Alpine tectonic evolution of a Jurassic subduction-accretionary complex: Deformation, kinematics and 40Ar/39Ar age constraints on the Mesozoic low-grade schists of the Circum-Rhodope Belt in the eastern Rhodope-Thrace region, Bulgaria-Greece

Deformation of the Circum-Rhodope Belt Mesozoic (Middle Triassic to earliest Lower Cretaceous) low-grade schists underneath an arc-related ophiolitic magmatic suite and associated sedimentary successions in the eastern Rhodope-Thrace region occurred as a two-episode tectonic process: (i) Late Jurassic deformation of arc to margin units resulting from the eastern Rhodope-Evros arc-Rhodope terrane continental margin collision and accretion to that margin, and (ii) Middle Eocene deformation related to the Tertiary crustal extension and final collision resulting in the closure of the Vardar ocean south of the Rhodope terrane. The first deformational event D-1 is expressed by Late Jurassic NW-N vergent fold generations and the main and subsidiary planar-linear structures. Although overprinting, these structural elements depict uniform bulk north-directed thrust kinematics and are geometrically compatible with the increments of progressive deformation that develops in same greenschist-facies metamorphic grade. It followed the Early-Middle Jurassic magmatic evolution of the eastern Rhodope-Evros arc established on the upper plate of the southward subducting Maliac-Meliata oceanic lithosphere that established the Vardar Ocean in a supra-subduction back-arc setting. This first event resulted in the thrust-related tectonic emplacement of the Mesozoic schists in a supra-crustal level onto the Rhodope continental margin. This Late Jurassic-Early Cretaceous tectonic event related to N-vergent Balkan orogeny is well-constrained by geochronological data and traced at a regional-scale within distinct units of the Carpatho-Balkan Belt. Following subduction reversal towards the north whereby the Vardar Ocean was subducted beneath the Rhodope margin by latest Cretaceous times, the low-grade schists aquired a new position in the upper plate, and hence, the Mesozoic schists are lacking the Cretaceous S-directed tectono-metamorphic episode whose effects are widespread in the underlying high-grade basement. The subduction of the remnant Vardar Ocean located behind the colliding arc since the middle Cretaceous was responsible for its ultimate closure, Early Tertiary collision with the Pelagonian block and extension in the region caused the extensional collapse related to the second deformational event D-2. This extensional episode was experienced passively by the Mesozoic schists located in the hanging wall of the extensional detachments in Eocene times. It resulted in NE-SW oriented open folds representing corrugation antiforms of the extensional detachment surfaces, brittle faulting and burial history beneath thick Eocene sediments as indicated by 42.1-39.7 Ma Ar-40/Ar-39 mica plateau ages obtained in the study. The results provide structural constraints for the involvement components of Jurassic paleo-subduction zone in a Late Jurassic arc-continental margin collisional history that contributed to accretion-related crustal growth of the Rhodope terrane. (C) 2011 Elsevier Ltd. All rights reserved.

Artificial evolution on network structures : how time and space influence dynamics

