Conditioning of stochastic 3-D fracture networks to hydrological and geophysical data

The geometry and connectivity of fractures exert a strong influence on the flow and transport properties of fracture networks. We present a novel approach to stochastically generate three-dimensional discrete networks of connected fractures that are conditioned to hydrological and geophysical data. A hierarchical rejection sampling algorithm is used to draw realizations from the posterior probability density function at different conditioning levels. The method is applied to a well-studied granitic formation using data acquired within two boreholes located 6 m apart. The prior models include 27 fractures with their geometry (position and orientation) bounded by information derived from single-hole ground-penetrating radar (GPR) data acquired during saline tracer tests and optical televiewer logs. Eleven cross-hole hydraulic connections between fractures in neighboring boreholes and the order in which the tracer arrives at different fractures are used for conditioning. Furthermore, the networks are conditioned to the observed relative hydraulic importance of the different hydraulic connections by numerically simulating the flow response. Among the conditioning data considered, constraints on the relative flow contributions were the most effective in determining the variability among the network realizations. Nevertheless, we find that the posterior model space is strongly determined by the imposed prior bounds. Strong prior bounds were derived from GPR measurements and helped to make the approach computationally feasible. We analyze a set of 230 posterior realizations that reproduce all data given their uncertainties assuming the same uniform transmissivity in all fractures. The posterior models provide valuable statistics on length scales and density of connected fractures, as well as their connectivity. In an additional analysis, effective transmissivity estimates of the posterior realizations indicate a strong influence of the DFN structure, in that it induces large variations of equivalent transmissivities between realizations. The transmissivity estimates agree well with previous estimates at the site based on pumping, flowmeter and temperature data.

Camallanus tridentatus (Drasche) (Nematoda: Camallanidae): new taxonomically important morphological data

Camallanus tridentatus is redescribed on the basis of the examination of specimens obtained from the stomach, caeca and intestine of the naturally infected arapaima Arapaima gigas (Schinz) from the Mexiana Island, Amazon River Delta, Brazil. Data on the surface morphology of adults inferred from confocal laser scanning and scanning electron microscopical observations are also provided. The study revealed some taxonomically important, previously unreported morphological features in this species, such as the presence of the poorly sclerotized left spicule and deirids. C. tridentatus distinctly differs from other congeneric species parasitizing freshwater fishes in South America mainly in the structure of the buccal capsule and the female caudal end. C. maculatus Martins, Garcia, Piazza and Ghiraldelli is considered a junior synonymm of Camallanus cotti Fujita.

Coherent forecasting of multiple-decrement life tables: a test using Japanese cause of death data

Planners in public and private institutions would like coherent forecasts of the components of age-specic mortality, such as causes of death. This has been di cult toachieve because the relative values of the forecast components often fail to behave ina way that is coherent with historical experience. In addition, when the group forecasts are combined the result is often incompatible with an all-groups forecast. It hasbeen shown that cause-specic mortality forecasts are pessimistic when compared withall-cause forecasts (Wilmoth, 1995). This paper abandons the conventional approachof using log mortality rates and forecasts the density of deaths in the life table. Sincethese values obey a unit sum constraint for both conventional single-decrement life tables (only one absorbing state) and multiple-decrement tables (more than one absorbingstate), they are intrinsically relative rather than absolute values across decrements aswell as ages. Using the methods of Compositional Data Analysis pioneered by Aitchison(1986), death densities are transformed into the real space so that the full range of multivariate statistics can be applied, then back-transformed to positive values so that theunit sum constraint is honoured. The structure of the best-known, single-decrementmortality-rate forecasting model, devised by Lee and Carter (1992), is expressed incompositional form and the results from the two models are compared. The compositional model is extended to a multiple-decrement form and used to forecast mortalityby cause of death for Japan

Compositional data and Simpson's paradox

Simpson's paradox, also known as amalgamation or aggregation paradox, appears whendealing with proportions. Proportions are by construction parts of a whole, which canbe interpreted as compositions assuming they only carry relative information. TheAitchison inner product space structure of the simplex, the sample space of compositions, explains the appearance of the paradox, given that amalgamation is a nonlinearoperation within that structure. Here we propose to use balances, which are specificelements of this structure, to analyse situations where the paradox might appear. Withthe proposed approach we obtain that the centre of the tables analysed is a naturalway to compare them, which avoids by construction the possibility of a paradox.Key words: Aitchison geometry, geometric mean, orthogonal projection

Estimation of the lateral correlation structure of subsurface water content from surface-based ground-penetrating radar reflection images

