Chemical Evolution of the Galactic Bulge as Derived from High-Resolution Infrared Spectroscopy of K and M Red Giants

We present chemical abundances in K and M red-giant members of the Galactic bulge derived from high-resolution infrared spectra obtained with the Phoenix spectrograph on Gemini-South. The elements studied are carbon, nitrogen, oxygen, sodium, titanium, and iron. The evolution of C and N abundances in the studied red-giants show that their oxygen abundances represent the original values with which the stars were born. Oxygen is a superior element for probing the timescale of bulge chemical enrichment via [O/Fe] versus [Fe/H]. The [O/Fe]-[Fe/H] relation in the bulge does not follow the disk relation, with [O/Fe] values falling above those of the disk. Titanium also behaves similarly to oxygen with respect to iron. Based on these elevated values of [O/Fe] and [Ti/Fe] extending to large Fe abundances, it is suggested that the bulge underwent a more rapid chemical enrichment than the halo. In addition, there are declines in both [O/Fe] and [Ti/Fe] in those bulge targets with the largest Fe abundances, signifying another source affecting chemical evolution: perhaps Supernovae of Type Ia. Sodium abundances increase dramatically in the bulge with increasing metallicity, possibly reflecting the metallicity dependant yields from supernovae of Type II, although Na contamination from H-burning in intermediate mass stars cannot be ruled out.Comment: ApJ in pres

NASA's GeneLab Phase II: Federated Search and Data Discovery

GeneLab is currently being developed by NASA to accelerate 'open science' biomedical research in support of the human exploration of space and the improvement of life on earth. Phase I of the four-phase GeneLab Data Systems (GLDS) project emphasized capabilities for submission, curation, search, and retrieval of genomics, transcriptomics and proteomics ('omics') data from biomedical research of space environments. The focus of development of the GLDS for Phase II has been federated data search for and retrieval of these kinds of data across other open-access systems, so that users are able to conduct biological meta-investigations using data from a variety of sources. Such meta-investigations are key to corroborating findings from many kinds of assays and translating them into systems biology knowledge and, eventually, therapeutics

NASA's GeneLab: An Integrated Omics Data Commons and Workbench

GeneLab (http://genelab.nasa.gov) is a NASA initiative designed to accelerate open science biomedical research in support of the human exploration of space and the improvement of life on earth. The GeneLab Data Systems (GLDS) were developed to help investigators corroborate findings from omics (genomics, transcriptomics, proteomics, and metabolomics) assays and translate them into systems biology knowledge and, eventually, therapeutics, including countermeasures to support life in space. Phase I of the project (completed) emphasized developing key capabilities for submission, curation, storage, search, and retrieval of omics data from biomedical research in and of space environments. The development focus for Phase II (completed) was federated data search and retrieval of these kinds of data from other open-access repositories. The last phase of the project (in work) entails developing an omics analysis tool set, and a portal to visualize processed omics data, emphasizing integration with the data repository and search functions developed during the prior phases. The final product will be an open-access system where users can individually or collaboratively publish, search, integrate, analyze, and visualize omics data

NASA's GeneLab: An Integrated Omics Data Commons and Workbench

GeneLab (http://genelab.nasa.gov) is a NASA initiative designed to accelerate "open science" biomedical research in support of the human exploration of space and the improvement of life on earth. The GeneLab Data Systems (GLDS) were developed to help investigators corroborate findings from "omics" (genomics, transcriptomics, proteomics, and metabolomics) assays and translate them into systems biology knowledge and, eventually, therapeutics, including countermeasures to support life in space. Phase I of the project (completed) emphasized developing key capabilities for submission, curation, storage, search, and retrieval of omics data from biomedical research in and of space environments. The development focus for Phase II (completed) was federated data search and retrieval of these kinds of data from other open-access repositories. The last phase of the project (in work) entails developing an omics analysis tool set, and a portal to visualize processed omics data, emphasizing integration with the data repository and search functions developed during the prior phases. The final product will be an open-access system where users can individually or collaboratively publish, search, integrate, analyze, and visualize omics data

Curricular Tracking, Students’ Academic Identity, and School Belonging

Curricular tracking is common in many countries, yet this school practice might have unintended consequences for students’ attitudes toward school. We examined the changes in adolescents’ school belonging among sixth graders placed in honors versus regular math, with academic identity as a mediator in this relation. Early adolescents (N = 322; 72% White; 164 girls) in the southeastern United States completed measures of school belonging and academic identity at the beginning and end of their sixth-grade year. With parent education, prior math achievement, and prior school belonging controlled, honors math placement predicted increases in school belonging from the beginning to the end of students’ sixth-grade year, and this association was positively mediated by academic identity. Results of this study are important for further understanding the influences of tracking on students’ motivational beliefs

Nonprescription Stimulant Use at a Public University: Students’ Motives, Experiences, and Guilt

We examined the use of nonmedical prescription stimulants (NPSs) among students (N = 1,208) at a large public university in southeastern United States. After students who had been prescribed stimulants had been removed from the sample, 202 of the remaining 1,067 students (i.e., 18.9%) reported having engaged in NPS use in their lifetime. NPS use was strongly associated with membership in Greek societies and with binge drinking behavior. NPS users overwhelmingly reported engagement in NPS use for academic rather than for recreational purposes, and as anticipated, NPS users with academic motives reported stronger academic benefits than NPS users with social/recreational motives. Reports of guilt were low, and frequent users reported less guilt than infrequent users. Implications for interventions are discussed

MuSCA: A multi-scale source-sink carbon allocation model to explore carbon allocation in plants. An application to static apple tree structures

