Genetic control of bone density and turnover: Role of the collagen 1α1, estrogen receptor, and vitamin D receptor genes

Genetic factors are known to influence both the peak bone mass and probably the rate of change in bone density. A range of regulatory and structural genes has been proposed to be involved including collagen 1α1 (COL1A1), the estrogen receptor (ER), and the vitamin D receptor (VDR), but the actual genes involved are uncertain. We therefore studied the role of the COL1A1 and VDR loci in control of bone density by linkage in 45 dizygotic twin pairs and 29 nuclear families comprising 120 individuals. The influences on bone density of polymorphisms of COL1A1, VDR, and ER were studied by association both cross-sectionally and longitudinally in 193 elderly postmenopausal women (average age, 69 years) over a mean follow-up time of 6.3 years. Weak linkage of the COL1A1 locus with bone density was observed in both twins and families (p = 0.02 in both data sets), confirming previous observations of linkage of this locus with bone density. Association between the MscI polymorphism of COL1A1 and rate of lumbar spine bone loss was observed with significant gene-environment interaction related to dietary calcium intake (p = 0.0006). In the lowest tertile of dietary calcium intake, carriers of "s" alleles lost more bone than "SS" homozygotes (p = 0.01), whereas the opposite was observed in the highest dietary calcium intake (p = 0.003). Association also was observed between rate of bone loss at both the femoral neck and the lumbar spine and the TaqI VDR polymorphism (p = 0.03). This association was strongest in those in the lowest tertile of calcium intake, also suggesting the presence of gene-environment interaction involving dietary calcium and VDR, influencing bone turnover. No significant association was observed between the PvuII ER polymorphism alone or in combination with VDR or COL1A1 genotypes, with either bone density or its rate of change. These data support the involvement of COL1A1 in determination of bone density and the interaction of both COL1A1 and VDR with calcium intake in regulation of change of bone density over time.

Evaluation of CaO-CeO2-partially stabilized zirconia thermal barrier coatings

Plasma sprayable powders were prepared from ZrO2-CaO-CeO2 system using an organic binder and coated onto stainless steel substrates previously coated by a bond coat (Ni 22Cr 20Al 1.0Y) using plasma spraying. The coatings exhibited good thermal barrier characteristics and excellent resistance to thermal shock at 1000 degrees C under simulated laboratory conditions (90 half hour cycles without failure) and at 1200 degrees C under accelerated burner rig test conditions (500 2 min cycles without failure). No destabilization of cubic/tetragonal ZrO2 phase fraction occured either during the long hours (45 h cumulative) or the large number of thermal shock tests. Growth of a distinct SiO2 rich region within the ceramic was observed in the specimens thermal shock cycled at 1000 degrees C apart from mild oxidation of the bond coat. The specimens tested at 1200 degrees C had a glassy appearance on the top surface and exhibited severe oxidation of the bond coat at the ceramic-bond coat interface. The glassy appearance of the surface is due to the formation of a liquid silicate layer attributable to the impurity phase present in commercial grade ZrO2 powder. These observations are supported by SEM analysis and quantitative EDAX data.

Managing the impacts of sugarcane farming on the Great Barrier Reef: An evaluation of the implementation of the Polluter Pays Principle

This report provides an evaluation of the implementation of the Polluter Pays Principle (PPP) – a principle of international environmental law – in the context of pollution from sugarcane farming affecting Australia’s Great Barrier Reef (GBR). The research was part of an experiment to test methods for evaluating the effectiveness of environmental laws. Overall, we found that whilst the PPP is reflected to a limited extent in Australian law (more so in Queensland law, than at the national level), the behaviour one might expect in terms of implementing the principle was largely inadequate. Evidence of a longer term, explicit commitment to the PPP was particularly weak.

Nature and extent of genetic diversity of dengue viruses determined by 454 pyrosequencing

