Evidence for middle Cretaceous accretion at Santa Elena Peninsula (Santa Rosa Accretionary Complex), Costa Rica

An oceanic assemblage of alkaline basalts, radiolarites and polymictic breccias forms the tectonic substratum of the Santa Elena Nappe, which is constituted by extensive outcrops of ultramafic and mafic rocks of the Santa Elena Peninsula (NW Costa Rica). The undulating basal contact of this nappe defines several half-windows along the south shores of the Santa Elena Peninsula. Lithologically it is constituted by vesicular pillowed and massive alkaline basaltic flows, alkaline sills, ribbon-bedded and knobby radiolarites, muddy tuffaceous and detrital turbidites, debris flows and polymictic breccias and megabreccias. Sediments and basalt flows show predominant subvertical dips and occur in packages separated by roughly bed-parallel thrust planes. Individual packages reveal a coherent internal stratigraphy that records younging to the east in all packages and shows rapid coarsening upwards of the detrital facies. Alkaline basalt flows, pillow breccias and sills within radiolarite successions are genetically related to a mid-Cretaceous submarine seamount. Detrital sedimentary facies range form distal turbidites to proximal debris flows and culminate in megabreccias related to collapse and mass wasting in an accretionary prism. According to radiolarian dating, bedded radiolarites and soft-sediment- deformed clasts in the megabreccias formed in a short, late Aptian to Cenomanian time interval. Middle Jurassic to Lower Cretaceous radiolarian ages are found in clasts and blocks reworked from an older oceanic basement. We conclude that the oceanic assemblage beneath the Santa Elena Nappe does not represent a continuous stratigraphic succession. It is a pile of individual thrust sheets constituting an accretionary sequence, where intrusion and extrusion of alkaline basalts, sedimentation of radiolarites, turbidites and trench fill chaotic sediments occurred during the Aptian-Cenomanian. These thrust sheets formed shortly before the off-scraping and accretion of the complex. Here we define the Santa Rosa Accretionary Complex and propose a new hypothesis not considered in former interpretations. This hypothesis would be the basis for further research.

The human epidermal differentiation complex: cornified envelope precursors, S100 proteins and the 'fused genes' family.

  The skin is essential for survival and protects our body against biological attacks, physical stress, chemical injury, water loss, ultraviolet radiation and immunological impairment. The epidermal barrier constitutes the primordial frontline of this defense established during terminal differentiation. During this complex process proliferating basal keratinocytes become suprabasally mitotically inactive and move through four epidermal layers (basal, spinous, granular and layer, stratum corneum) constantly adapting to the needs of the respective cell layer. As a result, squamous keratinocytes contain polymerized keratin intermediate filament bundles and a water-retaining matrix surrounded by the cross-linked cornified cell envelope (CE) with ceramide lipids attached on the outer surface. These cells are concomitantly insulated by intercellular lipid lamellae and hold together by corneodesmosmes. Many proteins essential for epidermal differentiation are encoded by genes clustered on chromosomal human region 1q21. These genes constitute the 'epidermal differentiation complex' (EDC), which is divided on the basis of common gene and protein structures, in three gene families: (i) CE precursors, (ii) S100A and (iii) S100 fused genes. EDC protein expression is regulated in a gene and tissue-specific manner by a pool of transcription factors. Among them, Klf4, Grhl3 and Arnt are essential, and their deletion in mice is lethal. The importance of the EDC is further reflected by human diseases: FLG mutations are the strongest risk factor for atopic dermatitis (AD) and for AD-associated asthma, and faulty CE formation caused by TG1 deficiency causes life-threatening lamellar ichthyosis. Here, we review the EDC genes and the progress in this field.

Performance in a complex task and breathing under odor exposure.

