cellules. En combinant les bénéfices de la reperfusion avec les effets d'un composé neurooprotecteur, cela représenterait l'avantage d'apporter des meilleures chances de protéger le tissu cérébral.

Application of the european customer satisfaction index to postal services. Structural equation models versus partial least squars

Customer satisfaction and retention are key issues for organizations in today’s competitive market place. As such, much research and revenue has been invested in developing accurate ways of assessing consumer satisfaction at both the macro (national) and micro (organizational) level, facilitating comparisons in performance both within and between industries. Since the instigation of the national customer satisfaction indices (CSI), partial least squares (PLS) has been used to estimate the CSI models in preference to structural equation models (SEM) because they do not rely on strict assumptions about the data. However, this choice was based upon some misconceptions about the use of SEM’s and does not take into consideration more recent advances in SEM, including estimation methods that are robust to non-normality and missing data. In this paper, both SEM and PLS approaches were compared by evaluating perceptions of the Isle of Man Post Office Products and Customer service using a CSI format. The new robust SEM procedures were found to be advantageous over PLS. Product quality was found to be the only driver of customer satisfaction, while image and satisfaction were the only predictors of loyalty, thus arguing for the specificity of postal services

Pédiatrie 1. Formule Quadratique: une nouveauté pédiatrique et pratique pour estimer le taux de filtration glomérulaire [Quadratic formula: a new pediatric advance for glomerular filtration rate estimation].

A new formula for glomerular filtration rate estimation in pediatric population from 2 to 18 years has been developed by the University Unit of Pediatric Nephrology. This Quadratic formula, accessible online, allows pediatricians to adjust drug dosage and/or follow-up renal function more precisely and in an easy manner.

Towards a new combination therapy for tuberculosis with next generation benzothiazinones.

The benzothiazinone lead compound, BTZ043, kills Mycobacterium tuberculosis by inhibiting the essential flavo-enzyme DprE1, decaprenylphosphoryl-beta-D-ribose 2-epimerase. Here, we synthesized a new series of piperazine-containing benzothiazinones (PBTZ) and show that, like BTZ043, the preclinical candidate PBTZ169 binds covalently to DprE1. The crystal structure of the DprE1-PBTZ169 complex reveals formation of a semimercaptal adduct with Cys387 in the active site and explains the irreversible inactivation of the enzyme. Compared to BTZ043, PBTZ169 has improved potency, safety and efficacy in zebrafish and mouse models of tuberculosis (TB). When combined with other TB drugs, PBTZ169 showed additive activity against M. tuberculosis in vitro except with bedaquiline (BDQ) where synergy was observed. A new regimen comprising PBTZ169, BDQ and pyrazinamide was found to be more efficacious than the standard three drug treatment in a murine model of chronic disease. PBTZ169 is thus an attractive drug candidate to treat TB in humans.

Development and validation of AMANDA, a new algorithm for selecting highly relevant regions in Molecular Interaction Fields

Descriptors based on Molecular Interaction Fields (MIF) are highly suitable for drug discovery, but their size (thousands of variables) often limits their application in practice. Here we describe a simple and fast computational method that extracts from a MIF a handful of highly informative points (hot spots) which summarize the most relevant information. The method was specifically developed for drug discovery, is fast, and does not require human supervision, being suitable for its application on very large series of compounds. The quality of the results has been tested by running the method on the ligand structure of a large number of ligand-receptor complexes and then comparing the position of the selected hot spots with actual atoms of the receptor. As an additional test, the hot spots obtained with the novel method were used to obtain GRIND-like molecular descriptors which were compared with the original GRIND. In both cases the results show that the novel method is highly suitable for describing ligand-receptor interactions and compares favorably with other state-of-the-art methods.

Synthesis, binding affinity and SAR of new benzolactam derivatives as dopamine D3 receptor ligands

A series of new benzolactam derivatives was synthesized and the derivatives were evaluated for theiraffinities at the dopamine D1, D2, and D3 receptors. Some of these compounds showed high D2 and/orD3 affinity and selectivity over the D1 receptor. The SAR study of these compounds revealed structuralcharacteristics that decisively influenced their D2 and D3 affinities. Structural models of the complexesbetween some of the most representative compounds of this series and the D2 and D3 receptors wereobtained with the aim of rationalizing the observed experimental results. Moreover, selected compoundsshowed moderate binding affinity on 5-HT2A which could contribute to reducing the occurrence of extrapyramidalside effects as potential antipsychotics.

Concise reviews: in vitro-produced pancreas organogenesis models in three dimensions: self-organization from few stem cells or progenitors.

