The microsomal epoxide hydrolase Tyr113His polymorphism: Association with risk of ovarian cancer

Functional significance has been demonstrated in vitro for the exon 3 T-->C Tyr113His amino acid substitution polymorphism of the microsomal epoxide hydrolase (EPHX) gene. The higher activity or fast TT genotype was previously reported to be associated with an increased risk of ovarian cancer, and this association may reflect enhanced activation of endogenous or exogenous substrates to more reactive and mutagenic derivatives. Components of cigarette smoke are examples of exogenous substrates subject to such bioactivation, and smoking exposure may thus modify the risk associated with the EPHX polymorphism. We examined 545 cases of epithelial ovarian cancer and 287 unaffected controls for this EPHXT-C genetic variant to investigate whether, in the Australian population, the TT genotype was associated with (i) specific ovarian tumor characteristics; (ii) risk of ovarian cancer, overall or for specific subgroups; and (iii) risk of ovarian cancer in smokers specifically. Genotyping was carried out using the Perkin-Elmer ABI Prism 7700 Sequence Detection System for fluorogenic polymerase chain reaction allelic discrimination. Stratification of the ovarian cancer cases according to tumor behavior (low malignant potential or invasive), grade, stage, and p53 immunohistochemical status failed to show any heterogeneity with respect to the genotype defined by the EPHX polymorphism. There was a suggestion of heterogeneity with respect to histologic subtype (P= 0.03), largely due to a decreased frequency of the TT genotype in endometrioid tumors. EPHX genotype distribution did not differ significantly between unaffected controls and ovarian cancer cases (overall, low malignant potential, or invasive) either overall or after stratification by smoking status. However, the TT genotype was associated with a decreased risk of invasive ovarian cancer of the endometrioid subtype specifically (age-adjusted odds ratio = 0.38, 95% confidence interval=0.17-0.87). The results suggest that the proposed EPHX-mediated bioactivation of components of cigarette smoke to mutagenic forms is unlikely to be involved in the etiology of ovarian cancer in general but that a greater rate of EPHX-mediated detoxification may decrease the risk of endometrioid ovarian cancer. (C) 2001 Wiley-Liss, Inc.

No significant association between progesterone receptor exon 4 Val660Leu G/T polymorphism and risk of ovarian cancer

Epidemiological studies suggest that ovarian cancer is an endocrine-related tumour, and progesterone exposure specifically may decrease the risk of ovarian cancer. To assess whether the progesterone receptor (PR) exon 4 valine to leucine amino acid variant is associated with specific tumour characteristics or with overall risk of ovarian cancer, we examined 551 cases of epithelial ovarian cancer and 298 unaffected controls for the underlying G-->T nucleotide substitution polymorphism. Stratification of the ovarian cancer cases according to tumour behaviour (low malignant potential or invasive), histology, grade or stage failed to reveal any heterogeneity with respect to the genotype defined by the PR exon 4 polymorphism. Furthermore, the genotype distribution did not differ significantly between ovarian cancer cases and unaffected controls. Compared with the GG genotype, the age-adjusted odds ratio (95% confidence interval) for risk of ovarian cancer was 0.78 (0.57-1.08) for the GT genotype, and 1.39 (0.47-4.14) for the TT genotype. In conclusion, the PR exon 4 codon 660 leucine variant encoded by the T allele does not appear to be associated with ovarian tumour behaviour, histology, stage or grade. This variant is also not associated with an increased risk of ovarian cancer, and is unlikely to be associated with a large decrease in ovarian cancer risk, although we cannot rule out a moderate inverse association between the GT genotype and ovarian cancer.