Abstract The main objective of this work is to show how the choice of the temporal dimension and of the spatial structure of the population influences an artificial evolutionary process. In the field of Artificial Evolution we can observe a common trend in synchronously evolv¬ing panmictic populations, i.e., populations in which any individual can be recombined with any other individual. Already in the '90s, the works of Spiessens and Manderick, Sarma and De Jong, and Gorges-Schleuter have pointed out that, if a population is struc¬tured according to a mono- or bi-dimensional regular lattice, the evolutionary process shows a different dynamic with respect to the panmictic case. In particular, Sarma and De Jong have studied the selection pressure (i.e., the diffusion of a best individual when the only selection operator is active) induced by a regular bi-dimensional structure of the population, proposing a logistic modeling of the selection pressure curves. This model supposes that the diffusion of a best individual in a population follows an exponential law. We show that such a model is inadequate to describe the process, since the growth speed must be quadratic or sub-quadratic in the case of a bi-dimensional regular lattice. New linear and sub-quadratic models are proposed for modeling the selection pressure curves in, respectively, mono- and bi-dimensional regu¬lar structures. These models are extended to describe the process when asynchronous evolutions are employed. Different dynamics of the populations imply different search strategies of the resulting algorithm, when the evolutionary process is used to solve optimisation problems. A benchmark of both discrete and continuous test problems is used to study the search characteristics of the different topologies and updates of the populations. In the last decade, the pioneering studies of Watts and Strogatz have shown that most real networks, both in the biological and sociological worlds as well as in man-made structures, have mathematical properties that set them apart from regular and random structures. In particular, they introduced the concepts of small-world graphs, and they showed that this new family of structures has interesting computing capabilities. Populations structured according to these new topologies are proposed, and their evolutionary dynamics are studied and modeled. We also propose asynchronous evolutions for these structures, and the resulting evolutionary behaviors are investigated. Many man-made networks have grown, and are still growing incrementally, and explanations have been proposed for their actual shape, such as Albert and Barabasi's preferential attachment growth rule. However, many actual networks seem to have undergone some kind of Darwinian variation and selection. Thus, how these networks might have come to be selected is an interesting yet unanswered question. In the last part of this work, we show how a simple evolutionary algorithm can enable the emrgence o these kinds of structures for two prototypical problems of the automata networks world, the majority classification and the synchronisation problems. Synopsis L'objectif principal de ce travail est de montrer l'influence du choix de la dimension temporelle et de la structure spatiale d'une population sur un processus évolutionnaire artificiel. Dans le domaine de l'Evolution Artificielle on peut observer une tendence à évoluer d'une façon synchrone des populations panmictiques, où chaque individu peut être récombiné avec tout autre individu dans la population. Déjà dans les année '90, Spiessens et Manderick, Sarma et De Jong, et Gorges-Schleuter ont observé que, si une population possède une structure régulière mono- ou bi-dimensionnelle, le processus évolutionnaire montre une dynamique différente de celle d'une population panmictique. En particulier, Sarma et De Jong ont étudié la pression de sélection (c-à-d la diffusion d'un individu optimal quand seul l'opérateur de sélection est actif) induite par une structure régulière bi-dimensionnelle de la population, proposant une modélisation logistique des courbes de pression de sélection. Ce modèle suppose que la diffusion d'un individu optimal suit une loi exponentielle. On montre que ce modèle est inadéquat pour décrire ce phénomène, étant donné que la vitesse de croissance doit obéir à une loi quadratique ou sous-quadratique dans le cas d'une structure régulière bi-dimensionnelle. De nouveaux modèles linéaires et sous-quadratique sont proposés pour des structures mono- et bi-dimensionnelles. Ces modèles sont étendus pour décrire des processus évolutionnaires asynchrones. Différentes dynamiques de la population impliquent strategies différentes de recherche de l'algorithme résultant lorsque le processus évolutionnaire est utilisé pour résoudre des problèmes d'optimisation. Un ensemble de problèmes discrets et continus est utilisé pour étudier les charactéristiques de recherche des différentes topologies et mises à jour des populations. Ces dernières années, les études de Watts et Strogatz ont montré que beaucoup de réseaux, aussi bien dans les mondes biologiques et sociologiques que dans les structures produites par l'homme, ont des propriétés mathématiques qui les séparent à la fois des structures régulières et des structures aléatoires. En particulier, ils ont introduit la notion de graphe sm,all-world et ont montré que cette nouvelle famille de structures possède des intéressantes propriétés dynamiques. Des populations ayant ces nouvelles topologies sont proposés, et leurs dynamiques évolutionnaires sont étudiées et modélisées. Pour des populations ayant ces structures, des méthodes d'évolution asynchrone sont proposées, et la dynamique résultante est étudiée. Beaucoup de réseaux produits par l'homme se sont formés d'une façon incrémentale, et des explications pour leur forme actuelle ont été proposées, comme le preferential attachment de Albert et Barabàsi. Toutefois, beaucoup de réseaux existants doivent être le produit d'un processus de variation et sélection darwiniennes. Ainsi, la façon dont ces structures ont pu être sélectionnées est une question intéressante restée sans réponse. Dans la dernière partie de ce travail, on montre comment un simple processus évolutif artificiel permet à ce type de topologies d'émerger dans le cas de deux problèmes prototypiques des réseaux d'automates, les tâches de densité et de synchronisation.

Electron cryo-microscopy reveals mechanism of action of propranolol on artificial membranes.

