34 research outputs found
COSORE: A community database for continuous soil respiration and other soilâatmosphere greenhouse gas flux data
Globally, soils store two to three times as much carbon as currently resides in the atmosphere, and it is critical to understand how soil greenhouse gas (GHG) emissions and uptake will respond to ongoing climate change. In particular, the soilâtoâatmosphere CO2 flux, commonly though imprecisely termed soil respiration (RS), is one of the largest carbon fluxes in the Earth system. An increasing number of highâfrequency RS measurements (typically, from an automated system with hourly sampling) have been made over the last two decades; an increasing number of methane measurements are being made with such systems as well. Such high frequency data are an invaluable resource for understanding GHG fluxes, but lack a central database or repository. Here we describe the lightweight, openâsource COSORE (COntinuous SOil REspiration) database and software, that focuses on automated, continuous and longâterm GHG flux datasets, and is intended to serve as a community resource for earth sciences, climate change syntheses and model evaluation. Contributed datasets are mapped to a single, consistent standard, with metadata on contributors, geographic location, measurement conditions and ancillary data. The design emphasizes the importance of reproducibility, scientific transparency and open access to data. While being oriented towards continuously measured RS, the database design accommodates other soilâatmosphere measurements (e.g. ecosystem respiration, chamberâmeasured net ecosystem exchange, methane fluxes) as well as experimental treatments (heterotrophic only, etc.). We give brief examples of the types of analyses possible using this new community resource and describe its accompanying R software package
Patient-derived xenograft (PDX) models in basic and translational breast cancer research
Patient-derived xenograft (PDX) models of a growing spectrum of cancers are rapidly supplanting long-established traditional cell lines as preferred models for conducting basic and translational preclinical research. In breast cancer, to complement the now curated collection of approximately 45 long-established human breast cancer cell lines, a newly formed consortium of academic laboratories, currently from Europe, Australia, and North America, herein summarizes data on over 500 stably transplantable PDX models representing all three clinical subtypes of breast cancer (ER+, HER2+, and "Triple-negative" (TNBC)). Many of these models are well-characterized with respect to genomic, transcriptomic, and proteomic features, metastatic behavior, and treatment response to a variety of standard-of-care and experimental therapeutics. These stably transplantable PDX lines are generally available for dissemination to laboratories conducting translational research, and contact information for each collection is provided. This review summarizes current experiences related to PDX generation across participating groups, efforts to develop data standards for annotation and dissemination of patient clinical information that does not compromise patient privacy, efforts to develop complementary data standards for annotation of PDX characteristics and biology, and progress toward "credentialing" of PDX models as surrogates to represent individual patients for use in preclinical and co-clinical translational research. In addition, this review highlights important unresolved questions, as well as current limitations, that have hampered more efficient generation of PDX lines and more rapid adoption of PDX use in translational breast cancer research
Nitrogenase-mimic iron-containing chalcogels for photochemical reduction of dinitrogen to ammonia
Simulation of the VUV Absorption Spectra of Oxygenates and Hydrocarbons: A Joint TheoreticalâExperimental Study
Vacuum UV absorption spectroscopy is regularly used to
provide
unambiguous identification of a target species, insight into the electronic
structure of molecules, and quantitative species concentrations. As
molecules of interest have become more complex, theoretical spectra
have been used in tandem with laboratory spectroscopic analysis or
as a replacement when experimental data is unavailable. However, it
is difficult to determine which theoretical methodologies can best
simulate experiment. This study examined the performance of EOM-CCSD
and 10 TD-DFT functionals (B3LYP, BH&HLYP, BMK, CAM-B3LYP, HSE,
M06-2X, M11, PBE0, ÏB97X-D, and X3LYP) to produce reliable vacuum
UV absorption spectra for 19 small oxygenates and hydrocarbons using
vertical excitation energies. The simulated spectra were analyzed
against experiment using both a qualitative analysis and quantitative
metrics, including cosine similarity, relative integral change, mean
signed error, and mean absolute error. Based on our ranking system,
it was determined that M06-2X was consistently the top performing
TD-DFT method with BMK, CAM-B3LYP, and ÏB97X-D also producing
reliable spectra for these small combustion species
Simulation of the VUV Absorption Spectra of Oxygenates and Hydrocarbons: A Joint TheoreticalâExperimental Study
Vacuum UV absorption spectroscopy is regularly used to
provide
unambiguous identification of a target species, insight into the electronic
structure of molecules, and quantitative species concentrations. As
molecules of interest have become more complex, theoretical spectra
have been used in tandem with laboratory spectroscopic analysis or
as a replacement when experimental data is unavailable. However, it
is difficult to determine which theoretical methodologies can best
simulate experiment. This study examined the performance of EOM-CCSD
and 10 TD-DFT functionals (B3LYP, BH&HLYP, BMK, CAM-B3LYP, HSE,
M06-2X, M11, PBE0, ÏB97X-D, and X3LYP) to produce reliable vacuum
UV absorption spectra for 19 small oxygenates and hydrocarbons using
vertical excitation energies. The simulated spectra were analyzed
against experiment using both a qualitative analysis and quantitative
metrics, including cosine similarity, relative integral change, mean
signed error, and mean absolute error. Based on our ranking system,
it was determined that M06-2X was consistently the top performing
TD-DFT method with BMK, CAM-B3LYP, and ÏB97X-D also producing
reliable spectra for these small combustion species