We investigated the influences of odor exposure on performance and on breathing measures. The task was composed of tracking, short-term memory, and peripheral reaction parts. During rest or while performing the task, 12 participants were exposed to 4 different odors in 2 intensities. The higher intensity of the malodors induced a short-term decrement in mean inspiration flow (Vi/Ti) after stimulus onset and impaired performance in the short-term memory task, as compared with control trials; no effect was found for the positively judged odors. The study suggests that a distractor as simple as a bad smell may pull a person off task, however briefly, and may result in a detriment to performance. Actual or potential applications of this research involve designing or securing tasks in such a way that a brief withdrawal of attention does not have fatal consequences.

Crystallization and preliminary X-ray diffraction studies of Drosophila melanogaster Gαo-subunit of heterotrimeric G protein in complex with the RGS domain of CG5036.

Regulator of G-protein signalling (RGS) proteins negatively regulate heterotrimeric G-protein signalling through their conserved RGS domains. RGS domains act as GTPase-activating proteins, accelerating the GTP hydrolysis rate of the activated form of Gα-subunits. Although omnipresent in eukaryotes, RGS proteins have not been adequately analysed in non-mammalian organisms. The Drosophila melanogaster Gαo-subunit and the RGS domain of its interacting partner CG5036 have been overproduced and purified; the crystallization of the complex of the two proteins using PEG 4000 as a crystallizing agent and preliminary X-ray crystallographic analysis are reported. Diffraction data were collected to 2.0 Å resolution using a synchrotron-radiation source.

A History of Particle-Size Limits, Special Report, HR-99

Soils consist largely of mineral particles in a wide range of sizes. It is advantageous to assign names, such as "sand", etc., to describe particles which lie between certain size limits. These names are convenient to use and give more information than merely stating that the particles fit certain size limitations. Many systems of particle-size limits have been proposed and used, and have many discrepancies. For example, depending on the system used, a term such as "sand" may designate very different materials. Since no clear-cut divisions can be made between members of a continuous series all particle-size limit schemes are arbitrary. The originators of the various systems were influenced by many factors: convenience of investigation, methods and equipment available for analysis, ease of presenting data, convenience for statistical analysis, previous work, and systems in use. The complications were further compounded because of widely varying fields of endeavor with varying background, outlook, and goals. For example, many inconsistencies are found in engineering depending on whether the size limits are used to differentiate soils, or characterize aggregates for concrete. Some of the investigators have tried to place limits to correspond with the various properties of the soil components; others were more interested in the ease and convenience of obtaining and presenting data. The purpose of this paper is to review many of the systems which have been proposed and used, and if possible, to suggest what may have been the reasons for the selection of the particle-size limits.

Particle exposure scenarios for research and production activities involving nanomaterials

Nanomaterials with structures in the nanoscale (1 to 100 nm) often have chemical, physical and bioactive characteristics different from those of larger entities of the same material. This is interesting for industry but raises questions about the health of exposed people. However, little is known so far about the exposure of workers to inhalable airborne nanomaterials. We investigated several activities in research laboratories and industry to learn about relevant exposure scenarios. Work process analyses were combined with measurements of airborne particle mass concentrations and number−size distributions. Background levels in research settings were mostly low, while in industrial production, levels were sometimes elevated, especially in halls near busy roads or in the presence of diesel fork lifts without particle filters. Peak levels were found in an industrial setting dealing with powders (up to 80,000 particles/cm³ and up to 15 mg/m³). Mostly low concentrations were found for activities involving liquid applications. However, centrifugation and lyophilization of nanoparticle containing solutions resulted in very high particle number concentrations (up to 300,000 particles/cm³), whereas no increases were seen for the same activities conducted with nanoparticle−free liquids. No significant increases of particle concentrations were found for processes involving nanoparticles bound to surfaces. Also no increases were observed in laboratories that were visualizing properties and structures of small amounts of nanomaterials. Conclusion: When studying exposure scenarios for airborne nanomaterials, the focus should not only be on processes involving nano−powders, but also on processes involving intensively treated nanoparticle−containing liquids. Acknowledgement: We thank Chantal Imhof, MSc and Guillaume Ferraris, MSc for their contributions.

Inter and intra-guild interactions in egg parasitoid species of the soybean stink bug complex

The objective of this research was to evaluate the parasitism behavior of Telenomus podisi Ashmead, Trissolcus basalis (Wollaston) e Trissolcus urichi Crawford (Hymenoptera: Scelionidae) on eggs of Nezara viridula L., Euschistus heros F., Piezodorus guildinii Westwood and Acrosternum aseadum Rolston (Heteroptera: Pentatomidae), in no choice and multiple choice experiments. For all parasitoid species, the results demonstrated the existence of a main host species that maximizes the reproductive success. The competitive interactions among the parasitoid species were investigated in experiments of sequential and simultaneous release of different combinations of parasitoid pairs on the hosts N. viridula, E. heros and A. aseadum. Exploitative competition was observed for egg batches at the genus level (Telenomus vs. Trissolcus) and interference competition at the species level (T. basalis vs. T. urichi). Trissolcus urichi was the most aggressive species, interfering with the parasitism of T. basalis. Generally, T. basalis showed an opportunistic behavior trying to parasitise eggs after T. urichi had abandoned the egg batch. The selection of parasitoid species for use in augmentative biological control programs should take into account the diversity of pentatomids present in soybean in addition to the interactions among the different species of parasitoids.

Expression of genes encoding the pre-TCR and CD3 complex during thymus development.

The mature TCR is composed of a clonotypic heterodimer (alpha beta or gamma delta) associated with the invariant CD3 components (gamma, delta, epsilon and zeta). There is now considerable evidence that more immature forms of the TCR-CD3 complex (consisting of either CD3 alone or CD3 associated with a heterodimer of TCR beta and pre-T alpha) can be expressed at the cell surface on early thymocytes. These pre-TCR complexes are believed to be necessary for the ordered progression of early T cell development. We have analyzed in detail the expression of both the pre-TCR and CD3 complex at various stages of adult thymus development. Our data indicate that all CD3 components are already expressed at the mRNA level by the earliest identifiable (CD4lo) thymic precursor. In contrast, genes encoding the pre-TCR complex (pre-T alpha and fully rearranged TCR beta) are first expressed at the CD44loCD25+CD4-CD8- stage. Detectable surface expression of both CD3 and TCR beta are delayed relative to expression of the corresponding genes, suggesting the existence of other (as yet unidentified) components of the pre-TCR complex.

Gene-disease network analysis reveals functional modules in mendelian, complex and environmental diseases

AbstractBACKGROUND: Scientists have been trying to understand the molecular mechanisms of diseases to design preventive and therapeutic strategies for a long time. For some diseases, it has become evident that it is not enough to obtain a catalogue of the disease-related genes but to uncover how disruptions of molecular networks in the cell give rise to disease phenotypes. Moreover, with the unprecedented wealth of information available, even obtaining such catalogue is extremely difficult.PRINCIPAL FINDINGS: We developed a comprehensive gene-disease association database by integrating associations from several sources that cover different biomedical aspects of diseases. In particular, we focus on the current knowledge of human genetic diseases including mendelian, complex and environmental diseases. To assess the concept of modularity of human diseases, we performed a systematic study of the emergent properties of human gene-disease networks by means of network topology and functional annotation analysis. The results indicate a highly shared genetic origin of human diseases and show that for most diseases, including mendelian, complex and environmental diseases, functional modules exist. Moreover, a core set of biological pathways is found to be associated with most human diseases. We obtained similar results when studying clusters of diseases, suggesting that related diseases might arise due to dysfunction of common biological processes in the cell.CONCLUSIONS: For the first time, we include mendelian, complex and environmental diseases in an integrated gene-disease association database and show that the concept of modularity applies for all of them. We furthermore provide a functional analysis of disease-related modules providing important new biological insights, which might not be discovered when considering each of the gene-disease association repositories independently. Hence, we present a suitable framework for the study of how genetic and environmental factors, such as drugs, contribute to diseases.AVAILABILITY: The gene-disease networks used in this study and part of the analysis are available at http://ibi.imim.es/DisGeNET/DisGeNETweb.html#Download

Complex suicide with homemade nicotine patches.