The pharmacological activity of several amphiphilic drugs is often related to their ability to interact with biological membranes. Propranolol is an efficient multidrug resistance (MDR) modulator; it is a nonselective beta-blocker and is thought to reduce hypertension by decreasing the cardiac frequency and thus blood pressure. It is used in drug delivery studies in order to treat systemic hypertension. We are interested in the interaction of propranolol with artificial membranes, as liposomes of controllable size are used as biocompatible and protective structures to encapsulate labile molecules, such as proteins, nucleic acids or drugs, for pharmaceutical, cosmetic or chemical applications. We present here a study of the interaction of propranolol, a cationic surfactant, with pure egg phosphatidylcholine (EPC) vesicles. The gradual transition from liposome to micelle of EPC vesicles in the presence of propranolol was monitored by time-resolved electron cryo-microscopy (cryo-EM) under different experimental conditions. The liposome-drug interaction was studied with varying drug/lipid (D/L) ratios and different stages were captured by direct thin-film vitrification. The time-series cryo-EM data clearly illustrate the mechanism of action of propranolol on the liposome structure: the drug disrupts the lipid bilayer by perturbing the local organization of the phospholipids. This is followed by the formation of thread-like micelles, also called worm-like micelles (WLM), and ends with the formation of spherical (globular) micelles. The overall reaction is slow, with the process taking almost two hours to be completed. The effect of a monovalent salt was also investigated by repeating the lipid-surfactant interaction experiments in the presence of KCl as an additive to the lipid/drug suspension. When KCl was added in the presence of propranolol the overall reaction was the same but with slower kinetics, suggesting that this monovalent salt affects the general lipid-to-micelle transition by stabilizing the membrane, presumably by binding to the carbonyl chains of the phosphatidylcholine.

Wear of two artificial tooth materials in vivo: a 12-month pilot study.

STATEMENT OF PROBLEM: Wear of methacrylate artificial teeth resulting in vertical loss is a problem for both dentists and patients. PURPOSE: The purpose of this study was to quantify wear of artificial teeth in vivo and to relate it to subject and tooth variables. MATERIAL AND METHODS: Twenty-eight subjects treated with complete dentures received 2 artificial tooth materials (polymethyl methacrylate (PMMA)/double-cross linked PMMA fillers; 35%/59% (SR Antaris DCL, SR Postaris DCL); experimental 48%/46%). At baseline and after 12 months, impressions of the dentures were poured with improved stone. After laser scanning, the casts were superimposed and matched. Maximal vertical loss (mm) and volumetric loss (mm(3)) were calculated for each tooth and log-transformed to reduce variability. Volumetric loss was related to the occlusally active surface area. Linear mixed models were used to study the influence of the factors jaw, tooth, and material on adjusted (residual) wear values (alpha=.05). RESULTS: Due to drop outs (n=5) and unmatchable casts (n=3), 69% of all teeth were analyzed. Volumetric loss had a strong linear relationship to surface area (P<.001); this was less pronounced for vertical loss (P=.004). The factor showing the highest influence was the subject. Wear was tooth dependent (increasing from incisors to molars). However, these differences diminished once the wear rates were adjusted for occlusal area, and only a few remained significant (anterior versus posterior maxillary teeth). Another influencing factor was the age of the subject. CONCLUSIONS: Clinical wear of artificial teeth is higher than previously measured or expected. The presented method of analyzing wear of artificial teeth using a laser-scanning device seemed suitable.

Wavelet analysis residual kriging vs. neural network residual kriging

This paper deals with the problem of spatial data mapping. A new method based on wavelet interpolation and geostatistical prediction (kriging) is proposed. The method - wavelet analysis residual kriging (WARK) - is developed in order to assess the problems rising for highly variable data in presence of spatial trends. In these cases stationary prediction models have very limited application. Wavelet analysis is used to model large-scale structures and kriging of the remaining residuals focuses on small-scale peculiarities. WARK is able to model spatial pattern which features multiscale structure. In the present work WARK is applied to the rainfall data and the results of validation are compared with the ones obtained from neural network residual kriging (NNRK). NNRK is also a residual-based method, which uses artificial neural network to model large-scale non-linear trends. The comparison of the results demonstrates the high quality performance of WARK in predicting hot spots, reproducing global statistical characteristics of the distribution and spatial correlation structure.

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.

The meiosis-specific recombinase hDmc1 forms ring structures and interacts with hRad51.

Eukaryotic cells encode two homologs of Escherichia coli RecA protein, Rad51 and Dmc1, which are required for meiotic recombination. Rad51, like E.coli RecA, forms helical nucleoprotein filaments that promote joint molecule and heteroduplex DNA formation. Electron microscopy reveals that the human meiosis-specific recombinase Dmc1 forms ring structures that bind single-stranded (ss) and double-stranded (ds) DNA. The protein binds preferentially to ssDNA tails and gaps in duplex DNA. hDmc1-ssDNA complexes exhibit an irregular, often compacted structure, and promote strand-transfer reactions with homologous duplex DNA. hDmc1 binds duplex DNA with reduced affinity to form nucleoprotein complexes. In contrast to helical RecA/Rad51 filaments, however, Dmc1 filaments are composed of a linear array of stacked protein rings. Consistent with the requirement for two recombinases in meiotic recombination, hDmc1 interacts directly with hRad51.

