CeO2-dolomite as fire retardant additives on the conventional intumescent coating in steel substrate for improved performance

Multiple combinations of CeO2-Dolomite as fillers and Intumescent Flame Retardant (IFR) ingredients were used to optimize the intumescent coatings designed for I-beam steel substrates. The influenced of fillers and various combinations of flame-retardants on the fire protective performance of the coatings were evaluated using vertical Bunsen burner fire test and various characterization techniques. Formula C and Formula F having 1:1 and 2:2 CeO2-Dolomite ratio, obtained the lowest substrate temperature around 150oC and 150.4oC, respectively after 90 minutes fire exposure. Also, the morphological structures of intumescent char observed by SEM-EDX, demonstrated that Formula C and Formula F stimulated the formation of homogeneous and more compacted surface structure. X-ray photoelectron spectroscopy (XPS) provide the binding energies of C and O constituents, it was observed that [-(C2H4)n-] was the most important free radical as it could promote the formation of aromatic carbon chain in the char surface. Finally, the findings of this study revealed that the selection of appropriate fillers and combinations of flame-retardant ingredients significantly influenced the morphological structure of the char layer, of which, Formula C and Formula F produced a char with higher thermal stability, resulting to a more fire resistive IFR coating during fire exposure

Phantom Inflation in Little Rip

We study the phantom inflation in little rip cosmology, in which the current acceleration is driven by the field with the parameter of state w < -1, but since w tends to -1 asymptotically, the rip singularity occurs only at infinite time. In this scenario, before the rip singularity is arrived, the universe is in an inflationary regime. We numerically calculate the spectrum of primordial perturbation generated during this period and find that the results may be consistent with observations. This implies that if the reheating happens again, the current acceleration might be just a start of phantom inflation responsible for the upcoming observational universe.Comment: 7 pages, 8 figures, discussion added, Appendix and refs. added, to be published in PL

Measurement of Electron Backscattering in the Energy Range of Neutron β\beta-Decay

We report on the first detailed measurements of electron backscattering from low Z targets at energies up to 124 keV. Both energy and angular distributions of the backscattered electrons are measured and compared with electron transport simulations based on the Geant4 and Penelope Monte Carlo simulation codes. Comparisons are also made with previous, less extensive, measurements and with measurements at lower energies.Comment: 9 pages, 8 figures, accepted for publication in Phys. Rev.

Connecting Mutations of the RNA Polymerase II C-Terminal Domain to Complex Phenotypic Changes Using Combined Gene Expression and Network Analyses

The C-terminal domain (CTD) of the largest subunit in DNA-dependent RNA polymerase II (RNAP II) is essential for mRNA synthesis and processing, through coordination of an astounding array of protein-protein interactions. Not surprisingly, CTD mutations can have complex, pleiotropic impacts on phenotype. For example, insertions of five alanine residues between CTD diheptads in yeast, which alter the CTD's overall tandem structure and physically separate core functional units, dramatically reduce growth rate and result in abnormally large cells that accumulate increased DNA content over time. Patterns by which specific CTD-protein interactions are disrupted by changes in CTD structure, as well as how downstream metabolic pathways are impacted, are difficult to target for direct experimental analyses. In an effort to connect an altered CTD to complex but quantifiable phenotypic changes, we applied network analyses of genes that are differentially expressed in our five alanine CTD mutant, combined with established genetic interactions from the Saccharomyces cerevisiae Genome Database (SGD). We were able to identify candidate genetic pathways, and several key genes, that could explain how this change in CTD structure leads to the specific phenotypic changes observed. These hypothetical networks identify links between CTD-associated proteins and mitotic function, control of cell cycle checkpoint mechanisms, and expression of cell wall and membrane components. Such results can help to direct future genetic and biochemical investigations that tie together the complex impacts of the CTD on global cellular metabolism

Humanized Rag1−/−γc−/− Mice Support Multilineage Hematopoiesis and Are Susceptible to HIV-1 Infection via Systemic and Vaginal Routes