Three-dimensional models of organ biogenesis have recently flourished. They promote a balance between stem/progenitor cell expansion and differentiation without the constraints of flat tissue culture vessels, allowing for autonomous self-organization of cells. Such models allow the formation of miniature organs in a dish and are emerging for the pancreas, starting from embryonic progenitors and adult cells. This review focuses on the currently available systems and how these allow new types of questions to be addressed. We discuss the expected advancements including their potential to study human pancreas development and function as well as to develop diabetes models and therapeutic cells.

Fading models and metrics for contemporary wireless systems

The purpose of this paper is to examine (1) some of the models commonly used to represent fading,and (2) the information-theoretic metrics most commonly used to evaluate performance over those models. We raise the question of whether these models and metrics remain adequate in light of the advances that wireless systems haveundergone over the last two decades. Weaknesses are pointedout, and ideas on possible fixes are put forth.

Identification of a new murine tumor necrosis factor receptor locus that contains two novel murine receptors for tumor necrosis factor-related apoptosis-inducing ligand (TRAIL).

Tumor necrosis factor (TNF) ligand and receptor superfamily members play critical roles in diverse developmental and pathological settings. In search for novel TNF superfamily members, we identified a murine chromosomal locus that contains three new TNF receptor-related genes. Sequence alignments suggest that the ligand binding regions of these murine TNF receptor homologues, mTNFRH1, -2 and -3, are most homologous to those of the tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) receptors. By using a number of in vitro ligand-receptor binding assays, we demonstrate that mTNFRH1 and -2, but not mTNFRH3, bind murine TRAIL, suggesting that they are indeed TRAIL receptors. This notion is further supported by our demonstration that both mTNFRH1:Fc and mTNFRH2:Fc fusion proteins inhibited mTRAIL-induced apoptosis of Jurkat cells. Unlike the only other known murine TRAIL receptor mTRAILR2, however, neither mTNFRH2 nor mTNFRH3 has a cytoplasmic region containing the well characterized death domain motif. Coupled with our observation that overexpression of mTNFRH1 and -2 in 293T cells neither induces apoptosis nor triggers NFkappaB activation, we propose that the mTnfrh1 and mTnfrh2 genes encode the first described murine decoy receptors for TRAIL, and we renamed them mDcTrailr1 and -r2, respectively. Interestingly, the overall sequence structures of mDcTRAILR1 and -R2 are quite distinct from those of the known human decoy TRAIL receptors, suggesting that the presence of TRAIL decoy receptors represents a more recent evolutionary event.

An evaluation of new parsimony-based versus parametric inference methods in biogeography: a case study using the globally distributed plant family Sapindaceae

Aim  Recently developed parametric methods in historical biogeography allow researchers to integrate temporal and palaeogeographical information into the reconstruction of biogeographical scenarios, thus overcoming a known bias of parsimony-based approaches. Here, we compare a parametric method, dispersal-extinction-cladogenesis (DEC), against a parsimony-based method, dispersal-vicariance analysis (DIVA), which does not incorporate branch lengths but accounts for phylogenetic uncertainty through a Bayesian empirical approach (Bayes-DIVA). We analyse the benefits and limitations of each method using the cosmopolitan plant family Sapindaceae as a case study.Location  World-wide.Methods  Phylogenetic relationships were estimated by Bayesian inference on a large dataset representing generic diversity within Sapindaceae. Lineage divergence times were estimated by penalized likelihood over a sample of trees from the posterior distribution of the phylogeny to account for dating uncertainty in biogeographical reconstructions. We compared biogeographical scenarios between Bayes-DIVA and two different DEC models: one with no geological constraints and another that employed a stratified palaeogeographical model in which dispersal rates were scaled according to area connectivity across four time slices, reflecting the changing continental configuration over the last 110 million years.Results  Despite differences in the underlying biogeographical model, Bayes-DIVA and DEC inferred similar biogeographical scenarios. The main differences were: (1) in the timing of dispersal events - which in Bayes-DIVA sometimes conflicts with palaeogeographical information, and (2) in the lower frequency of terminal dispersal events inferred by DEC. Uncertainty in divergence time estimations influenced both the inference of ancestral ranges and the decisiveness with which an area can be assigned to a node.Main conclusions  By considering lineage divergence times, the DEC method gives more accurate reconstructions that are in agreement with palaeogeographical evidence. In contrast, Bayes-DIVA showed the highest decisiveness in unequivocally reconstructing ancestral ranges, probably reflecting its ability to integrate phylogenetic uncertainty. Care should be taken in defining the palaeogeographical model in DEC because of the possibility of overestimating the frequency of extinction events, or of inferring ancestral ranges that are outside the extant species ranges, owing to dispersal constraints enforced by the model. The wide-spanning spatial and temporal model proposed here could prove useful for testing large-scale biogeographical patterns in plants.

