Diffusion modeling of percutaneous absorption kinetics: 3. Variable diffusion and partition coefficients, consequences for stratum corneum depth profiles and desorption kinetics

Stratum corneum (SC) desorption experiments have yielded higher calculated steady-state fluxes than those obtained by epidermal penetration studies. A possible explanation of this result is a variable diffusion or partition coefficient across the SC. We therefore developed the diffusion model for percutaneous penetration and desorption to study the effects of either a variable diffusion coefficient or variable partition coefficient in the SC over the diffusion path length. Steady-state flux, lag time, and mean desorption time were obtained from Laplace domain solutions. Numerical inversion of the Laplace domain solutions was used for simulations of solute concentration-distance and amount penetrated (desorbed)-time profiles. Diffusion and partition coefficients heterogeneity were examined using six different models. The effect of heterogeneity on predicted flux from desorption studies was compared with that obtained in permeation studies. Partition coefficient heterogeneity had a more profound effect on predicted fluxes than diffusion coefficient heterogeneity. Concentration-distance profiles show even larger dependence on heterogeneity, which is consistent with experimental tape-stripping data reported for clobetasol propionate and other solutes. The clobetasol propionate tape-stripping data were most consistent with the partition coefficient decreasing exponentially for half the SC and then becoming a constant for the remaining SC. (C) 2004 Wiley-Liss, Inc.

Reducing the height of a circular array of monopoles using top hats and dielectric coatings

Using a Radial Guide Field Matching Method, an investigation is performed into reducing the height of an electronically steered circular array of monopole antennas composed of a central active element surrounded by passive elements being either short- or open-circuited. It is shown that a considerable height reduction can be achieved using top hats attached to monopoles ends and by applying dielectric coating underneath the top hats. The trade-off in achieving height reduction is narrower impedance bandwidth.

Comparative habitat use in Juniper woodland bird community

We compared vegetation structure used by 14 bird species during the 1998 and 1999 breeding seasons to determine what habitat features best accounted for habitat division and community organization in Utah juniper (Juniperus osteosperma) woodlands of southwestern Wyoming. Habitat use was quantified by measuring 24 habitat variables in 461 bird-centered quadrats, each 0.04 ha in size. Using discriminant function analysis, we differentiated between habitat used by 14 bird species along 3 habitat dimensions: (1) variation in shrub cover, overstory juniper cover, mature tree density, understory height, and decadent tree density; (2) a gradient composed of elevation and forb cover; and (3) variation in grass cover, tree height, seedling/sapling cover, and bare ground/rock cover. Of 14 species considered, 9 exhibited substantial habitat partitioning: Mourning Dove (Zenaida macroura), Bewick's Wren (Thryomanes bewickii), Blue-gray Gnatcatcher (Polioptila caerulea), Mountain Bluebird (Sialia currucoides), Plumbeous Vireo (Vireo plumbeus), Green-tailed Towhee (Pipilo chlorurus), Brewer's Sparrow (Spizella breweri), Dark-eyed Junco (Junco hyemalis), and Cassin's Finch (Carpodacus cassinii). Our results indicate juniper bird communities of southwestern Wyoming are organized along a 3-dimensional habitat gradient composed of woodland maturity, elevation, and juniper recruitment. Because juniper birds partition habitat along successional and altitudinal gradients, indiscriminate woodland clearing as well as continued fire suppression will alter species composition. Restoration efforts should ensure that all successional stages of juniper woodland are present on the landscape.

