Hydrothermal sensitivities of seed populations underlie fluctuations of dormancy states in an annual plant community

Plant germination ecology involves continuous interactions between changing environmental conditions and the sensitivity of seed populations to respond to those conditions at a given time. Ecologically meaningful parameters characterizing germination capacity (or dormancy) are needed to advance our understanding of the evolution of germination strategies within plant communities. The germination traits commonly examined (e.g., maximum germination percentage under optimal conditions) may not adequately reflect the critical ecological differences in germination behavior across species, communities, and seasons. In particular, most seeds exhibit primary dormancy at dispersal that is alleviated by exposure to dry after-ripening or to hydrated chilling to enable germination in a subsequent favorable season. Population-based threshold (PBT) models of seed germination enable quantification of patterns of germination timing using parameters based on mechanistic assumptions about the underlying germination physiology. We applied the hydrothermal time (HTT) model, a type of PBT model that integrates environmental temperature and water availability, to study germination physiology in a guild of coexisting desert annual species whose seeds were after-ripened by dry storage under different conditions. We show that HTT assumptions are valid for describing germination physiology in these species, including loss of dormancy during after-ripening. Key HTT parameters, the hydrothermal time constant (θHT ) and base water potential distribution among seeds (Ψb (g)), were effective in describing changes in dormancy states and in clustering species exhibiting similar germination syndromes. θHT is an inherent species-specific trait relating to timing of germination that correlates well with long-term field germination fraction, while Ψb (g) shifts with depth of dormancy in response to after-ripening and seasonal environmental variation. Predictions based on variation among coexisting species in θHT and Ψb (g) in laboratory germination tests matched well with 25-yr observations of germination dates and fractions for the same species in natural field conditions. Seed dormancy and germination strategies, which are significant contributors to long-term species demographics under natural conditions, can be represented by readily measurable functional traits underlying variation in germination phenologies.This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Differing Lectin Binding Profiles among Human Embryonic Stem Cells and Derivatives Aid in the Isolation of Neural Progenitor Cells

Human embryonic stem cells (hESCs) and their differentiated progeny allow for investigation of important changes/events during normal embryonic development. Currently most of the research is focused on proteinacous changes occurring as a result of differentiation of stem cells and little is known about changes in cell surface glycosylation patterns. Identification of cell lineage specific glycans can help in understanding their role in maintenance, proliferation and differentiation. Furthermore, these glycans can serve as markers for isolation of homogenous populations of cells. Using a panel of eight biotinylated lectins, the glycan expression of hESCs, hESCs-derived human neural progenitors (hNP) cells, and hESCs-derived mesenchymal progenitor (hMP) cells was investigated. Our goal was to identify glycans that are unique for hNP cells and use the corresponding lectins for cell isolation. Flow cytometry and immunocytochemistry were used to determine expression and localization of glycans, respectively, in each cell type. These results show that the glycan expression changes upon differentiation of hESCs and is different for neural and mesenchymal lineage. For example, binding of PHA-L lectin is low in hESCs (14±4.4%) but significantly higher in differentiated hNP cells (99±0.4%) and hMP cells (90±3%). Three lectins: VVA, DBA and LTL have low binding in hESCs and hMP cells, but significantly higher binding in hNP cells. Finally, VVA lectin binding was used to isolate hNP cells from a mixed population of hESCs, hNP cells and hMP cells. This is the first report that compares glycan expression across these human stem cell lineages and identifies significant differences. Also, this is the first study that uses VVA lectin for isolation for human neural progenitor cells

Synthesis of N-Acyl-N,O-Acetals from N-Aryl Amides and Acetals in the Presence of TMSOTf

Secondary amides undergo in situ silyl imidate formation mediated by TMSOTf and an amine base, followed by addition to acetal acceptors to provide N-acyl-N,O-acetals in good yields. An analogous, high-yielding reaction is observed with 2-mercaptothiazoline as the silyl imidate precursor. Competing reduction of the acetal to the corresponding methyl ether via transfer hydrogenation can be circumvented by the replacement of i-Pr2NEt with 2,6-lutidine under otherwise identical reaction conditions

ProLuCID: An improved SEQUEST-like algorithm with enhanced sensitivity and specificity.