Over the past decade, significant interest has been expressed in relating the spatial statistics of surface-based reflection ground-penetrating radar (GPR) data to those of the imaged subsurface volume. A primary motivation for this work is that changes in the radar wave velocity, which largely control the character of the observed data, are expected to be related to corresponding changes in subsurface water content. Although previous work has indeed indicated that the spatial statistics of GPR images are linked to those of the water content distribution of the probed region, a viable method for quantitatively analyzing the GPR data and solving the corresponding inverse problem has not yet been presented. Here we address this issue by first deriving a relationship between the 2-D autocorrelation of a water content distribution and that of the corresponding GPR reflection image. We then show how a Bayesian inversion strategy based on Markov chain Monte Carlo sampling can be used to estimate the posterior distribution of subsurface correlation model parameters that are consistent with the GPR data. Our results indicate that if the underlying assumptions are valid and we possess adequate prior knowledge regarding the water content distribution, in particular its vertical variability, this methodology allows not only for the reliable recovery of lateral correlation model parameters but also for estimates of parameter uncertainties. In the case where prior knowledge regarding the vertical variability of water content is not available, the results show that the methodology still reliably recovers the aspect ratio of the heterogeneity.

Universal features of personality traits from the observer's perspective: Data from 50 cultures

To test hypotheses about the universality of personality traits, college students in 50 cultures identified an adult or college-aged man or woman whom they knew well and rated the 11,985 targets using the 3rd-person version of the Revised NEO Personality Inventory. Factor analyses within cultures showed that the normative American self-report structure was clearly replicated in most cultures and was recognizable in all. Sex differences replicated earlier self-report results, with the most pronounced differences in Western cultures. Cross-sectional age differences for 3 factors followed the pattern identified in self-reports, with moderate rates of change during college age and slower changes after age 40. With a few exceptions, these data support the hypothesis that features of personality traits are common to all human groups.

Structural components in functional data

Analyzing functional data often leads to finding common factors, for which functional principal component analysis proves to be a useful tool to summarize and characterize the random variation in a function space. The representation in terms of eigenfunctions is optimal in the sense of L-2 approximation. However, the eigenfunctions are not always directed towards an interesting and interpretable direction in the context of functional data and thus could obscure the underlying structure. To overcome such difficulty, an alternative to functional principal component analysis is proposed that produces directed components which may be more informative and easier to interpret. These structural components are similar to principal components, but are adapted to situations in which the domain of the function may be decomposed into disjoint intervals such that there is effectively independence between intervals and positive correlation within intervals. The approach is demonstrated with synthetic examples as well as real data. Properties for special cases are also studied.

