Adsorption of glyphosate in chilean soils and its relationship with unoccupied phosphate binding sites

The objective of this work was to investigate glyphosate adsorption by soils and its relationship with unoccupied binding sites for phosphate adsorption. Soil samples of three Chilean soils series - Valdivia (Andisol), Clarillo (Inceptisol) and Chicureo (Vertisol) - were incubated with different herbicide concentrations. Glyphosate remaining in solution was determined by adjusting a HPLC method with a UV detector. Experimental maximum adsorption capacity were 15,000, 14,300 and 4,700 mg g¹ for Valdivia, Clarillo, and Chicureo soils, respectively. Linear, Freundlich, and Langmuir models were used to describe glyphosate adsorption. Isotherms describing glyphosate adsorption differed among soils. Maximum adjusted adsorption capacity with the Langmuir model was 231,884, 17,874 and 5,670 mg g-1 for Valdivia, Clarillo, and Chicureo soils, respectively. Glyphosate adsorption on the Valdivia soil showed a linear behavior at the range of concentrations used and none of the adjusted models became asymptotic. The high glyphosate adsorption capacity of the Valdivia soil was probably a result of its high exchangeable Al, extractable Fe, and alophan and imogolite clay type. Adsorption was very much related to phosphate dynamics in the Valdivia soil, which showed the larger unoccupied phosphate binding sites. However relationship between unoccupied phosphate binding sites and glyphosate adsorption in the other two soils (Clarillo and Chicureo) was not clear.

Sequencing human-gibbon breakpoints of synteny reveals mosaic new insertions at rearrangement sites

The gibbon genome exhibits extensive karyotypic diversity with an increased rate of chromosomal rearrangements during evolution. In an effort to understand the mechanistic origin and implications of these rearrangement events, we sequenced 24 synteny breakpoint regions in the white-cheeked gibbon (Nomascus leucogenys, NLE) in the form of high-quality BAC insert sequences (4.2 Mbp). While there is a significant deficit of breakpoints in genes, we identified seven human gene structures involved in signaling pathways (DEPDC4, GNG10), phospholipid metabolism (ENPP5, PLSCR2), beta-oxidation (ECH1), cellular structure and transport (HEATR4), and transcription (ZNF461), that have been disrupted in the NLE gibbon lineage. Notably, only three of these genes show the expected evolutionary signatures of pseudogenization. Sequence analysis of the breakpoints suggested both nonclassical nonhomologous end-joining (NHEJ) and replication-based mechanisms of rearrangement. A substantial number (11/24) of human-NLE gibbon breakpoints showed new insertions of gibbon-specific repeats and mosaic structures formed from disparate sequences including segmental duplications, LINE, SINE, and LTR elements. Analysis of these sites provides a model for a replication-dependent repair mechanism for double-strand breaks (DSBs) at rearrangement sites and insights into the structure and formation of primate segmental duplications at sites of genomic rearrangements during evolution.

Data-driven topo-climatic mapping with machine learning methods

Automatic environmental monitoring networks enforced by wireless communication technologies provide large and ever increasing volumes of data nowadays. The use of this information in natural hazard research is an important issue. Particularly useful for risk assessment and decision making are the spatial maps of hazard-related parameters produced from point observations and available auxiliary information. The purpose of this article is to present and explore the appropriate tools to process large amounts of available data and produce predictions at fine spatial scales. These are the algorithms of machine learning, which are aimed at non-parametric robust modelling of non-linear dependencies from empirical data. The computational efficiency of the data-driven methods allows producing the prediction maps in real time which makes them superior to physical models for the operational use in risk assessment and mitigation. Particularly, this situation encounters in spatial prediction of climatic variables (topo-climatic mapping). In complex topographies of the mountainous regions, the meteorological processes are highly influenced by the relief. The article shows how these relations, possibly regionalized and non-linear, can be modelled from data using the information from digital elevation models. The particular illustration of the developed methodology concerns the mapping of temperatures (including the situations of Föhn and temperature inversion) given the measurements taken from the Swiss meteorological monitoring network. The range of the methods used in the study includes data-driven feature selection, support vector algorithms and artificial neural networks.

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.

Multi-Purpose ESS/ITS Data Collection Sites, SPR72-00-0003-042, 2014

This document presents the results of a state-of-practice survey of transportation agencies that are installing intelligent transportation sensors (ITS) and other devices along with their environmental sensing stations (ESS) also referred to as roadway weather information system (RWIS) assets.

Dementoituneiden asiakkaiden hoidon laadun havainnointi- pilottitutkimus Dementia Care Mapping -menetelmällä

Summary: Assessment of the quality of care of people with dementia - Dementia Care Mapping pilot

The QUASAR reproducibility study, Part II: Results from a multi-center Arterial Spin Labeling test-retest study.