ProLuCID, a new algorithm for peptide identification using tandem mass spectrometry and protein sequence databases has been developed. This algorithm uses a three tier scoring scheme. First, a binomial probability is used as a preliminary scoring scheme to select candidate peptides. The binomial probability scores generated by ProLuCID minimize molecular weight bias and are independent of database size. A modified cross-correlation score is calculated for each candidate peptide identified by the binomial probability. This cross-correlation scoring function models the isotopic distributions of fragment ions of candidate peptides which ultimately results in higher sensitivity and specificity than that obtained with the SEQUEST XCorr. Finally, ProLuCID uses the distribution of XCorr values for all of the selected candidate peptides to compute a Z score for the peptide hit with the highest XCorr. The ProLuCID Z score combines the discriminative power of XCorr and DeltaCN, the standard parameters for assessing the quality of the peptide identification using SEQUEST, and displays significant improvement in specificity over ProLuCID XCorr alone. ProLuCID is also able to take advantage of high resolution MS/MS spectra leading to further improvements in specificity when compared to low resolution tandem MS data. A comparison of filtered data searched with SEQUEST and ProLuCID using the same false discovery rate as estimated by a target-decoy database strategy, shows that ProLuCID was able to identify as many as 25% more proteins than SEQUEST. ProLuCID is implemented in Java and can be easily installed on a single computer or a computer cluster. This article is part of a Special Issue entitled: Computational Proteomics

CHARMM-GUI Membrane Builder Toward Realistic Biological Membrane Simulations

This is the peer reviewed version of the following article: Wu, E. L., Cheng, X., Jo, S., Rui, H., Song, K. C., Dávila-Contreras, E. M., … Im, W. (2014). CHARMM-GUI Membrane Builder Toward Realistic Biological Membrane Simulations. Journal of Computational Chemistry, 35(27), 1997–2004. http://doi.org/10.1002/jcc.23702, which has been published in final form at http://doi.org/10.1002/jcc.23702. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.CHARMM-GUI Membrane Builder, http://www.charmm-gui.org/input/membrane, is a web-based user interface designed to interactively build all-atom protein/membrane or membrane-only systems for molecular dynamics simulation through an automated optimized process. In this work, we describe the new features and major improvements in Membrane Builderthat allow users to robustly build realistic biological membrane systems, including (1) addition of new lipid types such as phosphoinositides, cardiolipin, sphingolipids, bacterial lipids, and ergosterol, yielding more than 180 lipid types, (2) enhanced building procedure for lipid packing around protein, (3) reliable algorithm to detect lipid tail penetration to ring structures and protein surface, (4) distance-based algorithm for faster initial ion displacement, (5) CHARMM inputs for P21 image transformation, and (6) NAMD equilibration and production inputs. The robustness of these new features is illustrated by building and simulating a membrane model of the polar and septal regions of E. coli membrane, which contains five lipid types: cardiolipin lipids with two types of acyl chains and phosphatidylethanolamine lipids with three types of acyl chains. It is our hope that CHARMM-GUI Membrane Builder becomes a useful tool for simulation studies to better understand the structure and dynamics of proteins and lipids in realistic biological membrane environments

Water Vapor Measurements by Howard University Raman Lidar during the WAVES 2006 Campaign

Retrieval of water vapor mixing ratio using the Howard University Raman Lidar is presented with emphasis on three aspects: i) performance of the lidar against collocated radiosondes and Raman lidar, ii) investigation of the atmospheric state variables when poor agreement between lidar and radiosondes values occurred and iii) a comparison with satellite-based measurements. The measurements were acquired during the Water Vapor Validation Experiment Sondes/Satellites 2006 field campaign. Ensemble averaging of water vapor mixing ratio data from ten night-time comparisons with Vaisala RS92 radiosondes shows on average an agreement within 10 % up to approx. 8 km. A similar analysis of lidar-to-lidar data of over 700 profiles revealed an agreement to within 20 % over the first 7 km (10 % below 4 km). A grid analysis, defined in the temperature - relative humidity space, was developed to characterize the lidar - radiosonde agreement and quantitatively localizes regions of strong and weak correlations as a function of altitude, temperature or relative humidity. Three main regions of weak correlation emerge: i) regions of low relative humidity and low temperature, ii) moderate relative humidity at low temperatures and iii) low relative humidity at moderate temperatures. Comparison of Atmospheric InfraRed Sounder and Tropospheric Emission Sounder satellites retrievals of moisture with that of Howard University Raman Lidar showed a general agreement in the trend but the formers miss a lot of the details in atmospheric structure due to their low resolution. A relative difference of about 20 % is usually found between lidar and satellites measurements