Clustering of related individuals in a population of the Australian lizard, Egernia frerei

Stable social aggregations are rarely recorded in lizards, but have now been reported from several species in the Australian scincid genus Egernia. Most of those examples come from species using rock crevice refuges that are relatively easy to observe. But for many other Egernia species that occupy different habitats and are more secretive, it is hard to gather the observational data needed to deduce their social structure. Therefore, we used genotypes at six polymorphic microsatellite DNA loci of 229 individuals of Egernia frerei, trapped in 22 sampling sites over 3500 ha of eucalypt forest on Fraser Island, Australia. Each sampling site contained 15 trap locations in a 100 x 50 m grid. We estimated relatedness among pairs of individuals and found that relatedness was higher within than between sites. Relatedness of females within sites was higher than relatedness of males, and was higher than relatedness between males and females. Within sites we found that juvenile lizards were highly related to other juveniles and to adults trapped at the same location, or at adjacent locations, but relatedness decreased with increasing trap separation. We interpreted the results as suggesting high natal philopatry among juvenile lizards and adult females. This result is consistent with stable family group structure previously reported in rock dwelling Egernia species, and suggests that social behaviour in this genus is not habitat driven.

Ultrasound organometry: the importance of body height adjusted normal ranges in assessing liver and spleen parameters among Chinese subjects with Schistosoma japonicum infection

Hepatosplenic measurements among 550 Chinese subjects, aged 3-59 years from Yueyang city-a nonendemic area for schistosomiasis in Hunan province, China-were performed to define normal ranges of ultrasound organometry for assessing hepatosplenic, morbidity in Schistosoma japonicum infection. Measurements included the size of the liver (left lobe and right lobe), the main portal vein stem, the peripheral periportal vein branches, and spleen length and thickness. The results document the significant relationship between body height and organometric parameters. The reference values stratified by body height improve the accuracy of assessment. Thus, height-based normal ranges established in this study can be applied in hospital routine and in field studies of patients infected with S. japonicum in Hunan province and in other endemic areas of China. (C) 2004 Elsevier B.V. All rights reserved.

Height, age at menarche, and risk of epithelial ovarian cancer

Objective: We hypothesized that the hormonal changes of adolescence influence ovarian cancer risk particularly in younger women. We investigated this possibility by examining the relationship between ovarian cancer and adult height and age at menarche as both factors reflect pubertal hormonal levels. Methods: Participants were a population-based sample of women with incident ovarian cancer (n = 794) and control women randomly selected from the Australian Electoral Roll (n = 855). The women provided comprehensive reproductive and lifestyle data during a standard interview. Results: Although neither height nor age at menarche was significantly related to the risk of ovarian cancer overall, increasing height was associated with increasing risk of the subgroup of mucinous borderline ovarian cancer (odds ratio, 5.3; 95% confidence interval, 1.5-19.1 for women 175 cm compared with women < 160 cm, P-trend = 0.02). Similarly, later age at menarche was associated with increasing risk of mucinous borderline cancers (odds ratio, 3.8; 95% confidence interval, 1.3-11.4 for those with age at menarche >= 44 years compared with those < 12 years, P-trend = 0.003). Women with mucinous borderline cancers were significantly younger than the women diagnosed with invasive cancers (mean 44 versus 57 years; P < 0.0001). Conclusions: Development of mucinous borderline ovarian cancers, predominantly diagnosed in women ages under 50 years, seems to be associated with age at menarche and attained adult height. These results are consistent with our original hypothesis that pubertal levels of reproductive hormones and insulin-like growth factor-I influence ovarian cancer risk in younger women.

Socioeconomic position, cognitive function, and clustering of cardiovascular risk factors in adolescence: Findings from the Mater University Study of Pregnancy and its outcomes

