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Construct validity of the abuse-dependence distinction as measured by DSM-IV criteria for different psychoactive substances.

This article used the diagnostic criteria of the Diagnostic and Statistical Manual-Fourth Edition (DSM-IV) to compare the validity of a qualitative and a quantitative model of the abuse-dependence distinction for different psychoactive substances in samples of drug users drawn from drug treatment inpatients, general psychiatric patients, and the community. The hypothesis that DSM-IV abuse criteria differ from dependence criteria in kind rather than degree (a qualitative model) was only occasionally supported by confirmatory factor analyses of DSM-IV diagnostic criteria, by patterns of correlations of the two kinds of criteria with Addiction Severity Score (ASI) composites and measures of frequency of substance abuse, and by concurrent/prognostic validity analyses. However, the findings were consistent with a quantitative model of the abuse-dependence distinction that posits that abuse is a mild form of dependence. Whether abuse and dependence categories of users were established from separate DSM-IV criteria for abuse and dependence or from scores from a severity-of-dependence scale based on the pooled DSM-IV dependence and abuse criteria, abusers generally used drugs less than users in the dependence category and reported less problems associated with substance abuse on the ASI.

Adolescent↗

End versus side branching by Arp2/3 complex.

We investigate the issue of end versus side branching of actin filaments by Arp2/3 complex, using a combination of analytic theory, polymerization assays, and quantitative modeling. The analytic theory shows that the effect of capping protein on the initial stages of actin polymerization in the presence of Arp2/3 complex depends strongly on whether new Arp2/3 complex-induced branches grow from the sides or ends of existing filaments. Motivated by these results, we measure and quantitatively model the kinetics of actin polymerization in the presence of activated Arp2/3 complex, for a range of concentrations of capping protein. Our model includes the most important types of events involving actin and actin-binding proteins, and can be adjusted to include end branching, side branching, or both. The side-branching model gives a better fit to the experimental data than the end-branching model. An end-plus-side model including both types of branching gives a moderate improvement in the quality of the fit. Another side-branching model, based on aging of subunits' capacity for branch formation, gives a significantly better fit than the end-plus-side model. We discuss implications for actin polymerization in cells.

Actin Cytoskeleton↗

Kinetic modeling of Na(+)-induced, Gbetagamma-dependent activation of G protein-gated K(+) channels.

G protein-activated K(+)(GIRK) channels are activated by numerous neurotransmitters that act on Gi/o proteins, via a direct interaction with the Gbetagamma subunit of G proteins. In addition, GIRK channels are positively regulated by intracellular Na(+) via a direct interaction (fast pathway) and via a GGbetagamma-dependent mechanism (slow pathway). The slow modulation has been proposed to arise from the recently described phenomenon of Na(+)-induced reduction of affinity of interaction between GalphaGDP and Gbetagamma subunits of G proteins. In this scenario, elevated Na(+) enhances basal dissociation of G protein heterotrimers, elevating free cellular Gbetagamma and activating GIRK. However, it is not clear whether this hypothesis can account for the quantitative and kinetic aspects of the observed regulation. Here, we report the development of a quantitative model of slow, Na(+)-dependent, G protein-mediated activation of GIRK. Activity of GIRK1F137S channels, which are devoid of direct interaction with Na(+), was measured in excised membrane patches and used as an indicator of free GGbetagamma levels. The change in channel activity was used to calculate the Na(+)-dependent change in the affinity of G protein subunit interaction. Under a wide range of initial conditions, the model predicted that a relatively small decrease in the affinity of interaction of GalphaGDP and GGbetagamma (about twofold under most conditions) accounts for the twofold activation of GIRK induced by Na(+), in agreement with biochemical data published previously. The model also correctly described the slow time course of Na(+) effect and explained the previously observed enhancement of Na(+)-induced activation of GIRK by coexpressed Galphai3. This is the first quantitative model that describes the basal equilibrium between free and bound G protein subunits and its consequences on regulation of a GGbetagamma effector.

Animals↗

Predicting P-glycoprotein substrates by a quantitative structure-activity relationship model.

A quantitative structure-activity relationship (QSAR) model has been developed to predict whether a given compound is a P-glycoprotein (Pgp) substrate or not. The training set consisted of 95 compounds classified as substrates or non-substrates based on the results from in vitro monolayer efflux assays. The two-group linear discriminant model uses 27 statistically significant, information-rich structure quantifiers to compute the probability of a given structure to be a Pgp substrate. Analysis of the descriptors revealed that the ability to partition into membranes, molecular bulk, and the counts and electrotopological values of certain isolated and bonded hydrides are important structural attributes of substrates. The model fits the data with sensitivity of 100% and specificity of 90.6% in the jackknifed cross-validation test. A prediction accuracy of 86.2% was obtained on a test set of 58 compounds. Examination of the eight "mispredicted" compounds revealed two distinct categories. Five mispredictions were explained by experimental limitations of the efflux assay; these compounds had high permeability and/or were inhibitors of calcein-AM transport. Three mispredictions were due to limitations of the chemical space covered by the current model. The Pgp QSAR model provides an in silico screen to aid in compound selection and in vitro efflux assay prioritization.