Biochemical characterization of recombinant human telomerase

Résumé Les télomères sont les structures ADN-protéines des extrémités des chromosomes des eucaryotes. L'ADN télomérique est constitué de courtes séquences répétitives. L'intégrité des télomères est essentielle pour protéger les extrémités des chromosomes contre les systèmes de dégradations et pour les distinguer des cassures de l'ADN double brin. Parce que la machinerie de la réplication de l'ADN n'est pas capable de répliquer l'extrémité des chromosomes, les télomères raccourcissent au fur et à mesure des cycles de réplication. Dès que les télomères atteignent une longueur critique, leur structure protectrice est perdue. Cela induit un signal de dommage de l'ADN et l'arrêt du cycle cellulaire. Pour contrebalancer le raccourcissement des télomères, les cellules qui s'auto régénèrent, dont les cellules de la moelle osseuse, les lymphocytes activés et 80-90% des cellules cancéreuses, expriment la télomérase. C'est une ribonucléoprotéine qui a la capacité de synthétiser des séquences télomériques par transcription inverse d'une courte séquence contenue dans sa propre sous-unité ARN avec laquelle elle est associée. La télomérase humaine est une enzyme processive au niveau de l'addition des nucléotides et aussi des répétitions télomériques. La télomérase de levure et la télomérase humaine sont toutes deux dimériques et il a été montré que la télomérase humaine recombinante contient deux ARN qui coopèrent pour fonctionner ainsi que deux sous-unités catalytiques. Cependant, il n'a pas encore été montré quel est le rôle de la dimérisation dans l'activité de la télomérase. Afin d'élucider ce rôle, nous avons exprimé, reconstitué et purifié la télomérase humaine dimérique recombinante. Et pour étudier l'effet d'ARN mutants sur l'activité de la télomérase, nous avons développé une méthode pour reconstituer et enrichir en hétérodimères de télomérase. Les hétérodimères contiennent une sous-unité ARN sauvage et une sous-unité ARN mutée au niveau de la séquence de la matrice. Sur l'ARN muté nous avons introduit une étiquette aptamer ARN-S1 puis nous avons purifié la télomérase via l'etiquette Si. Nous avons montré que la dimérisation est essentielle pour l'activité de la télomérase. Nos données indiquent que chaque télomérase du dimère allonge leur substrat, l'ADN télomérique, indépendamment l'une de l'autre à chaque cycle d'élongation mais que l'addition itérative de répétitions télomériques nécessite une coopération entre les deux télomérases du dimère. Nous proposons donc un modèle dans lequel les deux télomérases du dimères se lient et allongent deux substrats télomères et que pendant l'élongation processive les deux enzymes subissent un changement de conformation de manière coordonnée, ce changement va permettre le repositionnement des substrats pour d'autres cycles d'additions de répétitions télomériques. Dyskeratosis congenita est une maladie mortelle due majoritairement au disfonctionnement de la moelle osseuse. Dans la forme autosomale de la maladie, l'ARN de la télomérase contient des mutations. En utilisant notre système de reconstitution, nous avons montré que ces ARN mutés, qui ont perdu leur activité enzymatique dans le cas d'un homodimère de mutants, sont dominant négatifs quand ils sont présents dans les hétérodimères sauvage/mutant. Cet effet trans-dominant négatif pourrait contribuer à la progression de la maladie. Abstract Telomeres are protein-DNA structures at the ends of linear eukaryotic chromosomes. The telomeric DNA consists of tandemly repeated sequences. Telomeric integrity is essential to protect chromosomal ends from nucleolytic degradation and to prevent their recognition as DNA double strand breaks. Due to the inability of the conventional DNA replication machinery to replicate terminal DNA stretches, telomeres shorten with continuous rounds of DNA replication. As soon as telomeres reach a critical length, their protective structure is lost and the deprotected telomeres will induce a DNA damage response leading to cell cycle arrest. To counteract telomere shortening, self-renewing cells, including bone marrow cells, activated lymphocytes and 80-90% of cancer cells express the cellular reverse transcriptase telomerase, which has the capacity to synthesize telomeric repeats by reverse transcription of a short template sequence encoded by its stably associated RNA subunit. Human telomerase is a processive enzyme for nucleotide as well as repeat addition. Both yeast and human telomerase are dimeric enzymes and recombinant human telomerase has been shown to contain two functionally cooperating RNAs and most probably also two protein subunits. However, it has remained unclear how dimerization may contribute to telomerase activity. To study the role of dimerization, we expressed, reconstituted and purified recombinant human telomerase. We also developed a new method to reconstitute and enrich for telomerase heterodimers containing wild-type (wt) and mutant telomerase RNA subunits. To this end we introduced an S1-RNA-aptamer tag into telomerase RNA and purified telomerase reconstituted with a mixture of untagged and tagged RNA via the S1-tag. Using this experimental system, we introduced template mutations in the tagged RNA subunit and examined the effect of mutant RNAs on wt telomerase activity in wt/mutant heterodimers. We obtained evidence that dimerization is essential for telomerase activity. Our data indicate that the two subunits elongate telomere substrates independently of each other during single rounds of elongation, but that iterative addition of telomeric repeats requires cooperation between the two subunits. We suggest a model, in which dimeric telomerases bind and elongate two telomere substrates and that the two subunits undergo coordinated conformational changes during processive elongation that enable repositioning the substrates for subsequent rounds of repeat addition. Dyskeratosis congenita is a multisystemic disease with bone marrow failure as the major cause of death. The autosomal form of this disease was found to harbor mutations in the telomerase RNA. Using our reconstitution system, we tested whether mutant dyskeratosis telomerase RNAs behaved in a dominant negative manner. We observed that dyskeratosis telomerase RNA mutants, which lacked enzymatic activity were dominant negative, when present in wt/ mutant heterodimers. The transdominant negative effect of these mutants may contribute to disease progression.

Forecasting changes in population genetic structure of alpine plants in response to global warming.

