Testing predictions of macroscopic binary diffusion coefficients using lattice models with site heterogeneity

Quantitatively predicting mass transport rates for chemical mixtures in porous materials is important in applications of materials such as adsorbents, membranes, and catalysts. Because directly assessing mixture transport experimentally is challenging, theoretical models that can predict mixture diffusion coefficients using Only single-component information would have many uses. One such model was proposed by Skoulidas, Sholl, and Krishna (Langmuir, 2003, 19, 7977), and applications of this model to a variety of chemical mixtures in nanoporous materials have yielded promising results. In this paper, the accuracy of this model for predicting mixture diffusion coefficients in materials that exhibit a heterogeneous distribution of local binding energies is examined. To examine this issue, single-component and binary mixture diffusion coefficients are computed using kinetic Monte Carlo for a two-dimensional lattice model over a wide range of lattice occupancies and compositions. The approach suggested by Skoulidas, Sholl, and Krishna is found to be accurate in situations where the spatial distribution of binding site energies is relatively homogeneous, but is considerably less accurate for strongly heterogeneous energy distributions.

Mixture models for detecting differentially expressed genes in microarrays

An important and common problem in microarray experiments is the detection of genes that are differentially expressed in a given number of classes. As this problem concerns the selection of significant genes from a large pool of candidate genes, it needs to be carried out within the framework of multiple hypothesis testing. In this paper, we focus on the use of mixture models to handle the multiplicity issue. With this approach, a measure of the local FDR (false discovery rate) is provided for each gene. An attractive feature of the mixture model approach is that it provides a framework for the estimation of the prior probability that a gene is not differentially expressed, and this probability can subsequently be used in forming a decision rule. The rule can also be formed to take the false negative rate into account. We apply this approach to a well-known publicly available data set on breast cancer, and discuss our findings with reference to other approaches.

On the simultaneous use of clinical and microarray expression data in the cluster analysis of tissue samples

This paper considers a model-based approach to the clustering of tissue samples of a very large number of genes from microarray experiments. It is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. Frequently in practice, there are also clinical data available on those cases on which the tissue samples have been obtained. Here we investigate how to use the clinical data in conjunction with the microarray gene expression data to cluster the tissue samples. We propose two mixture model-based approaches in which the number of components in the mixture model corresponds to the number of clusters to be imposed on the tissue samples. One approach specifies the components of the mixture model to be the conditional distributions of the microarray data given the clinical data with the mixing proportions also conditioned on the latter data. Another takes the components of the mixture model to represent the joint distributions of the clinical and microarray data. The approaches are demonstrated on some breast cancer data, as studied recently in van't Veer et al. (2002).

Multilevel modelling for inference of genetic regulatory networks

Time-course experiments with microarrays are often used to study dynamic biological systems and genetic regulatory networks (GRNs) that model how genes influence each other in cell-level development of organisms. The inference for GRNs provides important insights into the fundamental biological processes such as growth and is useful in disease diagnosis and genomic drug design. Due to the experimental design, multilevel data hierarchies are often present in time-course gene expression data. Most existing methods, however, ignore the dependency of the expression measurements over time and the correlation among gene expression profiles. Such independence assumptions violate regulatory interactions and can result in overlooking certain important subject effects and lead to spurious inference for regulatory networks or mechanisms. In this paper, a multilevel mixed-effects model is adopted to incorporate data hierarchies in the analysis of time-course data, where temporal and subject effects are both assumed to be random. The method starts with the clustering of genes by fitting the mixture model within the multilevel random-effects model framework using the expectation-maximization (EM) algorithm. The network of regulatory interactions is then determined by searching for regulatory control elements (activators and inhibitors) shared by the clusters of co-expressed genes, based on a time-lagged correlation coefficients measurement. The method is applied to two real time-course datasets from the budding yeast (Saccharomyces cerevisiae) genome. It is shown that the proposed method provides clusters of cell-cycle regulated genes that are supported by existing gene function annotations, and hence enables inference on regulatory interactions for the genetic network.

