Grants for Libraries

More and more libraries, museums and cultural institutions rely on fundraising and grant writing to sustain their services, special projects, or new initiatives Since most MLIS programs do not include grant project planning and proposal writing as part of their curriculum, librarians learn the process through trial and error, or continuing education classes. There are numerous books and websites that can assist the novice grant writer. We hope to provide beginners with basic information on the types of grants available, where to look for funding agencies, selected grant writing resources, and a few helpful grant writing hints to get you started. The presentation will be a three-person panel providing a short overview of the areas mentioned above, and discussion of sample grants submitted or received. The overview will be presented in Power Point format with an accompanying handout for each attendee

Characterization of a Conserved Interaction between DNA Glycosylase and ParA in Mycobacterium smegmatis and M. tuberculosis

The chromosome partitioning proteins, ParAB, ensure accurate segregation of genetic materials into daughter cells and most bacterial species contain their homologs. However, little is known about the regulation of ParAB proteins. In this study, we found that 3-methyladenine DNA glycosylase I MsTAG(Ms5082) regulates bacterial growth and cell morphology by directly interacting with MsParA (Ms6939) and inhibiting its ATPase activity in Mycobacterium smegmatis. Using bacterial two-hybrid and pull-down techniques in combination with co-immunoprecipitation assays, we show that MsTAG physically interacts with MsParA both in vitro and in vivo. Expression of MsTAG under conditions of DNA damage induction exhibited similar inhibition of growth as the deletion of the parA gene in M. smegmatis. Further, the effect of MsTAG on mycobacterial growth was found to be independent of its DNA glycosylase activity, and to result instead from direct inhibition of the ATPase activity of MsParA. Co-expression of these two proteins could counteract the growth defect phenotypes observed in strains overexpressing MsTAG alone in response to DNA damage induction. Based on protein co-expression and fluorescent co-localization assays, MsParA and MsTAG were further found to co-localize in mycobacterial cells. In addition, the interaction between the DNA glycosylase and ParA, and the regulation of ParA by the glycosylase were conserved in M. tuberculosis and M. smegmatis. Our findings provide important new insights into the regulatory mechanism of cell growth and division in mycobacteria

PSORTb 3.0: improved protein subcellular localization prediction with refined localization subcategories and predictive capabilities for all prokaryotes

Motivation: PSORTb has remained the most precise bacterial protein subcellular localization (SCL) predictor since it was first made available in 2003. However, the recall needs to be improved and no accurate SCL predictors yet make predictions for archaea, nor differentiate important localization subcategories, such as proteins targeted to a host cell or bacterial hyperstructures/organelles. Such improvements should preferably be encompassed in a freely available web-based predictor that can also be used as a standalone program

Exact Hybrid Particle/Population Simulation of Rule-Based Models of Biochemical Systems

Detailed modeling and simulation of biochemical systems is complicated by the problem of combinatorial complexity, an explosion in the number of species and reactions due to myriad protein-protein interactions and post-translational modifications. Rule-based modeling overcomes this problem by representing molecules as structured objects and encoding their interactions as pattern-based rules. This greatly simplifies the process of model specification, avoiding the tedious and error prone task of manually enumerating all species and reactions that can potentially exist in a system. From a simulation perspective, rule-based models can be expanded algorithmically into fully-enumerated reaction networks and simulated using a variety of network-based simulation methods, such as ordinary differential equations or Gillespie's algorithm, provided that the network is not exceedingly large. Alternatively, rule-based models can be simulated directly using particle-based kinetic Monte Carlo methods. This "network-free" approach produces exact stochastic trajectories with a computational cost that is independent of network size. However, memory and run time costs increase with the number of particles, limiting the size of system that can be feasibly simulated. Here, we present a hybrid particle/population simulation method that combines the best attributes of both the network-based and network-free approaches. The method takes as input a rule-based model and a user-specified subset of species to treat as population variables rather than as particles. The model is then transformed by a process of "partial network expansion" into a dynamically equivalent form that can be simulated using a population-adapted network-free simulator. The transformation method has been implemented within the open-source rule-based modeling platform BioNetGen, and resulting hybrid models can be simulated using the particle-based simulator NFsim. Performance tests show that significant memory savings can be achieved using the new approach and a monetary cost analysis provides a practical measure of its utility. © 2014 Hogg et al