Species range shifts in response to climate and land use change are commonly forecasted with species distribution models based on species occurrence or abundance data. Although appealing, these models ignore the genetic structure of species, and the fact that different populations might respond in different ways because of adaptation to their environment. Here, we introduced ancestry distribution models, that is, statistical models of the spatial distribution of ancestry proportions, for forecasting intra-specific changes based on genetic admixture instead of species occurrence data. Using multi-locus genotypes and extensive geographic coverage of distribution data across the European Alps, we applied this approach to 20 alpine plant species considering a global increase in temperature from 0.25 to 4 °C. We forecasted the magnitudes of displacement of contact zones between plant populations potentially adapted to warmer environments and other populations. While a global trend of movement in a north-east direction was predicted, the magnitude of displacement was species-specific. For a temperature increase of 2 °C, contact zones were predicted to move by 92 km on average (minimum of 5 km, maximum of 212 km) and by 188 km for an increase of 4 °C (minimum of 11 km, maximum of 393 km). Intra-specific turnover-measuring the extent of change in global population genetic structure-was generally found to be moderate for 2 °C of temperature warming. For 4 °C of warming, however, the models indicated substantial intra-specific turnover for ten species. These results illustrate that, in spite of unavoidable simplifications, ancestry distribution models open new perspectives to forecast population genetic changes within species and complement more traditional distribution-based approaches.

Structure-based drug design studies of the interactions ofent-kaurane diterpenes derived from Wedelia paludosa with the Plasmodium falciparumsarco/endoplasmic reticulum Ca2+-ATPase PfATP6

Malaria is responsible for more deaths around the world than any other parasitic disease. Due to the emergence of strains that are resistant to the current chemotherapeutic antimalarial arsenal, the search for new antimalarial drugs remains urgent though hampered by a lack of knowledge regarding the molecular mechanisms of artemisinin resistance. Semisynthetic compounds derived from diterpenes from the medicinal plant Wedelia paludosawere tested in silico against the Plasmodium falciparumCa2+-ATPase, PfATP6. This protein was constructed by comparative modelling using the three-dimensional structure of a homologous protein, 1IWO, as a scaffold. Compound 21 showed the best docking scores, indicating a better interaction with PfATP6 than that of thapsigargin, the natural inhibitor. Inhibition of PfATP6 by diterpene compounds could promote a change in calcium homeostasis, leading to parasite death. These data suggest PfATP6 as a potential target for the antimalarial ent-kaurane diterpenes.

Markov chain montecarlo method applied to rounding zeros of compositional data: first approach

As stated in Aitchison (1986), a proper study of relative variation in a compositional data set should be based on logratios, and dealing with logratios excludes dealing with zeros. Nevertheless, it is clear that zero observations might be present in real data sets, either because the corresponding part is completelyabsent –essential zeros– or because it is below detection limit –rounded zeros. Because the second kind of zeros is usually understood as “a trace too small to measure”, it seems reasonable to replace them by a suitable small value, and this has been the traditional approach. As stated, e.g. by Tauber (1999) and byMartín-Fernández, Barceló-Vidal, and Pawlowsky-Glahn (2000), the principal problem in compositional data analysis is related to rounded zeros. One should be careful to use a replacement strategy that does not seriously distort the general structure of the data. In particular, the covariance structure of the involvedparts –and thus the metric properties– should be preserved, as otherwise further analysis on subpopulations could be misleading. Following this point of view, a non-parametric imputation method isintroduced in Martín-Fernández, Barceló-Vidal, and Pawlowsky-Glahn (2000). This method is analyzed in depth by Martín-Fernández, Barceló-Vidal, and Pawlowsky-Glahn (2003) where it is shown that thetheoretical drawbacks of the additive zero replacement method proposed in Aitchison (1986) can be overcome using a new multiplicative approach on the non-zero parts of a composition. The new approachhas reasonable properties from a compositional point of view. In particular, it is “natural” in the sense thatit recovers the “true” composition if replacement values are identical to the missing values, and it is coherent with the basic operations on the simplex. This coherence implies that the covariance structure of subcompositions with no zeros is preserved. As a generalization of the multiplicative replacement, in thesame paper a substitution method for missing values on compositional data sets is introduced

Comparative analysis of human and mouse expression data illuminates tissue-specific evolutionary patterns of miRNAs.

MicroRNAs (miRNAs) constitute an important class of gene regulators. While models have been proposed to explain their appearance and expansion, the validation of these models has been difficult due to the lack of comparative studies. Here, we analyze miRNA evolutionary patterns in two mammals, human and mouse, in relation to the age of miRNA families. In this comparative framework, we confirm some predictions of previously advanced models of miRNA evolution, e.g. that miRNAs arise more frequently de novo than by duplication, or that the number of protein-coding gene targeted by miRNAs decreases with evolutionary time. We also corroborate that miRNAs display an increase in expression level with evolutionary time, however we show that this relation is largely tissue-dependent, and especially low in embryonic or nervous tissues. We identify a bias of tag-sequencing techniques regarding the assessment of breadth of expression, leading us, contrary to predictions, to find more tissue-specific expression of older miRNAs. Together, our results refine the models used so far to depict the evolution of miRNA genes. They underline the role of tissue-specific selective forces on the evolution of miRNAs, as well as the potential co-evolution patterns between miRNAs and the protein-coding genes they target.