Hepatic structure-pharmacokinetic relationships: The hepatic disposition and metabolite kinetics of a homologous series of O-acyl derivatives of salicylic acid

1 The hepatic disposition and metabolite kinetics of a homologous series of O-acyl (acetyl, propionyl, butanoyl, pentanoyl, hexanoyl and octanoyl) esters of salicylic acid (C2SA, C3SA, C4SA, C5SA, C6SA and C8SA, respectively) was determined using a single-pass, in-sills rat liver preparation. 2 The hepatic venous outflow profiles for the parent esters and the generated metabolite, salicylic acid (SA) were analysed by HPLC. Non-parametric moments analysis was used to determine the area under the curve (AUC'), mean transit time (MTT) and normalized variance (CV2) for the parent esters and generated SA. 3 Pregenerated SA ([C-14]-salicylic acid) was injected into each liver with the parent ester to determine its distribution characteristics. 4 The overall recovery of ester plus metabolite was 89% of the ester dose injected and independent of the ester carbon number, suggesting that ester extraction was due to hepatic metabolism to salicylic acid. 5 The metabolite AUC' value increased directly with the lipophilicity of the parent ester (from 0.12 for C2SA to 0.95 for C8SA). By contrast, the parent AUC' decreased with the lipophilicity (from 0.85 for C2SA to zero for C8SA). The metabolite MTT value also showed a trend to increase with the lipophilicity of the parent ester (from 15.72 s for C3SA to 61.97 s for C8SA). However, the parent MTT value shows no significant change across the series. 6 The two-compartment dispersion model was used to derive the kinetic parameters for parent ester, pregenerated SA and generated SA. Consequently, these parameters were used to estimate the values of AUG', MITT and CV2 for the parent ester and metabolite. The moments values obtained using the two-compartment dispersion model show similar trends to the corresponding moments values obtained from the outflow profiles using a non-parametric approach. 7 The more lipophilic aspirin analogues are more confined to the portal circulation after oral administration than aspirin due to their more extensive hepatic elimination avoiding systemic prostacyclin inhibition. Given that aspirin's selectivity as an anti-thrombotic agent has been postulated to be due to selective anti-platelet effects in the portal circulation, the more lipophilic and highly extracted analogues are potentially more selective anti-thrombotic agents than aspirin.

Hepatic disposition and metabolite kinetics of a homologous series of diflunisal esters

The hepatic disposition and metabolite kinetics of a homologous series of diflunisal O-acyl esters (acetyl, butanoyl, pentanoyl, anti hexanoyl) were determined using a single-pass perfused in situ rat liver preparation. The experiments were conducted using 2% BSA Krebs-Henseleit buffer (pH 7.4), and perfusions were performed at 30 mL/min in each liver. O-Acyl esters of diflunisal and pregenerated diflunisal were injected separately into the portal vein. The venous outflow samples containing the esters and metabolite diflunisal were analyzed by high performance liquid chromatography (HPLC). The normalized outflow concentration-time profiles for each parent ester and the formed metabolite, diflunisal, were analyzed using statistical moments analysis and the two-compartment dispersion model. Data (presented as mean +/- standard error for triplicate experiments) was compared using ANOVA repeated measures, significance level P < 0.05. The hepatic availability (AUC'), the fraction of the injected dose recovered in the outflowing perfusate, for O-acetyldiflunisal (C2D = 0.21 +/- 0.03) was significantly lower than the other esters (0.34-0.38). However, R-N/f(u), the removal efficiency number R-N divided by the unbound fraction in perfusate f(u), which represents the removal efficiency of unbound ester by the liver, was significantly higher for the most lipophilic ester (O-hexanoyldiflunisal, C6D = 16.50 +/- 0.22) compared to the other members of the series (9.57 to 11.17). The most lipophilic ester, C6D, had the largest permeability surface area (PS) product (94.52 +/- 38.20 mt min-l g-l liver) and tissue distribution value VT (35.62 +/- 11.33 mL g(-1) liver) in this series. The MTT of these O-acyl esters of diflunisal were not significantly different from one another. However, the metabolite diflunisal MTTs tended to increase with the increase in the parent ester lipophilicity (11.41 +/- 2.19 s for C2D to 38.63 +/- 9.81 s for C6D). The two-compartment dispersion model equations adequately described the outflow profiles for the parent esters and the metabolite diflunisal formed from the O-acyl esters of diflunisal in the liver.