Volume-energy correlations in the slow degrees of freedom of computer-simulated phospholipid membranes

Constant-pressure molecular-dynamics simulations of phospholipid membranes in the fluid phase reveal strong correlations between equilibrium fluctuations of volume and energy on the nanosecond time-scale. The existence of strong volume-energy correlations was previously deduced indirectly by Heimburg from experiments focusing on the phase transition between the fluid and the ordered gel phases. The correlations, which are reported here for three different membranes (DMPC, DMPS-Na, and DMPSH), have volume-energy correlation coefficients ranging from 0.81 to 0.89. The DMPC membrane was studied at two temperatures showing that the correlation coefficient increases as the phase transition is approached

ProLuCID: An improved SEQUEST-like algorithm with enhanced sensitivity and specificity

AbstractProLuCID, a new algorithm for peptide identification using tandem mass spectrometry and protein sequence databases has been developed. This algorithm uses a three tier scoring scheme. First, a binomial probability is used as a preliminary scoring scheme to select candidate peptides. The binomial probability scores generated by ProLuCID minimize molecular weight bias and are independent of database size. A modified cross-correlation score is calculated for each candidate peptide identified by the binomial probability. This cross-correlation scoring function models the isotopic distributions of fragment ions of candidate peptides which ultimately results in higher sensitivity and specificity than that obtained with the SEQUEST XCorr. Finally, ProLuCID uses the distribution of XCorr values for all of the selected candidate peptides to compute a Z score for the peptide hit with the highest XCorr. The ProLuCID Z score combines the discriminative power of XCorr and DeltaCN, the standard parameters for assessing the quality of the peptide identification using SEQUEST, and displays significant improvement in specificity over ProLuCID XCorr alone. ProLuCID is also able to take advantage of high resolution MS/MS spectra leading to further improvements in specificity when compared to low resolution tandem MS data. A comparison of filtered data searched with SEQUEST and ProLuCID using the same false discovery rate as estimated by a target-decoy database strategy, shows that ProLuCID was able to identify as many as 25% more proteins than SEQUEST. ProLuCID is implemented in Java and can be easily installed on a single computer or a computer cluster.This article is part of a Special Issue entitled: Computational Proteomics

Behavior and Impact of Zirconium in the Soil–Plant System: Plant Uptake and Phytotoxicity

Because of the large number of sites they pollute, toxic metals that contaminate terrestrial ecosystems are increasingly of environmental and sanitary concern (Uzu et al. 2010, 2011; Shahid et al. 2011a, b, 2012a). Among such metals is zirconium (Zr), which has the atomic number 40 and is a transition metal that resembles titanium in physical and chemical properties (Zaccone et al. 2008). Zr is widely used in many chemical industry processes and in nuclear reactors (Sandoval et al. 2011; Kamal et al. 2011), owing to its useful properties like hardness, corrosion-resistance and permeable to neutrons (Mushtaq 2012). Hence, the recent increased use of Zr by industry, and the occurrence of the Chernobyl and Fukashima catastrophe have enhanced environmental levels in soil and waters (Yirchenko and Agapkina 1993; Mosulishvili et al. 1994 ; Kruglov et al. 1996)

HCI policy and the smart city

While the idea of the ‘Smart City’ has attracted increasing attention from academia, industry, and government this interest has largely had a technical and technological focus. This paper identifies some of the important political and policy challenges facing the idea, the discourse, of a ‘smart city’ as a means to optimise HCI input into the ‘smart city’ debate. It then addresses that gap by detailing a research project that explored how experts in smart city research and development in the UK context responded to this policy challenge. Experts were asked questions regarding their prior experience with the “smart city”, their understandings of what it means for a city to be smart, and what policy potentials they've recognised in the smart city. The paper analyses and offers a synthesis of the responses collected throughout the research with the current policies concerning various smart city proximity, thereby providing a critical assessment of the values underlying the smart city. The paper aims to explore and present some of the policy possibilities for UK smart cities that are potentially useful for politicians, policy makers, planners, academics, and technology companies. I believe that these perspectives for policy development can be used to inform responsible development, spatially and socially inclusive technologies, and ultimately more resilient and liveable cities