Recent Decisions

Comments on recent decisions by William A. Alder, William B. Ball, John F. Bodle, Wm. J. Braunlich, Jr., James A. Cassidy, John J. Cauley, F. J. Coufal, Louis F. Di Giovanni, George B. Kashmer, Robert D. Londergan, James W. Oberfell, Robert S. Olivier, William V. Phelan, John G. Smith, E. A. Steffen, Jr., Edward L. Twohey, and Robert R. Uhl

Neural Network Parameterizations of Electromagnetic Nucleon Form Factors

The electromagnetic nucleon form-factors data are studied with artificial feed forward neural networks. As a result the unbiased model-independent form-factor parametrizations are evaluated together with uncertainties. The Bayesian approach for the neural networks is adapted for chi2 error-like function and applied to the data analysis. The sequence of the feed forward neural networks with one hidden layer of units is considered. The given neural network represents a particular form-factor parametrization. The so-called evidence (the measure of how much the data favor given statistical model) is computed with the Bayesian framework and it is used to determine the best form factor parametrization.Comment: The revised version is divided into 4 sections. The discussion of the prior assumptions is added. The manuscript contains 4 new figures and 2 new tables (32 pages, 15 figures, 2 tables

Characterisation and expression of SPLUNC2, the human orthologue of rodent parotid secretory protein

We recently described the Palate Lung Nasal Clone (PLUNC) family of proteins as an extended group of proteins expressed in the upper airways, nose and mouth. Little is known about these proteins, but they are secreted into the airway and nasal lining fluids and saliva where, due to their structural similarity with lipopolysaccharide-binding protein and bactericidal/permeability-increasing protein, they may play a role in the innate immune defence. We now describe the generation and characterisation of novel affinity-purified antibodies to SPLUNC2, and use them to determine the expression of this, the major salivary gland PLUNC. Western blotting showed that the antibodies identified a number of distinct protein bands in saliva, whilst immunohistochemical analysis demonstrated protein expression in serous cells of the major salivary glands and in the ductal lumens as well as in cells of minor mucosal glands. Antibodies directed against distinct epitopes of the protein yielded different staining patterns in both minor and major salivary glands. Using RT-PCR of tissues from the oral cavity, coupled with EST analysis, we showed that the gene undergoes alternative splicing using two 5' non-coding exons, suggesting that the gene is regulated by alternative promoters. Comprehensive RACE analysis using salivary gland RNA as template failed to identify any additional exons. Analysis of saliva showed that SPLUNC2 is subject to N-glycosylation. Thus, our study shows that multiple SPLUNC2 isoforms are found in the oral cavity and suggest that these proteins may be differentially regulated in distinct tissues where they may function in the innate immune response

Astrobiological Complexity with Probabilistic Cellular Automata

Search for extraterrestrial life and intelligence constitutes one of the major endeavors in science, but has yet been quantitatively modeled only rarely and in a cursory and superficial fashion. We argue that probabilistic cellular automata (PCA) represent the best quantitative framework for modeling astrobiological history of the Milky Way and its Galactic Habitable Zone. The relevant astrobiological parameters are to be modeled as the elements of the input probability matrix for the PCA kernel. With the underlying simplicity of the cellular automata constructs, this approach enables a quick analysis of large and ambiguous input parameters' space. We perform a simple clustering analysis of typical astrobiological histories and discuss the relevant boundary conditions of practical importance for planning and guiding actual empirical astrobiological and SETI projects. In addition to showing how the present framework is adaptable to more complex situations and updated observational databases from current and near-future space missions, we demonstrate how numerical results could offer a cautious rationale for continuation of practical SETI searches.Comment: 37 pages, 11 figures, 2 tables; added journal reference belo

Current quark mass dependence of nucleon magnetic moments and radii

A calculation of the current-quark-mass-dependence of nucleon static electromagnetic properties is necessary in order to use observational data as a means to place constraints on the variation of Nature's fundamental parameters. A Poincare' covariant Faddeev equation, which describes baryons as composites of confined-quarks and -nonpointlike-diquarks, is used to calculate this dependence The results indicate that, like observables dependent on the nucleons' magnetic moments, quantities sensitive to their magnetic and charge radii, such as the energy levels and transition frequencies in Hydrogen and Deuterium, might also provide a tool with which to place limits on the allowed variation in Nature's constants.Comment: 23 pages, 2 figures, 4 tables, 4 appendice

Envelope Determinants of Equine Lentiviral Vaccine Protection

Lentiviral envelope (Env) antigenic variation and associated immune evasion present major obstacles to vaccine development. The concept that Env is a critical determinant for vaccine efficacy is well accepted, however defined correlates of protection associated with Env variation have yet to be determined. We reported an attenuated equine infectious anemia virus (EIAV) vaccine study that directly examined the effect of lentiviral Env sequence variation on vaccine efficacy. The study identified a significant, inverse, linear correlation between vaccine efficacy and increasing divergence of the challenge virus Env gp90 protein compared to the vaccine virus gp90. The report demonstrated approximately 100% protection of immunized ponies from disease after challenge by virus with a homologous gp90 (EV0), and roughly 40% protection against challenge by virus (EV13) with a gp90 13% divergent from the vaccine strain. In the current study we examine whether the protection observed when challenging with the EV0 strain could be conferred to animals via chimeric challenge viruses between the EV0 and EV13 strains, allowing for mapping of protection to specific Env sequences. Viruses containing the EV13 proviral backbone and selected domains of the EV0 gp90 were constructed and in vitro and in vivo infectivity examined. Vaccine efficacy studies indicated that homology between the vaccine strain gp90 and the N-terminus of the challenge strain gp90 was capable of inducing immunity that resulted in significantly lower levels of post-challenge virus and significantly delayed the onset of disease. However, a homologous N-terminal region alone inserted in the EV13 backbone could not impart the 100% protection observed with the EV0 strain. Data presented here denote the complicated and potentially contradictory relationship between in vitro virulence and in vivo pathogenicity. The study highlights the importance of structural conformation for immunogens and emphasizes the need for antibody binding, not neutralizing, assays that correlate with vaccine protection. © 2013 Craigo et al

A Measurement of Rb using a Double Tagging Method

The fraction of Z to bbbar events in hadronic Z decays has been measured by the OPAL experiment using the data collected at LEP between 1992 and 1995. The Z to bbbar decays were tagged using displaced secondary vertices, and high momentum electrons and muons. Systematic uncertainties were reduced by measuring the b-tagging efficiency using a double tagging technique. Efficiency correlations between opposite hemispheres of an event are small, and are well understood through comparisons between real and simulated data samples. A value of Rb = 0.2178 +- 0.0011 +- 0.0013 was obtained, where the first error is statistical and the second systematic. The uncertainty on Rc, the fraction of Z to ccbar events in hadronic Z decays, is not included in the errors. The dependence on Rc is Delta(Rb)/Rb = -0.056*Delta(Rc)/Rc where Delta(Rc) is the deviation of Rc from the value 0.172 predicted by the Standard Model. The result for Rb agrees with the value of 0.2155 +- 0.0003 predicted by the Standard Model.Comment: 42 pages, LaTeX, 14 eps figures included, submitted to European Physical Journal