Numerical and experimental study of seepage in unconfined aquifers with a periodic boundary condition

The assessment of groundwater conditions within an unconfined aquifer with a periodic boundary condition is of interest in many hydrological and environmental problems. A two-dimensional numerical model for density dependent variably saturated groundwater flow, SUTRA (Voss, C.I., 1984. SUTRA: a finite element simulation model for saturated-unsaturated, fluid-density dependent ground-water flow with energy transport or chemically reactive single species solute transport. US Geological Survey, National Center, Reston, VA) is modified in order to be able to simulate the groundwater flow in unconfined aquifers affected by a periodic boundary condition. The basic flow equation is changed from pressure-form to mixed-form. The model is also adjusted to handle a seepage-face boundary condition. Experiments are conducted to provide data for the groundwater response to the periodic boundary condition for aquifers with both vertical and sloping faces. The performance of the numerical model is assessed using those data. The results of pressure- and mixed-form approximations are compared and the improvement achieved through the mixed-form of the equation is demonstrated. The ability of the numerical model to simulate the water table and seepage-face is tested by modelling some published experimental data. Finally the numerical model is successfully verified against present experimental results to confirm its ability to simulate complex boundary conditions like the periodic head and the seepage-face boundary condition on the sloping face. (C) 1999 Elsevier Science B.V. All rights reserved.

Modelling the distribution of stamp paper thickness via finite normal mixtures: The 1872 Hidalgo stamp issue of Mexico revisited

Izenman and Sommer (1988) used a non-parametric Kernel density estimation technique to fit a seven-component model to the paper thickness of the 1872 Hidalgo stamp issue of Mexico. They observed an apparent conflict when fitting a normal mixture model with three components with unequal variances. This conflict is examined further by investigating the most appropriate number of components when fitting a normal mixture of components with equal variances.

Impulse-response studies on tracer doses of [C-14]lignocaine and its multiple metabolites in the perfused rat liver

The outflow-concentration-time profiles for lignocaine (lidocaine) and its metabolites have been measured after bolus impulse administration of [C-14]lignocaine into the perfused rat liver. Livers from female Sprague-Dawley rats were perfused in a once-through fashion with red-blood-cell-free Krebs-Henseleit buffer containing 0 or 2% bovine serum albumin. Perfusate flow rates of 20 and 30 mL min(-1) were used and both normal and retrograde flow directions were employed. Significant amounts of metabolite were detected in the effluent perfusate soon after lignocaine injection. The early appearance of metabolite contributed to bimodal outflow profiles observed for total C-14 radioactivity. The lignocaine outflow profiles were well characterized by the two-compartment dispersion model, with efflux rate << influx rate. The profiles for lignocaine metabolites were also characterized in terms of a simplified two-compartment dispersion model. Lignocaine was found to be extensively metabolized under the experimental conditions with the hepatic availability ranging between 0.09 and 0.18. Generally lignocaine and metabolite availability showed no significant change with alterations in perfusate flow rate from 20 to 30 mt min(-1) or protein content from 0 to 2%. A significant increase in lignocaine availability occurred when 1200 mu M unlabelled lignocaine was added to the perfusate. Solute mean transit times generally decreased with increasing flow rate and with increasing perfusate protein content. The results confirm that lignocaine pharmacokinetics in the liver closely follow the predictions of the well-stirred model. The increase in lignocaine availability when 1200 mu M unlabelled lignocaine was added to the perfusate is consistent with saturation of the hydroxylation metabolic pathways of lignocaine metabolism.

Structure-hepatic disposition relationships for cationic drugs in isolated perfused rat livers: Transmembrane exchange and cytoplasmic binding process