Structural investigations into the interaction of hemoglobin and part structures with bacterial endotoxins.

An understanding of details of the interaction mechanisms of bacterial endotoxins (lipopolysaccharide, LPS) with the oxygen transport protein hemoglobin is still lacking, despite its high biological relevance. Here, a biophysical investigation into the endotoxin:hemoglobin interaction is presented which comprises the use of various rough mutant LPS as well as free lipid A; in addition to the complete hemoglobin molecule from fetal sheep extract, also the partial structure alpha-chain and the heme-free sample are studied. The investigations comprise the determination of the gel-to-liquid crystalline phase behaviour of the acyl chains of LPS, the ultrastructure (type of aggregate structure and morphology) of the endotoxins, and the incorporation of the hemoglobins into artificial immune cell membranes and into LPS. Our data suggest a model for the interaction between Hb and LPS in which hemoglobins do not react strongly with the hydrophilic or with the hydrophobic moiety of LPS, but with the complete endotoxin aggregate. Hb is able to incorporate into LPS with the longitudinal direction parallel to the lipid A double-layer. Although this does not lead to a strong disturbance of the LPS acyl chain packing, the change of the curvature leads to a slightly conical molecular shape with a change of the three-dimensional arrangement from unilamellar into cubic LPS aggregates. Our previous results show that cubic LPS structures exhibit strong endotoxic activity. The property of Hb on the physical state of LPS described here may explain the observation of an increase in LPS-mediating endotoxicity due to the action of Hb.

A general linear relaxometry model of R1 using imaging data.

PURPOSE: The longitudinal relaxation rate (R1 ) measured in vivo depends on the local microstructural properties of the tissue, such as macromolecular, iron, and water content. Here, we use whole brain multiparametric in vivo data and a general linear relaxometry model to describe the dependence of R1 on these components. We explore a) the validity of having a single fixed set of model coefficients for the whole brain and b) the stability of the model coefficients in a large cohort. METHODS: Maps of magnetization transfer (MT) and effective transverse relaxation rate (R2 *) were used as surrogates for macromolecular and iron content, respectively. Spatial variations in these parameters reflected variations in underlying tissue microstructure. A linear model was applied to the whole brain, including gray/white matter and deep brain structures, to determine the global model coefficients. Synthetic R1 values were then calculated using these coefficients and compared with the measured R1 maps. RESULTS: The model's validity was demonstrated by correspondence between the synthetic and measured R1 values and by high stability of the model coefficients across a large cohort. CONCLUSION: A single set of global coefficients can be used to relate R1 , MT, and R2 * across the whole brain. Our population study demonstrates the robustness and stability of the model. Magn Reson Med, 2014. © 2014 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals, Inc. Magn Reson Med 73:1309-1314, 2015. © 2014 Wiley Periodicals, Inc.

Is the relationship between major depressive disorder and self-reported alcohol use disorder an artificial one ?

AIMS: Many studies have suggested a close relationship between alcohol use disorder (AUD) and major depressive disorder (MDD). This study aimed to test whether the relationship between self-reported AUD and MDD was artificially strengthened by the diagnosis of MDD. This association was tested comparing relationships between alcohol use and AUD for depressive people and non-depressive people. METHODS: As part of the Cohort Study on Substance Use Risk Factors, 4352 male Swiss alcohol users in their early twenties answered questions concerning their alcohol use, AUD and MDD at two time points. Generalized linear models for cross-sectional and longitudinal associations were calculated. RESULTS: For cross-sectional associations, depressive participants reported a higher number of AUD symptoms (β = 0.743, P < 0.001) than non-depressive participants. Moreover, there was an interaction (β = -0.204, P = 0.001): the relationship between alcohol use and AUD was weaker for depressive participants rather than non-depressive participants. For longitudinal associations, there were almost no significant relationships between MDD at baseline and AUD at follow-up, but the interaction was still significant (β = -0.249, P < 0.001). CONCLUSION: MDD thus appeared to be a confounding variable in the relationship between alcohol use and AUD, and self-reported measures of AUD seemed to be overestimated by depressive people. This result brings into question the accuracy of self-reported measures of substance use disorders. Furthermore, it adds to the emerging debate about the usefulness of substance use disorder as a concept, when heavy substance use itself appears to be a sensitive and reliable indicator.