A single nucleotide polymorphism in the 5' untranslated region of RAD51 and risk of cancer among BRCA1/2 mutation carriers

RAD51 colocalizes with both BRCA1 and BRCA2, and genetic variants in RAD51 would be candidate BRCA1/2 modifiers. We searched for RAD51 polymorphisms by sequencing 20 individuals. We compared the polymorphism allele frequencies between female BRCA1/2 mutation carriers with and without breast or ovarian cancer and between population-based ovarian cancer cases with BRCA1/2 mutations to cases and controls without mutations. We discovered two single nucleotide polymorphisms (SNPs) at positions 135 g-->c and 172 g-->t of the 5' untranslated region. In an initial group of BRCA1/2 mutation carriers, 14 (21%) of 67 breast cancer cases carried a c allele at RAD51:135 g-->c, whereas 8 (7%) of 119 women without breast cancer carried this allele. In a second set of 466 mutation carriers from three centers, the association of RAD51:135 g-->c with breast cancer risk was not confirmed. Analyses restricted to the 216 BRCA2 mutation carriers, however, showed a statistically significant association of the 135 c allele with the risk of breast cancer (adjusted odds ratio, 3.2; 95% confidence limit, 1.4-40). BRCA1/2 mutation carriers with ovarian cancer were only about one half as likely to carry the RAD51:135 g-->c SNP. Analysis of the RAD51:135 g-->c SNP in 738 subjects from an Israeli ovarian cancer case-control study was consistent with a lower risk of ovarian cancer among BRCA1/2 mutation carriers with the c allele. We have identified a RAD51 5' untranslated region SNP that may be associated with an increased risk of breast cancer and a lower risk of ovarian cancer among BRCA2 mutation carriers. The biochemical basis of this risk modifier is currently unknown.

Fitting mixtures of Kent distributions to aid in joint set identification

When examining a rock mass, joint sets and their orientations can play a significant role with regard to how the rock mass will behave. To identify joint sets present in the rock mass, the orientation of individual fracture planer can be measured on exposed rock faces and the resulting data can be examined for heterogeneity. In this article, the expectation-maximization algorithm is used to lit mixtures of Kent component distributions to the fracture data to aid in the identification of joint sets. An additional uniform component is also included in the model to accommodate the noise present in the data.

A modified pore-filling isotherm for liquid-phase adsorption in activated carbon

This article modifies the usual form of the Dubinin-Radushkevich pore-filling model for application to liquid-phase adsorption data, where large molecules are often involved. In such cases it is necessary to include the repulsive part of the energy in the micropores, which is accomplished here by relating the pore potential to the fluid-solid interaction potential. The model also considers the nonideality of the bulk liquid phase through the UNIFAC activity coefficient model, as well as structural heterogeneity of the carbon. For the latter the generalized adsorption integral is used while incorporating the pore-size distribution obtained by density functional theory analysis of argon adsorption data. The model is applied here to the interpretation of aqueous phase adsorption isotherms of three different esters on three commercial activated carbons. Excellent agreement between the model and experimental data is observed, and the fitted Lennard-Jones size parameter for the adsorbate-adsorbate interactions compares well with that estimated from known critical properties, supporting the modified approach. On the other hand, the model without consideration of bulk nonideality, or when using classical models of the characteristic energy, gives much poorer bts of the data and unrealistic parameter values.

Characterization of activated carbons using liquid phase adsorption

A modification of the Dubinin-Radushkevich pore filling model by incorporation of the repulsive contribution to the pore potential, and of bulk non-ideality, is proposed in this paper for characterization of activated carbon using liquid phase adsorption. For this purpose experiments have been performed using ethyl propionate, ethyl butyrate, and ethyl isovalerate as adsorbates and the microporous-mesoporous activated carbons Filtrasorb 400, Norit ROW 0.8 and Norit ROX 0.8 as adsorbents. The repulsive contribution to the pore potential is incorporated through a Lennard-Jones intermolecular potential model, and the bulk-liquid phase non-ideality through the UNIFAC activity coefficient model. For the characterization of activated carbons, the generalized adsorption isotherm is utilized with a bimodal gamma function as the pore size distribution function. It is found that the model can represent the experimental data very well, and significantly better than when the classical energy-size relationship is used, or when bulk non-ideality is neglected. Excellent agreement between the bimodal gamma pore size distribution and DFT-cum-regularization based pore size distribution is also observed, supporting the validity of the proposed model. (C) 2001 Elsevier Science Ltd. All rights reserved.

