Substrate Scope for Human Histone Lysine Acetyltransferase KAT8

Biomedically important histone lysine acetyltransferase KAT8 catalyses the acetyl coenzyme A-dependent acetylation of lysine on histone and other proteins. Here, we explore the ability of human KAT8 to catalyse the acetylation of histone H4 peptides possessing lysine and its analogues at position 16 (H4K16). Our synthetic and enzymatic studies on chemically and structurally diverse lysine mimics demonstrate that KAT8 also has a capacity to acetylate selected lysine analogues that possess subtle changes on the side chain and main chain. Overall, this work highlights that KAT8 has a broader substrate scope beyond natural lysine, and contributes to the design of new chemical probes targeting KAT8 and other members of the histone lysine acetyltransferase (KAT) family.     

Cloud computing-based parallel genetic algorithm for gene selection in cancer classification

Cancer classification is one of the main steps during patient healing process. This fact enforces modern clinical researchers to use advanced bioinformatics methods for cancer classification. Cancer classification is usually performed using gene expression data gained in microarray experiment and advanced machine learning methods. Microarray experiment generates huge amount of data, and its processing via machine learning methods represents a big challenge. In this study, two-step classification paradigm which merges genetic algorithm feature selection and machine learning classifiers is utilized. Genetic algorithm is built in MapReduce programming spirit which makes this algorithm highly scalable for Hadoop cluster. In order to improve the performance of the proposed algorithm, it is extended into a parallel algorithm which process on microarray data in distributed manner using the Hadoop MapReduce framework. In this paper, the algorithm was tested on eleven GEMS data sets (9 tumors, 11 tumors, 14 tumors, brain tumor 1, lung cancer, brain tumor 2, leukemia 1, DLBCL, leukemia 2, SRBCT, and prostate tumor) and its accuracy reached 100% for less than 25 selected features. The proposed cloud computing-based MapReduce parallel genetic algorithm performed well on gene expression data. In addition, the scalability of the suggested algorithm is unlimited because of underlying Hadoop MapReduce platform. The presented results indicate that the proposed method can be effectively implemented for real-world microarray data in the cloud environment. In addition, the Hadoop MapReduce framework demonstrates substantial decrease in the computation time.

     

Soundness and Completeness Proofs by Coinductive Methods

We show how codatatypes can be employed to produce compact, high-level proofs of key results in logic: the soundness and completeness of proof systems for variations of first-order logic. For the classical completeness result, we first establish an abstract property of possibly infinite derivation trees. The abstract proof can be instantiated for a wide range of Gentzen and tableau systems for various flavors of first-order logic. Soundness becomes interesting as soon as one allows infinite proofs of first-order formulas. This forms the subject of several cyclic proof systems for first-order logic augmented with inductive predicate definitions studied in the literature. All the discussed results are formalized using Isabelle/HOL’s recently introduced support for codatatypes and corecursion. The development illustrates some unique features of Isabelle/HOL’s new coinductive specification language such as nesting through non-free types and mixed recursion–corecursion.     

Relational analysis of (co)inductive predicates, (co)algebraic datatypes, and (co)recursive functions

We present techniques for applying a finite relational model finder to logical specifications that involve high-level definitional principles such as (co)inductive predicates, (co)algebraic datatypes, and (co)recursive functions. In contrast to previous work, which focused on algebraic datatypes and restricted occurrences of unbounded quantifiers in formulas, we can handle arbitrary formulas by means of a three-valued Kleene logic. The techniques form the basis of the counterexample generator Nitpick for Isabelle/HOL. As case studies, we consider formulas about an inductively defined context-free grammar, a functional implementation of AA trees, and a coalgebraic list datatype.     

Deficits in complex motor functions, despite no evidence of procedural learning deficits, among HIV+ individuals with history of substance dependence.