Arterial Spin Labeling (ASL) is a method to measure perfusion using magnetically labeled blood water as an endogenous tracer. Being fully non-invasive, this technique is attractive for longitudinal studies of cerebral blood flow in healthy and diseased individuals, or as a surrogate marker of metabolism. So far, ASL has been restricted mostly to specialist centers due to a generally low SNR of the method and potential issues with user-dependent analysis needed to obtain quantitative measurement of cerebral blood flow (CBF). Here, we evaluated a particular implementation of ASL (called Quantitative STAR labeling of Arterial Regions or QUASAR), a method providing user independent quantification of CBF in a large test-retest study across sites from around the world, dubbed "The QUASAR reproducibility study". Altogether, 28 sites located in Asia, Europe and North America participated and a total of 284 healthy volunteers were scanned. Minimal operator dependence was assured by using an automatic planning tool and its accuracy and potential usefulness in multi-center trials was evaluated as well. Accurate repositioning between sessions was achieved with the automatic planning tool showing mean displacements of 1.87+/-0.95 mm and rotations of 1.56+/-0.66 degrees . Mean gray matter CBF was 47.4+/-7.5 [ml/100 g/min] with a between-subject standard variation SD(b)=5.5 [ml/100 g/min] and a within-subject standard deviation SD(w)=4.7 [ml/100 g/min]. The corresponding repeatability was 13.0 [ml/100 g/min] and was found to be within the range of previous studies.

Mapping of quantitative trait loci for thermosensitive genic male sterility in indica rice

The objective of this work was to select and use microsatellite markers, to map genomic regions associated with the genetic control of thermosensitive genic male sterility (TGMS) in rice. An F2 population, derived from the cross between fertile and TGMS indica lines, was used to construct a microsatellite-based genetic map of rice. The TGMS phenotype showed a continuous variation in the segregant population. A low level of segregation distortion was detected in the F2 (14.65%), whose cause was found to be zygotic selection. There was no evidence suggesting a cause-effect relationship between zygotic selection and the control of TGMS in this cross. A linkage map comprising 1,213.3 cM was constructed based on the segregation data of the F2 population. Ninety-five out of 116 microsatellite polymorphic markers were assembled into 11 linkage groups, with an average of 12.77 cM between two adjacent marker loci. The phenotypic and genotypic data allowed for the identification of three new quantitative trait loci (QTL) for thermosensitive genic male sterility in indica rice. Two of the QTL were mapped on chromosomes that, so far, have not been associated with the genetic control of the TGMS trait (chromosomes 1 and 12). The third QTL was mapped on chromosome 7, where a TGMS locus (tms2) has recently been mapped. Allelic tests will have to be developed, in order to clarify if the two regions are the same or not.

A randomised controlled pilot study comparing Mepitel(®) and SurfaSoft(®) on paediatric donor sites treated with Recell(®).

This randomized controlled pilot study examined the effects of a silicone net dressing (Mepitel(®)) and a monofilament polyamide woven dressing (SurfaSoft(®)) on the rate of epithelialisation and epidermal maturation, pain, and ease of dressing removal on paediatric donor sites treated with epithelial cell suspension (ReCell(®)). Fifteen children (1-15 years) admitted for acute or reconstructive burns procedures in a tertiary referral hospital in Australia were randomly assigned to the experimental group, Mepitel(®) (n=8) and to the control group, SurfaSoft(®) (n=7). All donor sites were treated with ReCell(®) and covered with the assigned dressing. Measurements of rate of epithelialisation and epidermal maturation, pain, and ease of dressing removal were recorded every two days until the wound was healed. Results showed that there was no difference in the rate of epidermal maturation between the two groups. Less pain and force to remove the dressing was shown in the Mepitel(®) group when compared to SurfaSoft(®). The rate of epithelialisation was found to be an unreliable measure. Although additional research is required to support the results of this study, these results suggest that Mepitel's(®) pliable, self-adhesive and atraumatic properties may improve healing of ReCell(®) treated donor sites with less pain at dressing changes. This pilot study provides a strong base for further research in this area.

Predictive analysis and mapping of indoor radon concentrations in a complex environment using kernel estimation: an application to Switzerland.