Background and aims: Carbon allocation in plants is usually represented at a topological scale, specific to each model. This makes the results obtained with different models, and the impact of their scales of representation, difficult to compare. In this study, we developed a multi-scale carbon allocation model (MuSCA) that allows the use of different, user-defined, topological scales of a plant, and assessment of the impact of each spatial scale on simulated results and computation time. Methods: Model multi-scale consistency and behaviour were tested on three realistic apple tree structures. Carbon allocation was computed at five scales, spanning from the metamer (the finest scale, used as a reference) up to first-order branches, and for different values of a sap friction coefficient. Fruit dry mass increments were compared across spatial scales and with field data. Key Results: The model was able to represent effects of competition for carbon assimilates on fruit growth. Intermediate friction parameter values provided results that best fitted field data. Fruit growth simulated at the metamer scale differed of ~1 % in respect to results obtained at growth unit scale and up to 60 % in respect to first order branch and fruiting unit scales. Generally, the coarser the spatial scale the more predicted fruit growth diverged from the reference. Coherence in fruit growth across scales was also differentially impacted, depending on the tree structure considered. Decreasing the topological resolution reduced computation time by up to four orders of magnitude. Conclusions: MuSCA revealed that the topological scale has a major influence on the simulation of carbon allocation. This suggests that the scale should be a factor that is carefully evaluated when using a carbon allocation model, or when comparing results produced by different models. Finally, with MuSCA, trade-off between computation time and prediction accuracy can be evaluated by changing topological scales

A Multi-Scale Model to explore Carbon Allocation in Plants

International audienceUnderstanding and simulating carbon allocation in plants is necessary to distribute carbohydrates among growing and competing organs and to predict plant growth and structure development in relation to climatic conditions. In this context several carbon allocation models have been developed but no clear consensus exists on (i) the most appropriate topological scale (organ, metamer, compartment...) to represent this process on complex plant structures, (ii) the importance of distances between organs in carbon transport, (iii) the priorities in carbon allocation among plant parts, that can depend on growth stages. Multi-scale tree graph (MTG) is a formalism allowing the representation of geometry and topology of a tree structure at different scales. In this study, several models were implemented to compute carbon allocation at user-defined spatial scales by using the MTG formalism. This allows multiple scales (e.g. metamer, growing unit, branch) to be combined during the computation of carbon allocation (e.g. allocation first within leafy shoots at metamer scale and then between growing units). The model describes carbon transport, taking into account the distances between sources and sinks, the strength of the sinks and the available carbohydrates, following the equations of the SIMWAL and QualiTree models. Simulations on simplified branching structures, represented at different scales, showed how the scales chosen to represent the system influence the results of predicted carbon allocation. This modelling approach will be first applied to apple tree to analyze the impact of the scale of representation (branch, growth unit, metamer, and inflorescence) on the predicted fruit growth variability which, in turn, will be compared with field observations. The present work is available through the OpenAlea platform and provides existing Functional Structural Plant Models with a new generic model to simulate carbon allocation in plants depending on user-defined biological hypotheses, such as the choice of the scale of representation or the effect of distance

GeneLab: Omics Database for Spaceflight Experiments

Motivation - To curate and organize expensive spaceflight experiments conducted aboard space stations and maximize the scientific return of investment, while democratizing access to vast amounts of spaceflight related omics data generated from several model organisms. Results - The GeneLab Data System (GLDS) is an open access database containing fully coordinated and curated "omics" (genomics, transcriptomics, proteomics, metabolomics) data, detailed metadata and radiation dosimetry for a variety of model organisms. GLDS is supported by an integrated data system allowing federated search across several public bioinformatics repositories. Archived datasets can be queried using full-text search (e.g., keywords, Boolean and wildcards) and results can be sorted in multifactorial manner using assistive filters. GLDS also provides a collaborative platform built on GenomeSpace for sharing files and analyses with collaborators. It currently houses 172 datasets and supports standard guidelines for submission of datasets, MIAME (for microarray), ENCODE Consortium Guidelines (for RNA-seq) and MIAPE Guidelines (for proteomics)

Abundances in bulge stars from high-resolution, near-IR spectra I. The CNO elements observed during the science verification of CRIRES at VLT

The formation and evolution of the Milky Way bulge is not yet well understood and its classification is ambiguous. Constraints can, however, be obtained by studying the abundances of key elements in bulge stars. The aim of this study is to determine the chemical evolution of CNO, and a few other elements in stars in the Galactic bulge, and to discuss the sensitivities of the derived abundances from molecular lines. High-resolution, near-IR spectra in the H band were recorded using VLT/CRIRES. Due to the high and variable visual extinction in the line-of-sight towards the bulge, an analysis in the near-IR is preferred. The CNO abundances can all be determined simultaneously from the numerous molecular lines in the wavelength range observed. The three giant stars in Baade's window presented here are the first bulge stars observed with CRIRES. We have especially determined the CNO abundances, with uncertainties of less than 0.20 dex, from CO, CN, and OH lines. Since the systematic uncertainties in the derived CNO abundances due to uncertainties in the stellar fundamental parameters, notably Teff, are significant, a detailed discussion of the sensitivities of the derived abundances is included. We find good agreement between near-IR and optically determined O, Ti, Fe, and Si abundances. Two of our stars show a solar [C+N/Fe], suggesting that these giants have experienced the first dredge-up and that the oxygen abundance should reflect the original abundance of the giants. The two giants fit into the picture, in which there is no significant difference between the O abundance in bulge and thick-disk stars. Our determination of the S abundances is the first for bulge stars. The high [S/Fe] values for all the stars indicate a high star-formation rate in an early phase of the bulge evolution.Comment: Accepted by A&