Human immunodeficiency virus (HIV) and drugs of abuse affect common neural systems underlying procedural memory, including the striatum. The authors compared performance of 48 HIV seropositive (HIV+) and 48 HIV seronegative (HIV-) participants with history of cocaine and/or heroin dependence across multiple Trial Blocks of three procedural learning (PL) tasks: Rotary Pursuit (RP), Mirror Star Tracing (MST), and Weather Prediction (WP). Groups were well matched on demographic, psychiatric, and substance use parameters, and all participants were verified abstinent from drugs. Mixed model analyses of variance revealed that the individuals in the HIV+ group performed more poorly across all tasks, with a significant main effect of HIV serostatus observed on the Mirror Star Tracing and a trend toward significance obtained for the Rotary Pursuit task. No significant differences were observed on the Weather Prediction task. Both groups demonstrated significant improvements in performance across all three procedural learning tasks. It is important to note that no significant Serostatus × Trial Block interactions were observed on any task. Thus, the individuals in the HIV+ group tended to perform worse than those in the HIV- group across all trial blocks of procedural learning tasks with motor demands, but showed no differences in their rate of improvement across all tasks. These findings are consistent with HIV--associated deficits in complex motor skills, but not in procedural learning. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A Thermodynamic Investigation of the Redox Properties of VPO Catalysts

Abstract  

The redox properties of a vanadium phosphorus oxide (VPO) catalyst with a V:P ratio of one were investigated using Coulometric Titration at 873 K. Equilibrium between (VO)₂P₂O₇ and VOPO₄ exists at a P(O₂) of 3 × 10⁻⁴ atm, corresponding to ΔG of −60 kJ/mol O₂. This value for VPO is significantly lower than that measured with other vanadium-containing catalysts that have been studied. Furthermore, compared to other vanadium catalysts, V⁺⁴ was stabilized against further reduction at lower P(O₂). These redox thermodynamics may help to explain the unique catalytic properties of VPO catalysts for partial oxidation of butane to maleic anhydride.     

45S5 Bioglass®-derived scaffolds coated with organic–inorganic hybrids containing graphene

Highly porous 45S5 Bioglass®-based scaffolds fabricated by a foam replication technique were coated with electrically conductive organic–inorganic hybrid layers containing graphene by a solution method. α,ω-Triethoxysilane terminated poly (ethylene glycol) and tetraethoxysilane were used as the precursors of the organic–inorganic hybrid coatings, that contained 1.5 wt.% of homogeneously dispersed graphene nanoplatelets. The resulting coated scaffolds retained their original high porosity and interconnected pore structure after coating. The presence of graphene did not impair the bioactivity of the scaffolds in simulated body fluid.Initial tests carried out using MG-63 cells demonstrated that both uncoated scaffolds and scaffolds coated with organic/inorganic hybrids containing graphene offered the cultured cells an adequate surface for cell attachment, spreading and expression of extracellular matrix. The results showed that scaffolds coated with graphene are biocompatible and they can support cellular activity. The electrical conductivity introduced by the coating might have the potential to increase tissue growth when cell culture is carried out under an applied electric field.     

Preparation and characterization of uniform molecularly imprinted polymer beads for separation of triazine herbicides

Uniform molecularly imprinted polymer beads were synthesized by precipitation polymerization for separation of triazine herbicides. A series of imprinted polymers were prepared using ametryn as template and divinylbenzene as crosslinking monomer, in combination with three different functional monomers under different solvent conditions. Under optimized reaction conditions, we obtained uniform molecularly imprinted polymer microspheres that display favorable molecular binding selectivity for triazine herbicides. The imprinted polymer beads synthesized using methacrylic acid as functional monomer in a mixture of methyl ethyl ketone and heptane showed the best results in terms of particle size distribution and molecular selectivity. Compared with nonimprinted polymer microspheres, the imprinted microspheres displayed significantly higher binding for a group of triazine herbicides including atrazine, simazine, propazine, ametryn, prometryn, and terbutryn. For the first time, precipitation polymerization has been used to produce highly uniform imprinted microspheres suitable for affinity separation of triazine herbicides. © 2012 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

Catalytic degradation of waste high-density polyethylene into fuel products using BaCO3 as a catalyst

Waste high-density polyethylene (HDPE) was degraded thermally and catalytically using BaCO₃ as a catalyst under different conditions of temperature, cat/pol ratio and time. The oil collected at optimum conditions (450 °C, 0.1 cat/pol ratio and 2 h reaction time) was fractionated at different temperatures and fuel property of the fractions and parent oil was evaluated by their physicochemical parameters for fuel tests. The results were compared with the standard values for gasoline, kerosene and diesel oil. Boiling point distribution (BPD) curves were plotted from the gas chromatographic study of the samples and compared with that of the standard gasoline, kerosene and diesel. The oil samples were analyzed using GC/MS in order to find out their composition. The physical parameters and the composition of the parent oil and its fractions support the resemblance of the samples with the standard fuel oils. The light fractions best match with gasoline, the middle fractions match with kerosene and the heavier fractions match with diesel oil in almost all of the characteristic properties.