Dengue virus (DENV) populations are characteristically highly diverse. Regular lineage extinction and replacement is an important dynamic DENV feature, and most DENV lineage turnover events are associated with increased incidence of disease. The role of genetic diversity in DENV lineage extinctions is not understood. We investigated the nature and extent of genetic diversity in the envelope (E) gene of DENV serotype 1 representing different lineages histories. A region of the DENV genome spanning the E gene was amplified and sequenced by Roche/454 pyrosequencing. The pyrosequencing results identified distinct sub-populations (haplotypes) for each DENV-1 E gene. A phylogenetic tree was constructed with the consensus DENV-1 E gene nucleotide sequences, and the sequences of each constructed haplotype showed that the haplotypes segregated with the Sanger consensus sequence of the population from which they were drawn. Haplotypes determined through pyrosequencing identified a recombinant DENV genome that could not be identified through Sanger sequencing. Nucleotide level sequence diversities of DENV-1 populations determined from SNP analysis were very low, estimated from 0.009-0.01. There were also no stop codon, frameshift or non-frameshift mutations observed in the E genes of any lineage. No significant correlations between the accumulation of deleterious mutations or increasing genetic diversity and lineage extinction were observed (p>0.5). Although our hypothesis that accumulation of deleterious mutations over time led to the extinction and replacement of DENV lineages was ultimately not supported by the data, our data does highlight the significant technical issues that must be resolved in the way in which population diversity is measured for DENV and other viruses. The results provide an insight into the within-population genetic structure and diversity of DENV-1 populations.

A linear programming approach for estimating the structure of a sparse linear genetic network from transcript profiling data

Background: A genetic network can be represented as a directed graph in which a node corresponds to a gene and a directed edge specifies the direction of influence of one gene on another. The reconstruction of such networks from transcript profiling data remains an important yet challenging endeavor. A transcript profile specifies the abundances of many genes in a biological sample of interest. Prevailing strategies for learning the structure of a genetic network from high-dimensional transcript profiling data assume sparsity and linearity. Many methods consider relatively small directed graphs, inferring graphs with up to a few hundred nodes. This work examines large undirected graphs representations of genetic networks, graphs with many thousands of nodes where an undirected edge between two nodes does not indicate the direction of influence, and the problem of estimating the structure of such a sparse linear genetic network (SLGN) from transcript profiling data. Results: The structure learning task is cast as a sparse linear regression problem which is then posed as a LASSO (l1-constrained fitting) problem and solved finally by formulating a Linear Program (LP). A bound on the Generalization Error of this approach is given in terms of the Leave-One-Out Error. The accuracy and utility of LP-SLGNs is assessed quantitatively and qualitatively using simulated and real data. The Dialogue for Reverse Engineering Assessments and Methods (DREAM) initiative provides gold standard data sets and evaluation metrics that enable and facilitate the comparison of algorithms for deducing the structure of networks. The structures of LP-SLGNs estimated from the INSILICO1, INSILICO2 and INSILICO3 simulated DREAM2 data sets are comparable to those proposed by the first and/or second ranked teams in the DREAM2 competition. The structures of LP-SLGNs estimated from two published Saccharomyces cerevisae cell cycle transcript profiling data sets capture known regulatory associations. In each S. cerevisiae LP-SLGN, the number of nodes with a particular degree follows an approximate power law suggesting that its degree distributions is similar to that observed in real-world networks. Inspection of these LP-SLGNs suggests biological hypotheses amenable to experimental verification. Conclusion: A statistically robust and computationally efficient LP-based method for estimating the topology of a large sparse undirected graph from high-dimensional data yields representations of genetic networks that are biologically plausible and useful abstractions of the structures of real genetic networks. Analysis of the statistical and topological properties of learned LP-SLGNs may have practical value; for example, genes with high random walk betweenness, a measure of the centrality of a node in a graph, are good candidates for intervention studies and hence integrated computational – experimental investigations designed to infer more realistic and sophisticated probabilistic directed graphical model representations of genetic networks. The LP-based solutions of the sparse linear regression problem described here may provide a method for learning the structure of transcription factor networks from transcript profiling and transcription factor binding motif data.

Optimal barrier subdivision for Kramers' escape rate

We examine the effect of subdividing the potential barrier along the reaction coordinate on Kramers' escape rate for a model potential. Using the known supersymmetric potential approach, we show the existence of an optimal number of subdivisions that maximizes the rate.

Theoretical Optimization of Metal Para-Normal Silicon Schottky-Barrier Solar-Cell

The theoretical optimization of the design parametersN A ,N D andW P has been done for efficient operation of Au-p-n Si solar cell including thermionic field emission, dependence of lifetime and mobility on impurity concentrations, dependence of absorption coefficient on wavelength, variation of barrier height and hence the optimum thickness ofp region with illumination. The optimized design parametersN D =5×1020 m−3,N A =3×1024 m−3 andW P =11.8 nm yield efficiencyη=17.1% (AM0) andη=19.6% (AM1). These are reduced to 14.9% and 17.1% respectively if the metal layer series resistance and transmittance with ZnS antireflection coating are included. A practical value ofW P =97.0 nm gives an efficiency of 12.2% (AM1).