Fitting the HIV Epidemic in Zambia: A Two-Sex Micro-Simulation Model

BACKGROUND: In describing and understanding how the HIV epidemic spreads in African countries, previous studies have not taken into account the detailed periods at risk. This study is based on a micro-simulation model (individual-based) of the spread of the HIV epidemic in the population of Zambia, where women tend to marry early and where divorces are not frequent. The main target of the model was to fit the HIV seroprevalence profiles by age and sex observed at the Demographic and Health Survey conducted in 2001. METHODS AND FINDINGS: A two-sex micro-simulation model of HIV transmission was developed. Particular attention was paid to precise age-specific estimates of exposure to risk through the modelling of the formation and dissolution of relationships: marriage (stable union), casual partnership, and commercial sex. HIV transmission was exclusively heterosexual for adults or vertical (mother-to-child) for children. Three stages of HIV infection were taken into account. All parameters were derived from empirical population-based data. Results show that basic parameters could not explain the dynamics of the HIV epidemic in Zambia. In order to fit the age and sex patterns, several assumptions were made: differential susceptibility of young women to HIV infection, differential susceptibility or larger number of encounters for male clients of commercial sex workers, and higher transmission rate. The model allowed to quantify the role of each type of relationship in HIV transmission, the proportion of infections occurring at each stage of disease progression, and the net reproduction rate of the epidemic (R(0) = 1.95). CONCLUSIONS: The simulation model reproduced the dynamics of the HIV epidemic in Zambia, and fitted the age and sex pattern of HIV seroprevalence in 2001. The same model could be used to measure the effect of changing behaviour in the future

Observation of Charge-Dependent Azimuthal Correlations in p-Pb Collisions and Its Implication for the Search for the Chiral Magnetic Effect

Peer reviewe

Pseudorapidity distributions of charged hadrons in proton-lead collisions at root s(NN)=5:02 and 8.16 TeV

The pseudorapidity distributions of charged hadrons in proton-lead collisions at nucleon-nucleon center-of-mass energies root s(NN) = 5.02 and 8.16 TeV are presented. The measurements are based on data samples collected by the CMS experiment at the LHC. The number of primary charged hadrons produced in non-single-diffractive proton-lead collisions is determined in the pseudorapidity range vertical bar eta(lab)vertical bar vertical bar(vertical bar eta cm vertical bar) <0.5 are 17.1 +/- 0.01 (stat) +/- 0.59 (syst) and 20.10 +/- 0.01 (stat) +/- 0.5(syst) at root s(NN) = 5.02 and 8.16 TeV, respectively. The particle densities per participant nucleon are compared to similar measurements in proton-proton, proton-nucleus, and nucleus-nucleus collisions.Peer reviewe

Search for Supersymmetry in pp Collisions at root s=13 TeV in the Single-Lepton Final State Using the Sum of Masses of Large-Radius Jets

Peer reviewe

Measurement of the B-+/- Meson Nuclear Modification Factor in Pb-Pb Collisions at root s(NN)=5.02 TeV

Peer reviewe

Measurement of b hadron lifetimes in pp collisions at root s=8TeV

Correction: DOI:10.1140/epjc/s10052-018-6014-7Measurements are presented of the lifetimes of the B-0, B-s(0), Lambda(0)(b), and B-c(+) hadrons using the decay channels B-0 -> J/psi K*(892)(0), B-0 -> J/psi K-S(0), B-s(0) -> J/psi pi(+)pi(-), B-s(0) -> J/psi phi(1020), Lambda(0)(b) -> J/psi Lambda(0), and B-c(+) -> J/psi pi(+). The data sample, corresponding to an integrated luminosity of 19.7 fb(-1), was collected by the CMS detector at the LHC in proton-proton collisions at root s = 8TeV. The B-0 life-time is measured to be 453.0 +/- 1.6 (stat) +/- 1.8 (syst) mu m in J/psi K*(892)(0) and 457.8 +/- 2.7 (stat) +/- 2.8 (syst) mu m in J/psi K-S(0), which results in a combined measurement of c tau(0) = 454.1 +/- 1.4 (stat) +/- 1.7 (syst) mu m. The effective lifetime of the B-s(0) meson is measured in two decay modes, with contributions from different amounts of the heavy and light eigenstates. This results in two different measured lifetimes: c tau(0)(Bs) -> J/psi pi(+)pi(-) = 502.7 +/- 10.2 (stat) +/- 3.4 (syst) mu m and c tau(0)(Bs) -> J/psi phi(1020) = 443.9 +/- 2.0 (stat) +/- 1.5 (syst) mu m. The Lambda(0)(b) lifetime is found to be 442.9 +/- 8.2 (stat) +/- 2.8 (syst) mu m. The precision from each of these channels is as good as or better than previous measurements. The B-c(+) lifetime, measured with respect to the B+ to reduce the systematic uncertainty, is 162.3 +/- 7.8 (stat) +/- 4.2 (syst) +/- 0.1 (tau(B+)) mu m. All results are in agreement with current world-average values.Peer reviewe