Objectives: The objectives of this study were to examine the extent of clustering of smoking, high levels of television watching, overweight, and high blood pressure among adolescents and whether this clustering varies by socioeconomic position and Cognitive function. Methods: This study was a cross-sectional analysis of 3613 (1742 females) participants of an Australian birth cohort who were examined at age 14. Results: Three hundred fifty-three (9.8%) of the participants had co-occurrence of three or four risk factors. Risk factors clustered in these adolescents with a greater number of participants than would be predicted by assumptions of independence having no risk factors and three or four risk factors. The extent of clustering tended to be greater in those from lower-income families and among those with lower cognitive function. The age-adjusted ratio of observed to expected cooccurrence of three or four risk factors was 2.70 (95% confidence interval [Cl], 1.80-4.06) among those from low-income families and 1.70 (95% Cl, 1.34-2.16) among those from more affluent families. The ratio among those with low Raven's scores (nonverbal reasoning) was 2.36 (95% Cl, 1.69-3.30) and among those with higher scores was 1.51 (95% Cl, 1.19-1.92); similar results for the WRAT 3 score (reading ability) were 2.69 (95% Cl, 1.85-3.94) and 1.68 (95% Cl, 1.34-2.11). Clustering did not differ by sex. Conclusion: Among adolescents, coronary heart disease risk factors cluster, and there is some evidence that this clustering is greater among those from families with low income and those who have lower cognitive function.

Prediction of height from knee height in children with cerebral palsy and non-disabled children

Measurement of height or length is essential in the assessment of nutritional status. In some conditions, for example cerebral palsy (CP), such measurements may be difficult or impossible. Proxy measurements such as knee height have been used to predict height in such cases. We have evaluated two equations in the literature that predict stature from knee height in a group of 17 children with CP and 20 non-disabled children. The two equations performed well on average in the non-disabled children, with the mean predicted height being within 1% of the mean measured height. Nevertheless, the limits of agreement were relatively large. This was also the case for the children with CP. Thus the equations may be accurate at the group level; however they may lead to unacceptable error at the individual level. © 2006 Informa UK Ltd.

A Mixture model with random-effects components for clustering correlated gene-expression profiles

Motivation: The clustering of gene profiles across some experimental conditions of interest contributes significantly to the elucidation of unknown gene function, the validation of gene discoveries and the interpretation of biological processes. However, this clustering problem is not straightforward as the profiles of the genes are not all independently distributed and the expression levels may have been obtained from an experimental design involving replicated arrays. Ignoring the dependence between the gene profiles and the structure of the replicated data can result in important sources of variability in the experiments being overlooked in the analysis, with the consequent possibility of misleading inferences being made. We propose a random-effects model that provides a unified approach to the clustering of genes with correlated expression levels measured in a wide variety of experimental situations. Our model is an extension of the normal mixture model to account for the correlations between the gene profiles and to enable covariate information to be incorporated into the clustering process. Hence the model is applicable to longitudinal studies with or without replication, for example, time-course experiments by using time as a covariate, and to cross-sectional experiments by using categorical covariates to represent the different experimental classes. Results: We show that our random-effects model can be fitted by maximum likelihood via the EM algorithm for which the E(expectation) and M(maximization) steps can be implemented in closed form. Hence our model can be fitted deterministically without the need for time-consuming Monte Carlo approximations. The effectiveness of our model-based procedure for the clustering of correlated gene profiles is demonstrated on three real datasets, representing typical microarray experimental designs, covering time-course, repeated-measurement and cross-sectional data. In these examples, relevant clusters of the genes are obtained, which are supported by existing gene-function annotation. A synthetic dataset is considered too.

ICICLE: A semantic-based retrieval system for WWW images

In this paper, we present ICICLE (Image ChainNet and Incremental Clustering Engine), a prototype system that we have developed to efficiently and effectively retrieve WWW images based on image semantics. ICICLE has two distinguishing features. First, it employs a novel image representation model called Weight ChainNet to capture the semantics of the image content. A new formula, called list space model, for computing semantic similarities is also introduced. Second, to speed up retrieval, ICICLE employs an incremental clustering mechanism, ICC (Incremental Clustering on ChainNet), to cluster images with similar semantics into the same partition. Each cluster has a summary representative and all clusters' representatives are further summarized into a balanced and full binary tree structure. We conducted an extensive performance study to evaluate ICICLE. Compared with some recently proposed methods, our results show that ICICLE provides better recall and precision. Our clustering technique ICC facilitates speedy retrieval of images without sacrificing recall and precision significantly.