This work studied the structure-hepatic disposition relationships for cationic drugs of varying lipophilicity using a single-pass, in situ rat liver preparation. The lipophilicity among the cationic drugs studied in this work is in the following order: diltiazem. propranolol. labetalol. prazosin. antipyrine. atenolol. Parameters characterizing the hepatic distribution and elimination kinetics of the drugs were estimated using the multiple indicator dilution method. The kinetic model used to describe drug transport (the two-phase stochastic model) integrated cytoplasmic binding kinetics and belongs to the class of barrier-limited and space-distributed liver models. Hepatic extraction ratio (E) (0.30-0.92) increased with lipophilicity. The intracellular binding rate constant (k(on)) and the equilibrium amount ratios characterizing the slowly and rapidly equilibrating binding sites (K-S and K-R) increase with the lipophilicity of drug (k(on) : 0.05-0.35 s(-1); K-S : 0.61-16.67; K-R : 0.36-0.95), whereas the intracellular unbinding rate constant (k(off)) decreases with the lipophilicity of drug (0.081-0.021 s(-1)). The partition ratio of influx (k(in)) and efflux rate constant (k(out)), k(in)/k(out), increases with increasing pK(a) value of the drug [from 1.72 for antipyrine (pK(a) = 1.45) to 9.76 for propranolol (pK(a) = 9.45)], the differences in k(in/kout) for the different drugs mainly arising from ion trapping in the mitochondria and lysosomes. The value of intrinsic elimination clearance (CLint), permeation clearance (CLpT), and permeability-surface area product (PS) all increase with the lipophilicity of drug [CLint (ml . min(-1) . g(-1) of liver): 10.08-67.41; CLpT (ml . min(-1) . g(-1) of liver): 10.80-5.35; PS (ml . min(-1) . g(-1) of liver): 14.59-90.54]. It is concluded that cationic drug kinetics in the liver can be modeled using models that integrate the presence of cytoplasmic binding, a hepatocyte barrier, and a vascular transit density function.

Pharmacokinetics and pharmacodynamics of melphalan in isolated limb infusion for recurrent localized limb malignancy

Isolated limb infusion (ILI) is an attractive, less complex alternative to Isolated limb perfusion (ILP). It has a lower morbidity in treating localized recurrences and in transit metastases of the limb for tumours such as melanoma, Merkel cell tumour and Kaposi's sarcoma, allowing administration of high concentrations of cytotoxic agent to the affected limb under hypoxic conditions. Melphalan is the preferred cytotoxic agent for the treatment of melanoma by ILP or ILI. We report pharmacokinetic data from 12 patients treated by ILI for tumours of the limb in Brisbane. The kinetics of drug distribution in the limb was calculated using a two-compartment vascular model, where both tissue and infusate act as well-stirred compartments. Analysis of melphalan concentrations in the perfusate during ILI showed good agreement between the values measured and the concentrations predicted by the model. Recirculation and wash-out flow rates, tissue concentrations and the permeability surface area product (PS) were calculated. Correlations between the PS value and the drug concentrations In the perfusate and tissue were supported by the results. These data contribute to a better understanding of the distribution of melphalan during ILI in the limb, and offer the opportunity to optimize the drug regimen for patients undergoing ILI. (C) 2001 Lippincott Williams & Wilkins.

Ring flexibility within tricyclic antidepressant drugs

The internal flexibility of the central seven-membered ring of a series of tricyclic antidepressant drugs (TCAs), imipramine {l}, amitriptyline {2}, doxepin {3}, and dothiepin {4}, has been investigated by H-1 and C-13 nuclear magnetic (NMR) techniques. Two dynamic processes were examined: ring inversion and bridge flexing. H-1 NMR lineshape analysis was used to obtain ring inversion barriers for 2-4. These studies yielded energy barriers of 14.3, 16.7, and 15.7 +/- 0.6 kcal/mol for the hydrochloride salts of doxepin, dothiepin, and amitriptyline, respectively. The barriers for the corresponding free bases were lower by 0.6 kcal/mol on average. (CT1)-C-13 relaxation measurements were used to determine the degree of bridge flexing associated with the central seven-membered ring for all four compounds. By fitting the T-1 data to a two-state jump model, lifetimes and amplitudes of rapid bridge flexing motions were determined. The results show that imipramine has the fastest rate of bridge flexing, followed by amitriptyline, doxepin, and dothiepin. The pharmacological profiles of the TCAs are complex and they interact with many receptor sites, resulting in numerous side effects and a general lack of understanding of their precise mode of action in different anxiety-related disorders. They all have similar three-dimensional structures, which makes it difficult to rationalize their differing relative potency in different assays/clinical settings. However, the clear finding here that there are significantly different degrees of internal mobility suggests that molecular dynamics should be an additional factor considered when trying to understand the mode of action of this clinically important family of molecules. (C) 2001 Wiley-Liss, Inc. and the American Pharmaceutical Association J Pharm Sci 90:713-721, 2001.