ATP Binding Cassette Transporter, Subfamily B, Mem↗

On the origin of modular variation.

We study the dynamics of modularization in a minimal substrate. A module is a functional unit relatively separable from its surrounding structure. Although it is known that modularity is useful both for robustness and for evolvability (Wagner 1996), there is no quantitative model describing how such modularity might originally emerge. Here we suggest, using simple computer simulations, that modularity arises spontaneously in evolutionary systems in response to variation, and that the amount of modular separation is logarithmically proportional to the rate of variation. Consequently, we predict that modular architectures would appear in correlation with high environmental change rates. Because this quantitative model does not require any special substrate to occur, it may also shed light on the origin of modular variation in nature. This observed relationship also indicates that modular design is a generic phenomenon that might be applicable to other fields, such as engineering: Engineering design methods based on evolutionary simulation would benefit from evolving to variable, rather than stationary, fitness criteria, as a weak and problem-independent method for inducing modularity.

Adaptation, Physiological↗

Multifactorial genetic models for quantitative traits in humans.

Quantitative traits measured in human families can be analyzed to partition the total population variance into genetic and environmental components, or to elucidate the genetic mechanism involved. We review the estimation of variance components directly from human pedigree data, or in the form of path coefficients from correlations between pairs of relatives. To elucidate genetic mechanisms, a mixed model that allows for segregation at a major locus, a polygenic effect and a sibling environmental correlation is described for nuclear families. In each case appropriate likelihoods are derived as a basis, using numerical maximum likelihood methods, for parameter estimation and hypothesis testing. A general model is then described that allows for several familial sources of environmental variation, assortative mating, and both major gene and polygenic effects; and an algorithm for calculating the likelihood of a pedigree under this model is indicated. Finally, some of the remaining problems in this area of biometric analysis are pointed out.

Genetic Variation↗

The hairless mouse as a model for quantitating skin deposition of 3,4,4'-trichlorocarbanilide in bar soap.

A method is described for quantitating the deposition of the germicide 3,4,4'-trichlorocarbanilide (TCC) via direct application of bar soap to the skin. The soap contained 1.5% [14C]TCC. Quantitating the skin deposition of biologically active materials is important in the safety evaluation of these ingredients as well as the finished products. In the case of rinse-off products such as soaps, the residue remaining after rinsing constitutes the major portion of material available for penetration. The hairless mouse and the clipped albino Sprague-Dawley rat were evaluated as models for human skin deposition. Little TCC remained on the skin of either species following the wash and rinse procedure. The amount deposited on rat skin was 1.5% of the applied dose or 0.87 micrograms TCC/cm2 while the amount deposited on hairless mouse skin was 1.1% or 0.18 micrograms TCC/cm2. The greater deposition of TCC onto rat skin was likely to be due to the presence of a greater amount of hair. Results obtained using the hairless mouse were consistent and reproducible. The hairless mouse does not require shaving and is easy to handle. Since, like man, it has little hair, it appears to be an excellent model for use in predicting the deposition of TCC on human skin.

Animals↗

Molecular classification of green tea catechin-sensitive and green tea catechin-resistant prostate cancer in the TRAMP mice model by quantitative real-time PCR gene profiling.

We previously found that human prostate cancer (CaP) progression is accompanied by differential expression of a panel of 8 informative genes, some of which are metabolically related. Gene profiling focused on this 8-gene pack by northern blot analysis in combination with standard clinical information provided reliable prognostic prediction of human CaP. For a better insight into the potential of this 8-gene signature in tumor detection/classification and therapeutic response, we determined, by qPCR, the expression of these informative genes in the TRAMP mice model of CaP progression. The 8-genes signature resulted effective in discriminating, by linear discriminant analysis (LDA), the prostate of wild type mice from transgenic TRAMP mice developing CaP (P < 0.0002). Since it is known that Green Tea Catechin (GTC) administration to TRAMP mice results in a substantial delay of CaP progression in 80% of the animals, while 20% remain unresponsive, we determined the 8-gene signature in the prostates of GTC-sensitive and GTC-resistant mice. LDA discriminated benign tissue from CaP (i.e. wild-type + chemoprevented, GTC-sensitive TRAMP mice, in which CaP progression was delayed, was discriminated from TRAMP mice + GTC-resistant TRAMP mice, in which CaP developed irrespective of GTC administration; P < 0.01). Moreover, GTC-sensitive TRAMP mice bearing CaP were discriminated from GTCs-resistant ones, (P = 0.0001). These results show that qPCR gene profiling, based on the signature of the 8-genes selected by us, could represent an appropriate means for studying the biological behavior of CaP, which may lead to identifying new tools of potential prognostic value, in that a molecular classification for the presence/absence of cancer and for discriminating GTCs-responsive from GTC-resistant CaP is provided.