An extended regression approach to estimating loads and their uncertainties in Great Barrier Reef catchments

There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates by minimizing the biases and making use of possible predictive variables. The load estimation procedure can be summarized by the following four steps: - (i) output the flow rates at regular time intervals (e.g. 10 minutes) using a time series model that captures all the peak flows; - (ii) output the predicted flow rates as in (i) at the concentration sampling times, if the corresponding flow rates are not collected; - (iii) establish a predictive model for the concentration data, which incorporates all possible predictor variables and output the predicted concentrations at the regular time intervals as in (i), and; - (iv) obtain the sum of all the products of the predicted flow and the predicted concentration over the regular time intervals to represent an estimate of the load. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized regression (rating-curve) approach with additional predictors that capture unique features in the flow data, namely the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and cumulative discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. The model also has the capacity to accommodate autocorrelation in model errors which are the result of intensive sampling during floods. Incorporating this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach using the concentrations of total suspended sediment (TSS) and nitrogen oxide (NOx) and gauged flow data from the Burdekin River, a catchment delivering to the Great Barrier Reef. The sampling biases for NOx concentrations range from 2 to 10 times indicating severe biases. As we expect, the traditional average and extrapolation methods produce much higher estimates than those when bias in sampling is taken into account.

A large-scale analysis of genetic variants within putative miRNA binding sites in prostate cancer

Prostate cancer is the second most common malignancy among men worldwide. Genome-wide association studies have identified 100 risk variants for prostate cancer, which can explain approximately 33% of the familial risk of the disease. We hypothesized that a comprehensive analysis of genetic variations found within the 3' untranslated region of genes predicted to affect miRNA binding (miRSNP) can identify additional prostate cancer risk variants. We investigated the association between 2,169 miRSNPs and prostate cancer risk in a large-scale analysis of 22,301 cases and 22,320 controls of European ancestry from 23 participating studies. Twenty-two miRSNPs were associated (P<2.3×10(-5)) with risk of prostate cancer, 10 of which were within 7 genes previously not mapped by GWAS studies. Further, using miRNA mimics and reporter gene assays, we showed that miR-3162-5p has specific affinity for the KLK3 rs1058205 miRSNP T-allele, whereas miR-370 has greater affinity for the VAMP8 rs1010 miRSNP A-allele, validating their functional role. SIGNIFICANCE Findings from this large association study suggest that a focus on miRSNPs, including functional evaluation, can identify candidate risk loci below currently accepted statistical levels of genome-wide significance. Studies of miRNAs and their interactions with SNPs could provide further insights into the mechanisms of prostate cancer risk.

A genetic variant of MDM4 influences regulation by multiple microRNAs in prostate cancer

The oncogene MDM4, also known as MDMX or HDMX, contributes to cancer susceptibility and progression through its capacity to negatively regulate a range of genes with tumour-suppressive functions. As part of a recent genome-wide association study it was determined that the A-allele of the rs4245739 SNP (A>C), located in the 3'-UTR of MDM4, is associated with an increased risk of prostate cancer. Computational predictions revealed that the rs4245739 SNP is located within a predicted binding site for three microRNAs (miRNAs): miR-191-5p, miR-887 and miR-3669. Herein, we show using reporter gene assays and endogenous MDM4 expression analyses that miR-191-5p and miR-887 have a specific affinity for the rs4245739 SNP C-allele in prostate cancer. These miRNAs do not affect MDM4 mRNA levels, rather they inhibit its translation in C-allele-containing PC3 cells but not in LNCaP cells homozygous for the A-allele. By analysing gene expression datasets from patient cohorts, we found that MDM4 is associated with metastasis and prostate cancer progression and that targeting this gene with miR-191-5p or miR-887 decreases in PC3 cell viability. This study is the first, to our knowledge, to demonstrate regulation of the MDM4 rs4245739 SNP C-allele by two miRNAs in prostate cancer, and thereby to identify a mechanism by which the MDM4 rs4245739 SNP A-allele may be associated with an increased risk for prostate cancer.