Power of the joint segregation analysis method for testing mixed major-gene and polygene inheritance models of quantitative traits

Understanding the genetic architecture of quantitative traits can greatly assist the design of strategies for their manipulation in plant-breeding programs. For a number of traits, genetic variation can be the result of segregation of a few major genes and many polygenes (minor genes). The joint segregation analysis (JSA) is a maximum-likelihood approach for fitting segregation models through the simultaneous use of phenotypic information from multiple generations. Our objective in this paper was to use computer simulation to quantify the power of the JSA method for testing the mixed-inheritance model for quantitative traits when it was applied to the six basic generations: both parents (P-1 and P-2), F-1, F-2, and both backcross generations (B-1 and B-2) derived from crossing the F-1 to each parent. A total of 1968 genetic model-experiment scenarios were considered in the simulation study to quantify the power of the method. Factors that interacted to influence the power of the JSA method to correctly detect genetic models were: (1) whether there were one or two major genes in combination with polygenes, (2) the heritability of the major genes and polygenes, (3) the level of dispersion of the major genes and polygenes between the two parents, and (4) the number of individuals examined in each generation (population size). The greatest levels of power were observed for the genetic models defined with simple inheritance; e.g., the power was greater than 90% for the one major gene model, regardless of the population size and major-gene heritability. Lower levels of power were observed for the genetic models with complex inheritance (major genes and polygenes), low heritability, small population sizes and a large dispersion of favourable genes among the two parents; e.g., the power was less than 5% for the two major-gene model with a heritability value of 0.3 and population sizes of 100 individuals. The JSA methodology was then applied to a previously studied sorghum data-set to investigate the genetic control of the putative drought resistance-trait osmotic adjustment in three crosses. The previous study concluded that there were two major genes segregating for osmotic adjustment in the three crosses. Application of the JSA method resulted in a change in the proposed genetic model. The presence of the two major genes was confirmed with the addition of an unspecified number of polygenes.

Spray drift of pesticides arising from aerial application in cotton

This paper presents results from field studies carried out during the 1993-1998 Australian cotton (Gossypium hirsutum L.) seasons to monitor off-target droplet movement of endosulfan (6,7,8,9,10,10-hexachloro-1,5,5a,6,9,9a-hexahydro-6,9-methano-2,4,3-benzodioxathiepin 3-oxide) insecticide applied to a commercial cotton crop. Averaged over a wide range of conditions, off-target deposition 500 m downwind of the field boundary was approximately 2% of the field-applied rate with oil-based applications and 1% with water-based applications. Mean airborne drift values recorded 100 m downwind of a single flight line were a third as much with water-based application compared with oil-based application. Calculations using a Gaussian diffusion model and the U.S. Spray Drift Task Force AgDRIFT model produced downwind drift profiles that compared favorably with experimental data. Both models and data indicate that by adopting large droplet placement (LDP) application methods and incorporating crop buffer distances, spray drift can be effectively managed.

Evaluation of various pre-treatments for the dehydration of banana and selection of suitable drying models

The thin-layer drying behaviour of bananas in a beat pump dehumidifier dryer was examined. Four pre-treatments (blanching, chilling, freezing and combined blanching and freezing) were applied to the bananas, which were dried at 50 degreesC with an air velocity of 3.1 m s(-1) and with the relative humidity of the inlet air of 10-35%. Three drying models, the simple model, the two-term exponential model and the Page model were examined. All models were evaluated using three statistical measures, correlation coefficient, root means square error, and mean absolute percent error. Moisture diffusivity was calculated based on the diffusion equation for an infinite cylindrical shape using the slope method. The rate of drying was higher for the pre-treatments involving freezing. The sample which was blanched only did not show any improvement in drying rate. In fact, a longer drying time resulted due to water absorption during blanching. There was no change in the rate for the chilled sample compared with the control. While all models closely fitted the drying data, the simple model showed greatest deviation from the experimental results. The two-term exponential model was found to be the best model for describing the drying curves of bananas because its parameters represent better the physical characteristics of the drying process. Moisture diffusivities of bananas were in the range 4.3-13.2 x 10(-10) m(2)s(-1). (C) 2002 Published by Elsevier Science Ltd.