Suicide by self-poisoning is rather common around the world. This paper presents an exceptional complex suicide in which nicotine was applied in the form of self-made patches soaked with an extraction from fine-cut tobacco. In addition, the 51-year-old suicide victim took a lethal dose of diphenhydramine. Toxicological analysis also revealed the presence of tetrazepam in subtherapeutic concentrations. The scene of death suggested an autoerotic accident at first, as the body was tied with tapes, cables and handcuffs. As a result of the entire investigations, the fatality had to be classified as a suicidal intoxication by nicotine and diphenhydramine.

Complex formation by the human RAD51C and XRCC3 recombination repair proteins.

In vertebrates, the RAD51 protein is required for genetic recombination, DNA repair, and cellular proliferation. Five paralogs of RAD51, known as RAD51B, RAD51C, RAD51D, XRCC2, and XRCC3, have been identified and also shown to be required for recombination and genome stability. At the present time, however, very little is known about their biochemical properties or precise biological functions. As a first step toward understanding the roles of the RAD51 paralogs in recombination, the human RAD51C and XRCC3 proteins were overexpressed and purified from baculovirus-infected insect cells. The two proteins copurify as a complex, a property that reflects their endogenous association observed in HeLa cells. Purified RAD51C--XRCC3 complex binds single-stranded, but not duplex DNA, to form protein--DNA networks that have been visualized by electron microscopy.

Kernel-based Mapping of Meteorological Fields in Complex Orography

Due to the advances in sensor networks and remote sensing technologies, the acquisition and storage rates of meteorological and climatological data increases every day and ask for novel and efficient processing algorithms. A fundamental problem of data analysis and modeling is the spatial prediction of meteorological variables in complex orography, which serves among others to extended climatological analyses, for the assimilation of data into numerical weather prediction models, for preparing inputs to hydrological models and for real time monitoring and short-term forecasting of weather.In this thesis, a new framework for spatial estimation is proposed by taking advantage of a class of algorithms emerging from the statistical learning theory. Nonparametric kernel-based methods for nonlinear data classification, regression and target detection, known as support vector machines (SVM), are adapted for mapping of meteorological variables in complex orography.With the advent of high resolution digital elevation models, the field of spatial prediction met new horizons. In fact, by exploiting image processing tools along with physical heuristics, an incredible number of terrain features which account for the topographic conditions at multiple spatial scales can be extracted. Such features are highly relevant for the mapping of meteorological variables because they control a considerable part of the spatial variability of meteorological fields in the complex Alpine orography. For instance, patterns of orographic rainfall, wind speed and cold air pools are known to be correlated with particular terrain forms, e.g. convex/concave surfaces and upwind sides of mountain slopes.Kernel-based methods are employed to learn the nonlinear statistical dependence which links the multidimensional space of geographical and topographic explanatory variables to the variable of interest, that is the wind speed as measured at the weather stations or the occurrence of orographic rainfall patterns as extracted from sequences of radar images. Compared to low dimensional models integrating only the geographical coordinates, the proposed framework opens a way to regionalize meteorological variables which are multidimensional in nature and rarely show spatial auto-correlation in the original space making the use of classical geostatistics tangled.The challenges which are explored during the thesis are manifolds. First, the complexity of models is optimized to impose appropriate smoothness properties and reduce the impact of noisy measurements. Secondly, a multiple kernel extension of SVM is considered to select the multiscale features which explain most of the spatial variability of wind speed. Then, SVM target detection methods are implemented to describe the orographic conditions which cause persistent and stationary rainfall patterns. Finally, the optimal splitting of the data is studied to estimate realistic performances and confidence intervals characterizing the uncertainty of predictions.The resulting maps of average wind speeds find applications within renewable resources assessment and opens a route to decrease the temporal scale of analysis to meet hydrological requirements. Furthermore, the maps depicting the susceptibility to orographic rainfall enhancement can be used to improve current radar-based quantitative precipitation estimation and forecasting systems and to generate stochastic ensembles of precipitation fields conditioned upon the orography.