Several new immunodeficient mouse models for human cell engraftment have recently been introduced that include the Rag2−/−γc−/−, NOD/SCID, NOD/SCIDγc−/− and NOD/SCIDβ2m−/− strains. Transplantation of these mice with CD34+ human hematopoietic stem cells leads to prolonged engraftment, multilineage hematopoiesis and the capacity to generate human immune responses against a variety of antigens. However, the various mouse strains used and different methods of engrafting human cells are beginning to illustrate strain specific variations in engraftment levels, duration and longevity of mouse life span. In these proof-of-concept studies we evaluated the Balb/c-Rag1−/−γ−/− strain for engraftment by human fetal liver derived CD34+ hematopoietic cells using the same protocol found to be effective for Balb/c-Rag2−/−γc−/− mice. We demonstrate that these mice can be efficiently engrafted and show multilineage human hematopoiesis with human cells populating different lymphoid organs. Generation of human cells continues beyond a year and production of human immunoglobulins is noted. Infection with HIV-1 leads to chronic viremia with a resultant CD4 T cell loss. To mimic the predominant sexual viral transmission, we challenged humanized Rag1−/−γc−/− mice with HIV-1 via vaginal route which also resulted in chronic viremia and helper T cell loss. Thus these mice can be further exploited for studying human pathogens that infect the human hematopoietic system in an in vivo setting

The evolution of new enzyme function: lessons from xenobiotic metabolizing bacteria versus insecticide-resistant insects

Here, we compare the evolutionary routes by which bacteria and insects have evolved enzymatic processes for the degradation of four classes of synthetic chemical insecticide. For insects, the selective advantage of such degradative activities is survival on exposure to the insecticide, whereas for the bacteria the advantage is simply a matter of access to additional sources of nutrients. Nevertheless, bacteria have evolved highly efficient enzymes from a wide variety of enzyme families, whereas insects have relied upon generalist esterase-, cytochrome P450- and glutathione-S-transferase-dependent detoxification systems. Moreover, the mutant insect enzymes are less efficient kinetically and less diverged in sequence from their putative ancestors than their bacterial counterparts. This presumably reflects several advantages that bacteria have over insects in the acquisition of new enzymatic functions, such as a broad biochemical repertoire from which new functions can be evolved, large population sizes, high effective mutation rates, very short generation times and access to genetic diversity through horizontal gene transfer. Both the insect and bacterial systems support recent theory proposing that new biochemical functions often evolve from ‘promiscuous’ activities in existing enzymes, with subsequent mutations then enhancing those activities. Study of the insect enzymes will help in resistance management, while the bacterial enzymes are potential bioremediants of insecticide residues in a range of contaminated environments

Simulated Evolution of Protein-Protein Interaction Networks with Realistic Topology

We model the evolution of eukaryotic protein-protein interaction (PPI) networks. In our model, PPI networks evolve by two known biological mechanisms: (1) Gene duplication, which is followed by rapid diversification of duplicate interactions. (2) Neofunctionalization, in which a mutation leads to a new interaction with some other protein. Since many interactions are due to simple surface compatibility, we hypothesize there is an increased likelihood of interacting with other proteins in the target protein’s neighborhood. We find good agreement of the model on 10 different network properties compared to high-confidence experimental PPI networks in yeast, fruit flies, and humans. Key findings are: (1) PPI networks evolve modular structures, with no need to invoke particular selection pressures. (2) Proteins in cells have on average about 6 degrees of separation, similar to some social networks, such as human-communication and actor networks. (3) Unlike social networks, which have a shrinking diameter (degree of maximum separation) over time, PPI networks are predicted to grow in diameter. (4) The model indicates that evolutionarily old proteins should have higher connectivities and be more centrally embedded in their networks. This suggests a way in which present-day proteomics data could provide insights into biological evolution

Using graph theory to analyze biological networks

Understanding complex systems often requires a bottom-up analysis towards a systems biology approach. The need to investigate a system, not only as individual components but as a whole, emerges. This can be done by examining the elementary constituents individually and then how these are connected. The myriad components of a system and their interactions are best characterized as networks and they are mainly represented as graphs where thousands of nodes are connected with thousands of vertices. In this article we demonstrate approaches, models and methods from the graph theory universe and we discuss ways in which they can be used to reveal hidden properties and features of a network. This network profiling combined with knowledge extraction will help us to better understand the biological significance of the system

High Density SNP Screen in A Large Multiplex Neural Tube Defect Family Refines Linkage to Loci at 7p21-Pter And 2q33.1-35

Neural tube defects (NTDs) are considered complex with both genetic and environmental factors implicated. To date, no major causative genes have been identified in humans despite several investigations. The first genomewide screen in NTDs (Rampersaud et al. 2005) demonstrated evidence of linkage to chromosomes 7 and 10. This screen included forty-four multiplex families and consisted of 402 microsatellite markers spaced approximately 10 cM apart. Further investigation of the genomic screen data identified a single large multiplex family, pedigree 8776, as primarily driving the linkage results on chromosome 7

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead