A Combination of Compositional Index and Genetic Algorithm for Predicting Transmembrane Helical Segments

Transmembrane helix (TMH) topology prediction is becoming a focal problem in bioinformatics because the structure of TM proteins is difficult to determine using experimental methods. Therefore, methods that can computationally predict the topology of helical membrane proteins are highly desirable. In this paper we introduce TMHindex, a method for detecting TMH segments using only the amino acid sequence information. Each amino acid in a protein sequence is represented by a Compositional Index, which is deduced from a combination of the difference in amino acid occurrences in TMH and non-TMH segments in training protein sequences and the amino acid composition information. Furthermore, a genetic algorithm was employed to find the optimal threshold value for the separation of TMH segments from non-TMH segments. The method successfully predicted 376 out of the 378 TMH segments in a dataset consisting of 70 test protein sequences. The sensitivity and specificity for classifying each amino acid in every protein sequence in the dataset was 0.901 and 0.865, respectively. To assess the generality of TMHindex, we also tested the approach on another standard 73-protein 3D helix dataset. TMHindex correctly predicted 91.8% of proteins based on TM segments. The level of the accuracy achieved using TMHindex in comparison to other recent approaches for predicting the topology of TM proteins is a strong argument in favor of our proposed method. Availability: The datasets, software together with supplementary materials are available at: http://faculty.uaeu.ac.ae/nzaki/TMHindex.htm

The evolution and distribution of recycled oceanic crust in the Earth's mantle: Insight from geodynamic models

A better understanding of the Earth's compositional structure is needed to place the geochemical record of surface rocks into the context of Earth accretion and evolution. Cosmochemical constraints imply that lower-mantle rocks may be enriched in silica relative to upper-mantle pyrolite, whereas geophysical observations support whole-mantle convection and mixing. To resolve this discrepancy, it has been suggested that subducted mid-ocean ridge basalt (MORB) segregates from subducted harzburgite to accumulate in the mantle transition zone (MTZ) and/or the lower mantle. However, the key parameters that control basalt segregation and accumulation remain poorly constrained. Here, we use global-scale 2D thermochemical convection models to investigate the influence of mantle-viscosity profile, planetary-tectonic style and bulk composition on the evolution and distribution of mantle heterogeneity. Our models robustly predict that, for all cases with Earth-like tectonics, a basalt-enriched reservoir is formed in the MTZ, and a harzburgite-enriched reservoir is sustained at 660∼800 km depth, despite ongoing whole-mantle circulation. The enhancement of basalt and harzburgite in and beneath the MTZ, respectively, are laterally variable, ranging from ∼30% to 50% basalt fraction, and from ∼40% to 80% harzburgite enrichment relative to pyrolite. Models also predict an accumulation of basalt near the core mantle boundary (CMB) as thermochemical piles, as well as moderate enhancement of most of the lower mantle by basalt. While the accumulation of basalt in the MTZ does not strongly depend on the mantle-viscosity profile (explained by a balance between basalt delivery by plumes and removal by slabs at the given MTZ capacity), that of the lowermost mantle does: lower-mantle viscosity directly controls the efficiency of basalt segregation (and entrainment) near the CMB; upper-mantle viscosity has an indirect effect through controlling slab thickness. Finally, the composition of the bulk-silicate Earth may be shifted relative to that of upper-mantle pyrolite, if indeed significant reservoirs of basalt exist in the MTZ and lower mantle

Combinatorial molecular optimization of cement hydrates

Despite its ubiquitous presence in the built environment, concrete’s molecular-level properties are only recently being explored using experimental and simulation studies. Increasing societal concerns about concrete’s environmental footprint have provided strong motivation to develop new concrete with greater specific stiffness or strength (for structures with less material). Herein, a combinatorial approach is described to optimize properties of cement hydrates. The method entails screening a computationally generated database of atomic structures of calcium-silicate-hydrate, the binding phase of concrete, against a set of three defect attributes: calcium-to-silicon ratio as compositional index and two correlation distances describing medium-range silicon-oxygen and calcium-oxygen environments. Although structural and mechanical properties correlate well with calcium-to-silicon ratio, the cross-correlation between all three defect attributes reveals an indentation modulus-to-hardness ratio extremum, analogous to identifying optimum network connectivity in glass rheology. We also comment on implications of the present findings for a novel route to optimize the nanoscale mechanical properties of cement hydrate.National Ready Mixed Concrete Association (Research sponsorship)Education Foundation (N.J.) (Research sponsorship)Portland Cement Association (Research sponsorship

Immigration and crime: do Asian immigrants bring more crimes to Australia?

The link between the increased Asian immigration to Australia and crime rates has been subjected to debates in Australian contemporary society. With the concern of Australia being overwhelmed by Asians, some politicians, scholars and the public strongly oppose the increase in Asian immigrants. Most of anti-Asian debates are however based on rather subjective claims that Asian immigrants bring more crimes and social disorders to Australia, and these claims have not been supported by any convincing empirical research. Applying multivariate regression analysis, this paper statistically examines the relationship between Asian population, Asian immigrants and crime rates in six states and two territories of Australia from 1981 to 2004. After controlling for the relevant factors such as the population size, state-specific fixed effects, and a measure of urbanisation, the results are mixed. On the one hand, an increase in Asian immigrants has no effect on crime against persons and crime against properties. On the other hand, an increase in the size of Asian population has a statistically significant effect on crime against persons

Protein Domain Linker Prediction: A Direction for Detecting Protein – Protein Interactions

Protein chains are generally long and consist of multiple domains. Domains are the basic of elements of protein structures that can exist, evolve and function independently. The accurate and reliable identification of protein domains and their interactions has very important impacts in several protein research areas. The accurate prediction of protein domains is a fundamental stage in both experimental and computational proteomics. The knowledge is an initial stage of protein tertiary structure prediction which can give insight into the way in which protein works. The knowledge of domains is also useful in classifying the proteins, understanding their structures, functions and evolution, and predicting protein-protein interactions (PPI). However, predicting structural domains within proteins is a challenging task in computational biology. A promising direction of domain prediction is detecting inter-domain linkers and then predicting the reigns of the protein sequence in which the structural domains are located accordingly. Protein-protein interactions occur at almost every level of cell function. The identification of interaction among proteins and their associated domains provide a global picture of cellular functions and biological processes. It is also an essential step in the construction of PPI networks for human and other organisms. PPI prediction has been considered as a promising alternative to the traditional drug design techniques. The identification of possible viral-host protein interaction can lead to a better understanding of infection mechanisms and, in turn, to the development of several medication drugs and treatment optimization. In this work, a compact and accurate approach for inter-domain linker prediction is developed based solely on protein primary structure information. Then, inter-domain linker knowledge is used in predicting structural domains and detecting PPI. The research work in this dissertation can be summarized in three main contributions. The first contribution is predicting protein inter-domain linker regions by introducing the concept of amino acid compositional index and refining the prediction by using the Simulated Annealing optimization technique. The second contribution is identifying structural domains based on inter-domain linker knowledge. The inter-domain linker knowledge, represented by the compositional index, is enhanced by the in cooperation of biological knowledge, represented by amino acid physiochemical properties. To develop a well optimized Random Forest classifier for predicting novel domain and inter-domain linkers. In the third contribution, the domain information knowledge is utilized to predict protein-protein interactions. This is achieved by characterizing structural domains within protein sequences, analyzing their interactions, and predicting protein interaction based on their interacting domains. The experimental studies and the higher accuracy achieved is a valid argument in favor of the proposed framework

The CM-proteins from cereal endosperm: Immunochemical relationships

The CM-proteins, which are salt-soluble proteins that can be extracted with chloroform: methanol (2: 1, v/v), seem to be present in the endosperm of all the cereal species investigated. Antibodies raised against a mixture of the barley CM-proteins (A-H) cross-reacted with wheat and rye proteins in Ouchterlony tests and a detailed study was carried out for purified wheat (CM1, CM2. CM3. CM3') and barley (CMa, CMb, CMc, CMd) CM-proteins. [35Sl-Cysteine-labelled endosperm proteins from wheat and barley were investigated by immuno-precipitation, electrophoresis and fluorography using the antibodies (A-H) and also those to a mixture of wheat CM-proteins and to CMd. There was complete antigenic identity for all the wheat proteins and CMd, some of the other proteins showed partial antigenic identity. Previously proposed genetic and biochemical relationships among these proteins were confirmed in the present study

Accumulation of saturated intramyocellular lipid is associated with insulin resistance.

Intramyocellular lipid (IMCL) accumulation has been linked to both insulin-resistant and insulin-sensitive (athletes) states. Biochemical analysis of intramuscular triglyceride composition is confounded by extramyocellular triglycerides in biopsy samples, and hence the specific composition of IMCLs is unknown in these states. 1H magnetic resonance spectroscopy (MRS) can be used to overcome this problem. Thus, we used a recently validated 1H MRS method to compare the compositional saturation index (CH2:CH3) and concentration independent of the composition (CH3) of IMCLs in the soleus and tibialis anterior muscles of 16 female insulin-resistant lipodystrophic subjects with that of age- and gender-matched athletes (n = 14) and healthy controls (n = 41). The IMCL CH2:CH3 ratio was significantly higher in both muscles of the lipodystrophic subjects compared with controls but was similar in athletes and controls. IMCL CH2:CH3 was dependent on the IMCL concentration in the controls and, after adjusting the compositional index for quantity (CH2:CH3adj), could distinguish lipodystrophics from athletes. This CH2:CH3adj marker had a stronger relationship with insulin resistance than IMCL concentration alone and was inversely related to VO2max The association of insulin resistance with the accumulation of saturated IMCLs is consistent with a potential pathogenic role for saturated fat and the reported benefits of exercise and diet in insulin-resistant states

Oxygen vacancies and hydrogen in amorphous In-Ga-Zn-O and ZnO

Hydrogen is known to be present as an impurity in amorphous oxide semiconductors at the 0.1% level. The behavior of hydrogen and oxygen vacancies in amorphous In-Ga-Zn-O is studied using density functional supercell calculations. We show that the hydrogens pair up at oxygen vacancies in the amorphous network, where they form metal-H-metal bridge bonds. These bonds are shown to create filled defect gap states lying just above the valence band edge, infrared modes at about 1400 and 1520cm−1, and they are shown to give a consistent mechanism to explain the negative bias illumination stress instability found in oxide semiconductors such as In-Ga-Zn-O (IGZO).The authors acknowledge funding from EPSRC Grants No. EP/P005152/1