Generalized linear and generalized additive models in studies of species distributions: setting the scene

An important statistical development of the last 30 years has been the advance in regression analysis provided by generalized linear models (GLMs) and generalized additive models (GAMs). Here we introduce a series of papers prepared within the framework of an international workshop entitled: Advances in GLMs/GAMs modeling: from species distribution to environmental management, held in Riederalp, Switzerland, 6-11 August 2001.We first discuss some general uses of statistical models in ecology, as well as provide a short review of several key examples of the use of GLMs and GAMs in ecological modeling efforts. We next present an overview of GLMs and GAMs, and discuss some of their related statistics used for predictor selection, model diagnostics, and evaluation. Included is a discussion of several new approaches applicable to GLMs and GAMs, such as ridge regression, an alternative to stepwise selection of predictors, and methods for the identification of interactions by a combined use of regression trees and several other approaches. We close with an overview of the papers and how we feel they advance our understanding of their application to ecological modeling.

Towards robust network based complex systems : from evolutionary cellular automata to biological models

Abstract Sitting between your past and your future doesn't mean you are in the present. Dakota Skye Complex systems science is an interdisciplinary field grouping under the same umbrella dynamical phenomena from social, natural or mathematical sciences. The emergence of a higher order organization or behavior, transcending that expected of the linear addition of the parts, is a key factor shared by all these systems. Most complex systems can be modeled as networks that represent the interactions amongst the system's components. In addition to the actual nature of the part's interactions, the intrinsic topological structure of underlying network is believed to play a crucial role in the remarkable emergent behaviors exhibited by the systems. Moreover, the topology is also a key a factor to explain the extraordinary flexibility and resilience to perturbations when applied to transmission and diffusion phenomena. In this work, we study the effect of different network structures on the performance and on the fault tolerance of systems in two different contexts. In the first part, we study cellular automata, which are a simple paradigm for distributed computation. Cellular automata are made of basic Boolean computational units, the cells; relying on simple rules and information from- the surrounding cells to perform a global task. The limited visibility of the cells can be modeled as a network, where interactions amongst cells are governed by an underlying structure, usually a regular one. In order to increase the performance of cellular automata, we chose to change its topology. We applied computational principles inspired by Darwinian evolution, called evolutionary algorithms, to alter the system's topological structure starting from either a regular or a random one. The outcome is remarkable, as the resulting topologies find themselves sharing properties of both regular and random network, and display similitudes Watts-Strogtz's small-world network found in social systems. Moreover, the performance and tolerance to probabilistic faults of our small-world like cellular automata surpasses that of regular ones. In the second part, we use the context of biological genetic regulatory networks and, in particular, Kauffman's random Boolean networks model. In some ways, this model is close to cellular automata, although is not expected to perform any task. Instead, it simulates the time-evolution of genetic regulation within living organisms under strict conditions. The original model, though very attractive by it's simplicity, suffered from important shortcomings unveiled by the recent advances in genetics and biology. We propose to use these new discoveries to improve the original model. Firstly, we have used artificial topologies believed to be closer to that of gene regulatory networks. We have also studied actual biological organisms, and used parts of their genetic regulatory networks in our models. Secondly, we have addressed the improbable full synchronicity of the event taking place on. Boolean networks and proposed a more biologically plausible cascading scheme. Finally, we tackled the actual Boolean functions of the model, i.e. the specifics of how genes activate according to the activity of upstream genes, and presented a new update function that takes into account the actual promoting and repressing effects of one gene on another. Our improved models demonstrate the expected, biologically sound, behavior of previous GRN model, yet with superior resistance to perturbations. We believe they are one step closer to the biological reality.

Prime Property Institutions for a Subprime Era: Exploring Innovative Models of Residential Development and Finance

This paper breaks new ground toward contractual and institutional innovation in models of homeownership, equity building, and mortgage enforcement. Inspired by recent developments in the affordable housing sector and in other types of public financing schemes, this paper suggests extending institutional and financial strategies such as timeand place-based division of property rights, conditional subsidies, and credit mediation to alleviate the systemic risks of mortgage foreclosure. Alongside a for-profit shared equity scheme that would be led by local governments, we also outline a private market shared equity model, one of bootstrapping home buying with purchase options.