Client resistance in outreaching social work in Hong Kong

This paper reports the survey findings of a study on the outreaching social workers' perceptions of client resistance. In light of their social work practice 10th youth-at-risk in Hong Kong, resistance is generally recognised as a natural phenomenon in the counselling process and to a certain extent, is an obstacle to engaging in purposeful worker-client relationship as well as effecting behavioural changes. On Pipes and Davenport's (1990) classification, the respondents were more likely to classify client resistance as innocuous behaviours like missing appointments and refusing to discuss problems than disarming and proactive behaviours. The implications of these findings are discussed.

Organophilicity of MCM-41 adsorbents studied by adsorption and temperature-programmed desorption

In this paper, the organophilic property of MCM-41 was studied and compared with hydrophobic silicalite-l using adsorption and temperature-programmed desorption (TPD) methods. The surface heterogeneity of MCM-41 was evaluated in terms of activation energy for desorption (E-d) and isosteric heat of adsorption (q(st)). Results show that MCM-41 has a higher affinity to polar organic compounds than to non-polar organics while silicalite-l has a higher affinity to non-polar organic compounds than to polar organics. This organophilic behaviour of MCM-41 is attributed to its surface heterogeneity. (C) 2001 Elsevier Science B.V. All rights reserved.

Discrimination of adsorption kinetic models for the description of hydrocarbon adsorption in activated carbon

Five kinetic models for adsorption of hydrocarbons on activated carbon are compared and investigated in this study. These models assume different mass transfer mechanisms within the porous carbon particle. They are: (a) dual pore and surface diffusion (MSD), (b) macropore, surface, and micropore diffusion (MSMD), (c) macropore, surface and finite mass exchange (FK), (d) finite mass exchange (LK), and (e) macropore, micropore diffusion (BM) models. These models are discriminated using the single component kinetic data of ethane and propane as well as the multicomponent kinetics data of their binary mixtures measured on two commercial activated carbon samples (Ajax and Norit) under various conditions. The adsorption energetic heterogeneity is considered for all models to account for the system. It is found that, in general, the models assuming diffusion flux of adsorbed phase along the particle scale give better description of the kinetic data.

On the surface diffusion of hydrocarbons in microporous activated carbon

This paper addresses the current status of the various diffusion theories for surface diffusion in the literature. The inadequacy of these models to explain the surface diffusion of many hydrocarbons in microporous activated carbon is shown in this paper. They all can explain the increase of the surface diffusivity (D-mu) with loading, but cannot explain the increase of the surface permeability (D(mu)partial derivativeC(mu)/partial derivativeP) with loading as observed in our data of diffusion of hydrocarbons in activated carbon, even when the surface heterogeneity is accounted for in those models. The explanation for their failure was presented, and we have put forward a theory to explain the increase of surface diffusion permeability with loading. This new theory assumes the variation of the activation energy for surface diffusion with surface loading, and it is validated with diffusion data of propane, n-butane, n-hexane, benzene and ethanol in activated carbon. (C) 2001 Elsevier Science Ltd. All rights reserved.

Surface diffusion of hydrocarbons in activated carbon: Comparison between constant molar flow, differential permeation and differential adsorption bed methods

This paper presents the comparison of surface diffusivities of hydrocarbons in activated carbon. The surface diffusivities are obtained from the analysis of kinetic data collected using three different kinetics methods- the constant molar flow, the differential adsorption bed and the differential permeation methods. In general the values of surface diffusivity obtained by these methods agree with each other, and it is found that the surface diffusivity increases very fast with loading. Such a fast increase can not be accounted for by a thermodynamic Darken factor, and the surface heterogeneity only partially accounts for the fast rise of surface diffusivity versus loading. Surface diffusivities of methane, ethane, propane, n-butane, n-hexane, benzene and ethanol on activated carbon are reported in this paper.

