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The diversity of experimental workflows involving LC−MS/MS and the extended range of mass spectrometers tend to produce extremely variable spectra. Variability reduces the accuracy of compound identification produced by commonly available software for a spectral library search. We introduce here a new algorithm that successfully matches MS/MS spectra generated by a range of instruments, acquired under different conditions. Our algorithm called X-Rank first sorts peak intensities of a spectrum and second establishes a correlation between two sorted spectra. X-Rank then computes the probability that a rank from an experimental spectrum matches a rank from a reference library spectrum. In a training step, characteristic parameter values are generated for a given data set. We compared the efficiency of the X-Rank algorithm with the dot-product algorithm implemented by MS Search from the National Institute of Standards and Technology (NIST) on two test sets produced with different instruments. Overall the X-Rank algorithm accurately discriminates correct from wrong matches and detects more correct substances than the MS Search. Furthermore, X-Rank could correctly identify and top rank eight chemical compounds in a commercially available test mix. This confirms the ability of the algorithm to perform both a straight single-platform identification and a cross-platform library search in comparison to other tools. It also opens the possibility for efficient general unknown screening (GUS) against large compound libraries.

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The Geographic Information Retrieval and Analysis System (GIRAS) was developed in the mid 70s to put into digital form a number of data layers which were of interest to the USGS. One of these data layers was the Hydrologic Units. The map is based on the Hydrologic Unit Maps published by the U.S. Geological Survey Office of Water Data Coordination, together with the list descriptions and name of region, subregion, accounting units, and cataloging unit. The hydrologic units are encoded with an eight- digit number that indicates the hydrologic region (first two digits), hydrologic subregion (second two digits), accounting unit (third two digits), and cataloging unit (fourth two digits). The data produced by GIRAS was originally collected at a scale of 1:250K. Some areas, notably major cities in the west, were recompiled at a scale of 1:100K. In order to join the data together and use the data in a geographic information system (GIS) the data were processed in the ARC/INFO GUS software package. Within the GIS, the data were edgematched and the neatline boundaries between maps were removed to create a single data set for the conterminous United States. NOTE: A version of this data theme that is more throughly checked (though based on smaller-scale maps) is available here: https://water.usgs.gov/lookup/getspatial?huc2m HUC, GIRAS, Hydrologic Units, 1:250 For the most current data and information relating to hydrologic unit codes (HUCs) please see http://water.usgs.gov/GIS/huc.html. The Watershed Boundary Dataset (WBD) is the most current data available for watershed delineation. See http://www.nrcs.usda.gov/wps/portal/nrcs/main/national/water/watersheds/dataset

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With growing concerns about declining snowpack, warmer temperatures, and land use changes, it is becoming increasingly important to determine the sources that contribute to surface water. In western states, such as New Mexico, most of the surface water is derived from mountainous watersheds. However, the interaction between the groundwater and the surface water within these mountain systems is poorly understood. Geochemical data collected from a mesoscale (~200 km2) watershed in northern New Mexico indicate there may be significant groundwater contributions to the surface water that have largely been ignored in previous studies. Stable isotopic analysis of δ18O and δ2H and Piper diagrams for surface water, groundwater, and spring water are not geochemically distinct. Surface water solute concentrations for most constituents increase as a function of the drainage area while the stable isotopic signature remains constant, suggesting that the water is sourced from similar areas but has undergone differing degrees of geochemical evolution along different flow paths. Plots of SiO2 vs Ca2+, Na+, Mg2+, and K+ show evidence of spatial evolution of groundwater with solute concentrations from the headwaters to the watershed outlet. We hypothesize that the increasing solute concentrations in the surface water are controlled by inputs from deep, more geochemically evolved groundwater. This is similar to what Frisbee et al. (2011) saw in the Saguache Watershed, though our watershed is significantly smaller and has a different geological setting. Due to the chemical kinetics involved, this more geochemically evolved groundwater would require longer residence time along a given flow path to achieve the observed chemical compositions. Significant contributions of old groundwater to surface water could result in the surface water system having increased buffering capacity against climate change. This deep groundwater component in watersheds has largely been unexplored. Our research provides support for our hypothesis and indicates that deep groundwater contributions to surface water may occur at even smaller scales than previously published.

Heterotrimeric G-proteins regulate plant growth and development as master regulators of signaling pathways. In legumes with indeterminate nodules (e.g., Medicago truncatula and Pisum sativum), the role of heterotrimeric G-proteins in symbiosis development has not been investigated extensively. Here, the involvement of heterotrimeric G-proteins in M. truncatula and P. sativum nodulation was evaluated. A genome-based search for G-protein subunit-coding genes revealed that M. truncatula and P. sativum harbored only one gene each for encoding the canonical heterotrimeric G-protein beta subunits, MtG beta 1 and PsG beta 1, respectively. RNAi-based suppression of MtGbeta1 and PsGbeta1 significantly decreased the number of nodules formed, suggesting the involvement of G-protein beta subunits in symbiosis in both legumes. Analysis of composite M. truncatula plants carrying the pMtGbeta1:GUS construct showed β-glucuronidase (GUS) staining in developing nodule primordia and young nodules, consistent with data on the role of G-proteins in controlling organ development and cell proliferation. In mature nodules, GUS staining was the most intense in the meristem and invasion zone (II), while it was less prominent in the apical part of the nitrogen-fixing zone (III). Thus, MtG beta 1 may be involved in the maintenance of meristem development and regulation of the infection process during symbiosis. Protein–protein interaction studies using co-immunoprecipitation revealed the possible composition of G-protein complexes and interaction of G-protein subunits with phospholipase C (PLC), suggesting a cross-talk between G-protein- and PLC-mediated signaling pathways in these legumes. Our findings provide direct evidence regarding the role of MtG beta 1 and PsG beta 1 in symbiosis development regulation.