Global adaptation of spring bread and durum wheat lines near-isogenic for major reduced height genes

The effect of major dwarfing genes, Rht-B1 and Rht-D1, in bread (Triticum aestivum L.) and durum (Triticum turgidum L. var. durum) wheats varies with environment. Six reduced-height near-isogenic spring wheat lines, included in the International Adaptation Trial (IAT), were grown in 81 trials around the world. Of the 56 IAT trials yielding > 3 Mg ha(-1), the mean yield of semidwarfs was significantly greater than tails in 54% of trials; in the 27 trials yielding < 3 Mg ha-1, semidwarfs were superior in only 24%. Sixteen pairs of semidwarf-tall near-isolines were grown in six managed drought environment trials (DETs) in northwestern Mexico. In these trials, semidwarfs outyielded talls in all but the most droughted environment (2.5 Mg ha(-1)). The effect of the height alleles varied with genetic background and environment. For both yield and height, variance components for allele and environment by allele interaction were larger than those for genetic background and genetic background by environment. Pattern analysis showed that tall and semidwarf lines had similar adaptation to stressed environments (< 2.8 Mg ha(-1), low rainfall), while semidwarfs yielded more in less stressed environments (> 4.3 Mg ha(-1), high rainfall). The best adapted near-isogenic pair had a Kauz background, where the tall was only 16% taller than the dwarf. In the Kauz-derived pair, the semidwarf outyielded the tall in only 13% of trials with no differences in low yielding trials. This supports the idea that '' short talls '' may be useful in marginal environments (yield < 3 Mg ha(-1)).

Indexing and integrating multiple features for WWW images

In this paper, we present a novel indexing technique called Multi-scale Similarity Indexing (MSI) to index image's multi-features into a single one-dimensional structure. Both for text and visual feature spaces, the similarity between a point and a local partition's center in individual space is used as the indexing key, where similarity values in different features are distinguished by different scale. Then a single indexing tree can be built on these keys. Based on the property that relevant images have similar similarity values from the center of the same local partition in any feature space, certain number of irrelevant images can be fast pruned based on the triangle inequity on indexing keys. To remove the dimensionality curse existing in high dimensional structure, we propose a new technique called Local Bit Stream (LBS). LBS transforms image's text and visual feature representations into simple, uniform and effective bit stream (BS) representations based on local partition's center. Such BS representations are small in size and fast for comparison since only bit operation are involved. By comparing common bits existing in two BSs, most of irrelevant images can be immediately filtered. To effectively integrate multi-features, we also investigated the following evidence combination techniques-Certainty Factor, Dempster Shafer Theory, Compound Probability, and Linear Combination. Our extensive experiment showed that single one-dimensional index on multi-features improves multi-indices on multi-features greatly. Our LBS method outperforms sequential scan on high dimensional space by an order of magnitude. And Certainty Factor and Dempster Shafer Theory perform best in combining multiple similarities from corresponding multiple features.

On the statistical analysis of the GS-NS0 cell proteome: Imputation, clustering and variability testing

We have undertaken two-dimensional gel electrophoresis proteomic profiling on a series of cell lines with different recombinant antibody production rates. Due to the nature of gel-based experiments not all protein spots are detected across all samples in an experiment, and hence datasets are invariably incomplete. New approaches are therefore required for the analysis of such graduated datasets. We approached this problem in two ways. Firstly, we applied a missing value imputation technique to calculate missing data points. Secondly, we combined a singular value decomposition based hierarchical clustering with the expression variability test to identify protein spots whose expression correlates with increased antibody production. The results have shown that while imputation of missing data was a useful method to improve the statistical analysis of such data sets, this was of limited use in differentiating between the samples investigated, and highlighted a small number of candidate proteins for further investigation. (c) 2006 Elsevier B.V. All rights reserved.