Genetic Options for Drought Management in Groundnut

Groundnut is one of the principal oilseeds in the world. It is cultivated on 24.8 million ha with a total production of 32.8 million t and an average productivity of 1.32 t ha-'. Developing countries account for 96.9% of the world groundnut area and 93.8% of total production. Production is concentrated in Asia (56.8% area and 66.5% production of the world) and Africa (38.0% area and 24.7% production). The groundnut productivity in Africa is only 0.86 t ha-' compared with 1.55 t hx1 of Asia. The world groundnut economy-facts, trends and outlook are desaibed in detail by Freeman et al., 1999. Briefly, in medium-term (i.e. up to 2010), 'groundnut production and consumption is likely to shift increasingly to developing countries; production will grow in all regions but most rapidly in Asia, slowly in sub-Saharan Africa and decline in Latin America; and utilizationwill continue to shift away from groundnut oil toward groundnut meal, specially confectionery products'.

A towed instrument package for fisheries research in great barrier reef waters

A tethered remote instrument package (TRIP) has been developed for biological surveys over Queensland's continental shelf and slope. The present system, evolved from an earlier sled configuration, is suspended above the sea bed and towed at low speeds. Survey information is collected through video and film cameras while instrument and environmental variables are handled by a minicomputer. The operator was able to "fly" the instrument package above the substrate by using an altitude echosounder, forward-looking sonar and real-time television viewing. Unwanted movements of the viewing system were stabilized through a gyro-controlled camera-head panning system. the hydrodynamic drag of the umbilical presented a major control problem which could be overcome only by a reduction in towing speed. Despite the constraints of towing a device such as this through the coral reef environment, the package performed well during a recent biological survey where it was worked at 50% of its 350 m design depth.

A robust approach to design a single facility layout plan in dynamic manufacturing environments using a permutation-based genetic algorithm

During the past few decades, developing efficient methods to solve dynamic facility layout problems has been focused on significantly by practitioners and researchers. More specifically meta-heuristic algorithms, especially genetic algorithm, have been proven to be increasingly helpful to generate sub-optimal solutions for large-scale dynamic facility layout problems. Nevertheless, the uncertainty of the manufacturing factors in addition to the scale of the layout problem calls for a mixed genetic algorithm–robust approach that could provide a single unlimited layout design. The present research aims to devise a customized permutation-based robust genetic algorithm in dynamic manufacturing environments that is expected to be generating a unique robust layout for all the manufacturing periods. The numerical outcomes of the proposed robust genetic algorithm indicate significant cost improvements compared to the conventional genetic algorithm methods and a selective number of other heuristic and meta-heuristic techniques.

A Genetic Analysis of Lysosomal Enzyme Activities in Brahman Cattle

Analyses of variance and co variance were carried out on the activities of three lysosomal enzymes in mononuclear blood cells from Brahman cattle. These were hexosaminidase (HEX), beta-D-galacto-sidase (GAL) and acid alpha-glucosidase (GLU) which had been measured in blood mononuclear cells from 1752 cattle from 6 herds in a Pompe's disease control programme. Herd of origin and date of bleeding significantly affected the level of activity of all enzymes. In addition, HEX and GAL were affected by age and HEX by the sex of the animal bled. Estimates of heritability from sire variances were 0.29:t 0.09 for HEX, 0.31 :t 0.09 for GAL and 0.44:t 0.09 for GLU. Genetic correlations between all enzymes were positive. The data indicate the existence of a major gene causing Pompe's disease and responsible for 16% of the genetic variation in GLU. One standard deviation of selection differential for high GLU should almost eliminate Pompe's disease from the population. The effi-ciency of selection would be aided by estimating the breeding value for GLU using measurements of HEX and GLU and taking account of an animal's sex, age, date of bleeding and herd of origin.

Genetic analysis of resistance to root-lesion nematode (Pratylenchus thornei) in wheat

The inheritance of resistance to root-lesion nematode was investigated in five synthetic hexaploid wheat lines and two bread wheat lines using a half-diallel design of F1 and F2 crosses. The combining ability of resistance genes in the synthetic hexaploid wheat lines was compared with the performance of the bread wheat line 'GS50a', the source of resistance to Pratylenchus thornei used in Australian wheat breeding programmes. Replicated glasshouse trials identified P. thornei resistance as polygenic and additive in gene action. General combining ability (GCA) of the parents was more important than specific combining ability (SCA) effects in the inheritance of P. thornei resistance in both F1 and F2 populations. The synthetic hexaploid wheat line 'CPI133872' was identified as the best general combiner, however, all five synthetic hexaploid wheat lines possessed better GCA than 'GS50a'. The synthetic hexaploid wheat lines contain novel sources of P. thornei resistance that will provide alternative and more effective sources of resistance to be utilized in wheat breeding programmes