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Variation on growth unit morphology in Khaya senegalensis (Desr.) A. Juss. (Meliaceae) and Pterocarpus erinaceus Poir. (Fabaceae) according to habitat and climate

Heterotrimeric G-proteins regulate plant growth and development as master regulators of signaling pathways. In legumes with indeterminate nodules (e.g., Medicago truncatula and Pisum sativum), the role of heterotrimeric G-proteins in symbiosis development has not been investigated extensively. Here, the involvement of heterotrimeric G-proteins in M. truncatula and P. sativum nodulation was evaluated. A genome-based search for G-protein subunit-coding genes revealed that M. truncatula and P. sativum harbored only one gene each for encoding the canonical heterotrimeric G-protein beta subunits, MtG beta 1 and PsG beta 1, respectively. RNAi-based suppression of MtGbeta1 and PsGbeta1 significantly decreased the number of nodules formed, suggesting the involvement of G-protein beta subunits in symbiosis in both legumes. Analysis of composite M. truncatula plants carrying the pMtGbeta1:GUS construct showed β-glucuronidase (GUS) staining in developing nodule primordia and young nodules, consistent with data on the role of G-proteins in controlling organ development and cell proliferation. In mature nodules, GUS staining was the most intense in the meristem and invasion zone (II), while it was less prominent in the apical part of the nitrogen-fixing zone (III). Thus, MtG beta 1 may be involved in the maintenance of meristem development and regulation of the infection process during symbiosis. Protein–protein interaction studies using co-immunoprecipitation revealed the possible composition of G-protein complexes and interaction of G-protein subunits with phospholipase C (PLC), suggesting a cross-talk between G-protein- and PLC-mediated signaling pathways in these legumes. Our findings provide direct evidence regarding the role of MtG beta 1 and PsG beta 1 in symbiosis development regulation.

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The Growing Up in Scotland (GUS) study is a large-scale longitudinal social survey which follows the lives of several groups of Scottish children from infancy through childhood and adolescence. It aims to provide important information on children, young people and their families in Scotland. The study forms a central part of the Scottish Government's strategy for the long-term monitoring and evaluation of its policies for children and young people, with a specific focus on the early years. The study seeks both to describe the characteristics, circumstances and experiences of children in their early years in Scotland and, through its longitudinal design, to generate a better understanding of how children's start in life can shape their longer term prospects and developmentSince 2005 fieldwork has been undertaken by the Scottish Centre for Social Research. The survey design for Birth Cohort 1 consisted of recruiting the parents of an initial total of 5,217 children aged 10 months old in 2005 and interviewing them annually until their child reached age six. Further fieldwork was then undertaken at ages 8, 10, 12, 14 and 17-18 with a sample boost added at age 12.Data for sweeps 1-9 were collected via an in-home, face-to-face interview with self-complete sections. Fieldwork for sweep 10 was disrupted due to the COVID pandemic. As a result, the final portion of the data was collected via web and telephone questionnaires. Sweep 11 data were gathered via web, telephone and face-to-face surveys of cohort members and their parent/carer.Further information about the survey may be found on the Growing Up in Scotland website.In May 20205, data and documentation for Cohort 1, Sweeps 1-11 were released as individual studies (SNs 9373-9383 and 9386-9387). Previously they were held under one study (SN 5760) which has been withdrawn from the data catalogue. SN 9120 - Growing Up in Scotland: Cohort 1, Sweep 8 Physical Activity Data, 2015-2016The Studying Physical Activity in Children's Environments across Scotland (SPACES) project aimed to investigate the ways in which the built, natural and social environment influences children's physical activity. The project employed an observational, cross-sectional design that sub-sampled from Birth Cohort 1 (BC1) of the GUS during the GUS Sweep 8 fieldwork. Children sub-sampled from GUS were invited to provide objectively measured physical activity data by wearing an accelerometer for eight days.This dataset provides a range of summary physical activity variables from this project. A total of 775 children provided valid data. As a sub sample of GUS BC1, the summary level physical activity data can be linked, where appropriate, to other GUS BC1 datasets held on UKDS at the individual level. The physical activity data were collected between May 2015 and May 2016 by the MRC/CSO Social and Public Health Sciences Unit (SPHSU), University of Glasgow. To support a range of analytical projects, a series of summary variables have been derived and included in the dataset. These include minutes spent in different categories of physical activity and variables indicating whether the child met the recommended Scottish Government guidelines of 60 minutes of physical activity each day (calculated in two forms: an average of 60 minutes per day overall valid days; a stricter measure of actual 60 minutes per day on each valid day).

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