Some vocabulary and grammar for the analysis of multi-environment trials, as applied to the analysis of FPB and PPB trials

For the improvement of genetic material suitable for on farm use under low-input conditions, participatory and formal plant breeding strategies are frequently presented as competing options. A common frame of reference to phrase mechanisms and purposes related to breeding strategies will facilitate clearer descriptions of similarities and differences between participatory plant breeding and formal plant breeding. In this paper an attempt is made to develop such a common framework by means of a statistically inspired language that acknowledges the importance of both on farm trials and research centre trials as sources of information for on farm genetic improvement. Key concepts are the genetic correlation between environments, and the heterogeneity of phenotypic and genetic variance over environments. Classic selection response theory is taken as the starting point for the comparison of selection trials (on farm and research centre) with respect to the expected genetic improvement in a target environment (low-input farms). The variance-covariance parameters that form the input for selection response comparisons traditionally come from a mixed model fit to multi-environment trial data. In this paper we propose a recently developed class of mixed models, namely multiplicative mixed models, also called factor-analytic models, for modelling genetic variances and covariances (correlations). Mixed multiplicative models allow genetic variances and covariances to be dependent on quantitative descriptors of the environment, and confer a high flexibility in the choice of variance-covariance structure, without requiring the estimation of a prohibitively high number of parameters. As a result detailed considerations regarding selection response comparisons are facilitated. ne statistical machinery involved is illustrated on an example data set consisting of barley trials from the International Center for Agricultural Research in the Dry Areas (ICARDA). Analysis of the example data showed that participatory plant breeding and formal plant breeding are better interpreted as providing complementary rather than competing information.

Habitat complexity, spatial interference, and "minimum risk distribution": a framework for population stability

In the past century, the debate over whether or not density-dependent factors regulate populations has generally focused on changes in mean population density, ignoring the spatial variance around the mean as unimportant noise. In an attempt to provide a different framework for understanding population dynamics based on individual fitness, this paper discusses the crucial role of spatial variability itself on the stability of insect populations. The advantages of this method are the following: (1) it is founded on evolutionary principles rather than post hoc assumptions; (2) it erects hypotheses that can be tested; and (3) it links disparate ecological schools, including spatial dynamics, behavioral ecology, preference-performance, and plant apparency into an overall framework. At the core of this framework, habitat complexity governs insect spatial variance. which in turn determines population stability. First, the minimum risk distribution (MRD) is defined as the spatial distribution of individuals that results in the minimum number of premature deaths in a population given the distribution of mortality risk in the habitat (and, therefore, leading to maximized population growth). The greater the divergence of actual spatial patterns of individuals from the MRD, the greater the reduction of population growth and size from high, unstable levels. Then, based on extensive data from 29 populations of the processionary caterpillar, Ochrogaster lunifer, four steps are used to test the effect of habitat interference on population growth rates. (1) The costs (increasing the risk of scramble competition) and benefits (decreasing the risk of inverse density-dependent predation) of egg and larval aggregation are quantified. (2) These costs and benefits, along with the distribution of resources, are used to construct the MRD for each habitat. (3) The MRD is used as a benchmark against which the actual spatial pattern of individuals is compared. The degree of divergence of the actual spatial pattern from the MRD is quantified for each of the 29 habitats. (4) Finally, indices of habitat complexity are used to provide highly accurate predictions of spatial divergence from the MRD, showing that habitat interference reduces population growth rates from high, unstable levels. The reason for the divergence appears to be that high levels of background vegetation (vegetation other than host plants) interfere with female host-searching behavior. This leads to a spatial distribution of egg batches with high mortality risk, and therefore lower population growth. Knowledge of the MRD in other species should be a highly effective means of predicting trends in population dynamics. Species with high divergence between their actual spatial distribution and their MRD may display relatively stable dynamics at low population levels. In contrast, species with low divergence should experience high levels of intragenerational population growth leading to frequent habitat-wide outbreaks and unstable dynamics in the long term. Six hypotheses, erected under the framework of spatial interference, are discussed, and future tests are suggested.