PURPOSE: The aim of this study was to develop models based on kernel regression and probability estimation in order to predict and map IRC in Switzerland by taking into account all of the following: architectural factors, spatial relationships between the measurements, as well as geological information. METHODS: We looked at about 240,000 IRC measurements carried out in about 150,000 houses. As predictor variables we included: building type, foundation type, year of construction, detector type, geographical coordinates, altitude, temperature and lithology into the kernel estimation models. We developed predictive maps as well as a map of the local probability to exceed 300 Bq/m(3). Additionally, we developed a map of a confidence index in order to estimate the reliability of the probability map. RESULTS: Our models were able to explain 28% of the variations of IRC data. All variables added information to the model. The model estimation revealed a bandwidth for each variable, making it possible to characterize the influence of each variable on the IRC estimation. Furthermore, we assessed the mapping characteristics of kernel estimation overall as well as by municipality. Overall, our model reproduces spatial IRC patterns which were already obtained earlier. On the municipal level, we could show that our model accounts well for IRC trends within municipal boundaries. Finally, we found that different building characteristics result in different IRC maps. Maps corresponding to detached houses with concrete foundations indicate systematically smaller IRC than maps corresponding to farms with earth foundation. CONCLUSIONS: IRC mapping based on kernel estimation is a powerful tool to predict and analyze IRC on a large-scale as well as on a local level. This approach enables to develop tailor-made maps for different architectural elements and measurement conditions and to account at the same time for geological information and spatial relations between IRC measurements.

Cross-species analysis of the replication complex of Old World arenaviruses reveals two nucleoprotein sites involved in L protein function.

Lassa virus (LASV) causing hemorrhagic Lassa fever in West Africa, Mopeia virus (MOPV) from East Africa, and lymphocytic choriomeningitis virus (LCMV) are the main representatives of the Old World arenaviruses. Little is known about how the components of the arenavirus replication machinery, i.e., the genome, nucleoprotein (NP), and L protein, interact. In addition, it is unknown whether these components can function across species boundaries. We established minireplicon systems for MOPV and LCMV in analogy to the existing LASV system and exchanged the components among the three systems. The functional and physical integrity of the resulting complexes was tested by reporter gene assay, Northern blotting, and coimmunoprecipitation studies. The minigenomes, NPs, and L proteins of LASV and MOPV could be exchanged without loss of function. LASV and MOPV L protein was also active in conjunction with LCMV NP, while the LCMV L protein required homologous NP for activity. Analysis of LASV/LCMV NP chimeras identified a single LCMV-specific NP residue (Ile-53) and the C terminus of NP (residues 340 to 558) as being essential for LCMV L protein function. The defect of LASV and MOPV NP in supporting transcriptional activity of LCMV L protein was not caused by a defect in physical NP-L protein interaction. In conclusion, components of the replication complex of Old World arenaviruses have the potential to functionally and physically interact across species boundaries. Residue 53 and the C-terminal domain of NP are important for function of L protein during genome replication and transcription.

Cation Transport Coupled to ATP Hydrolysis By the (Na, K)-ATPase : an integrated, animated model

An Adobe (R) animation is presented for use in undergraduate Biochemistry courses, illustrating the mechanism of Na+ and K+ translocation coupled to ATP hydrolysis by the (Na, K)-ATPase, a P-2c-type ATPase, or ATP-powered ion pump that actively translocates cations across plasma membranes. The enzyme is also known as an E-1/E-2-ATPase as it undergoes conformational changes between the E-1 and E-2 forms during the pumping cycle, altering the affinity and accessibility of the transmembrane ion-binding sites. The animation is based on Horisberger's scheme that incorporates the most recent significant findings to have improved our understanding of the (Na, K)-ATPase structure function relationship. The movements of the various domains within the (Na, K)-ATPase alpha-subunit illustrate the conformational changes that occur during Na+ and K+ translocation across the membrane and emphasize involvement of the actuator, nucleotide, and phosphorylation domains, that is, the "core engine" of the pump, with respect to ATP binding, cation transport, and ADP and P-i release.

Mapping of the binding domains of the axon guidance receptor Unc5B to Netrin-1 and FLRT3

Anàlisi de les interaccions, a nivell neuronal, que tenen lloc durant el desenvolupament embrionari entre el receptor Unc5B (receptor present a la membrana) i les proteïnes Netrin-1 i FLRT3 (fibronectin and leucine-rich transmembrane proteins). La interacció entre aquest receptor i Netrin-1 ha estat profundament estudiada fins al moment, de manera que es coneix que aquesta promou una repulsió en la guia d’axons durant el desenvolupament embrionari. A més, la interacció està implicada en la senyalització per a diferents processos com l’angiogènesi i la supervivència cel·lular. Per altra banda, la interacció entre neurones Unc5B positives i FLRT3, promou un retard en la migració de les neurones. Diversos estudis demostren que aquest retard en la migració està relacionat amb certes patologies mentals.