Extended family structure in the ant Formica paralugubris: the role of the breeding system

In populations of various ant species, many queens reproduce in the same nest (polygyny), and colony boundaries appear to be absent with individuals able to move fi eely between nests (unicoloniality). Such societies depart strongly from a simple family structure and pose a potential challenge to kin selection theory, because high queen number coupled with unrestricted gene flow among nests should result in levels of relatedness among nestmates close to zero. This study investigated the breeding system and genetic structure of a highly polygynous and largely unicolonial population of the wood ant Formica paralugubris. A microsatellite analysis revealed that nestmate workers, reproductive queens and reproductive males (the queens' mates) are all equally related to each other, with relatedness estimates centring around 0.14. This suggests that most of the queens and males reproducing in the study population had mated within or close to their natal nest, and that the queens did not disperse far after mating. We developed a theoretical model to investigate how the breeding system affects the relatedness structure of polygynous colonies. By combining the model and our empirical data, it was estimated that about 99.8% of the reproducing queens and males originated from within the nest, or from a nearby nest. This high rate of local mating and the rarity of long-distance dispersal maintain significant relatedness among nestmates, and contrast with the common view that unicoloniality is coupled with unrestricted gene flow among nests.

Possible solution of some essential zero problems in compositional data analysis

One of the tantalising remaining problems in compositional data analysis lies in how to deal with data sets in which there are components which are essential zeros. By anessential zero we mean a component which is truly zero, not something recorded as zero simply because the experimental design or the measuring instrument has not been sufficiently sensitive to detect a trace of the part. Such essential zeros occur inmany compositional situations, such as household budget patterns, time budgets,palaeontological zonation studies, ecological abundance studies. Devices such as nonzero replacement and amalgamation are almost invariably ad hoc and unsuccessful insuch situations. From consideration of such examples it seems sensible to build up amodel in two stages, the first determining where the zeros will occur and the secondhow the unit available is distributed among the non-zero parts. In this paper we suggest two such models, an independent binomial conditional logistic normal model and a hierarchical dependent binomial conditional logistic normal model. The compositional data in such modelling consist of an incidence matrix and a conditional compositional matrix. Interesting statistical problems arise, such as the question of estimability of parameters, the nature of the computational process for the estimation of both the incidence and compositional parameters caused by the complexity of the subcompositional structure, the formation of meaningful hypotheses, and the devising of suitable testing methodology within a lattice of such essential zero-compositional hypotheses. The methodology is illustrated by application to both simulated and real compositional data

Segmentation and grid generation for numerical simulations of vad connections with patient-specific data

Objectives: We are interested in the numerical simulation of the anastomotic region comprised between outflow canula of LVAD and the aorta. Segmenta¬tion, geometry reconstruction and grid generation from patient-specific data remain an issue because of the variable quality of DICOM images, in particular CT-scan (e.g. metallic noise of the device, non-aortic contrast phase). We pro¬pose a general framework to overcome this problem and create suitable grids for numerical simulations.Methods: Preliminary treatment of images is performed by reducing the level window and enhancing the contrast of the greyscale image using contrast-limited adaptive histogram equalization. A gradient anisotropic diffusion filter is applied to reduce the noise. Then, watershed segmentation algorithms and mathematical morphology filters allow reconstructing the patient geometry. This is done using the InsightToolKit library (www.itk.org). Finally the Vascular Model¬ing ToolKit (www.vmtk.org) and gmsh (www.geuz.org/gmsh) are used to create the meshes for the fluid (blood) and structure (arterial wall, outflow canula) and to a priori identify the boundary layers. The method is tested on five different patients with left ventricular assistance and who underwent a CT-scan exam.Results: This method produced good results in four patients. The anastomosis area is recovered and the generated grids are suitable for numerical simulations. In one patient the method failed to produce a good segmentation because of the small dimension of the aortic arch with respect to the image resolution.Conclusions: The described framework allows the use of data that could not be otherwise segmented by standard automatic segmentation tools. In particular the computational grids that have been generated are suitable for simulations that take into account fluid-structure interactions. Finally the presented method features a good reproducibility and fast application.