Animals↗

Model-based quantitative AAA image analysis using a priori knowledge.

Abdominal aortic aneurysm (AAA) is a serious vascular disease which may have a fatal outcome. AAA shape and size is important for diagnostics and intervention planning. In this paper, we present a new method for segmentation of AAA from computed tomography (CT) angiography images. The method works by segmenting the inner and the outer aortic border. Segmentation of AAA is a challenging problem because of low contrast of the outer aortic border. In our method, the inner aortic border is segmented using a geometric deformable model (GDM) and morphological postprocessing. The GDM is implemented using the level-set algorithm. The outer aortic border is segmented by a preprocessing method utilizing a priori knowledge about the aorta shape, followed by the GDM-based method, and morphological postprocessing. The preprocessing algorithm operates on a slice-by-slice basis with some information flow among neighboring slices. The GDM performs three-dimensional (3D) segmentation, reducing possible errors in the previous step. The proposed method is automatic and requires minimal user assistance. The method was statistically validated on 12 patient scans having a total number of 497 image slices. Statistical analysis has confirmed high correlation between the results obtained by the proposed method and the gold standard obtained by manual segmentation by an expert radiologist.

Algorithms↗

A kinetic model of quantitative real-time polymerase chain reaction.

Real-time polymerase chain reaction (PCR) is one of the most sensitive and accurate methods for quantifying transcript levels especially for those expressed at low abundance. The selective amplification of target DNA over multiple cycles allows its initial concentration to be determined. The amplification rate is a complex interplay of the operating conditions, initial reactant concentrations, and reaction rate constants. Experimentally, the compounded effect of all factors is quantified in terms of an effective efficiency, which is estimated by curve fitting to the amplification data. We present a comprehensive model of PCR to study the effect of various reactant concentrations on the amplification efficiency. The model is used to calculate the kinetic progression of the target DNA concentration with cycle number under conditions when different species are stoichiometrically or kinetically limiting. The reaction efficiency remains constant for the initial cycles. As the primer concentration becomes limiting, the efficiency is marked by a gradual decrease. This is in contrast to a steep decline under nucleotide limiting conditions. Under some conditions, commonly used experimentally, increasing primer concentration has the adverse effect of reducing the final amplified template concentration. This phenomenon seen at times experimentally is explained by the simulation results under rate limiting enzyme concentrations. Primer dimer formation is shown to significantly affect the reaction rates, effective efficiency, and the estimated initial concentrations. This model, by describing the interplay of the many operating variables, will be a useful tool in designing PCR conditions and evaluating its results.

Computer Simulation↗

Mathematical models in quantitative assessment of carcinogenic risk.

Regulatory guidelines have specified default assumptions for the calculation of upper bounds on potential carcinogenic risk. These default "science policy" assumptions are used in the absence of more appropriate biological information, but can, in theory, be overridden by compound-specific data. As a screening tool, the standard LMS procedure provides a useful yardstick for regulators to compare hazard potential across compounds and across exposure scenarios. This standard methodology does not estimate actual risk, however. When specific compounds are being considered for detailed evaluation, methodology for more accurately estimating the true risk is often available. Pharmacokinetic models can be used to more accurately define the high-dose to low-dose extrapolation as well as to provide insight into across route and across species extrapolations. "More central" estimates of the upper bound on risk can be derived, or decision analysis techniques can be used to define the probability distribution of risk estimates, as the assumptions are changed. These data give the risk manager more information as to the relevance of the upper bound, and should be presented in any risk estimate to provide a richer demonstration as to the true risk.

Animals↗

Novel gliosarcoma cell line expressing green fluorescent protein: A model for quantitative assessment of angiogenesis.

Angiogenesis is essential for tumor proliferation and metastasis. The extent of angiogenesis is measured by microvessel density (MVD) which has been identified as an independent prognostic factor for relapse-free survival in cancer patients. Existing methods of MVD assessment measure the microvessel count in the most active area of neovascularization ("hot spots") using antibodies against vascular endothelial antigens. This may produce unreliable results because of tissue volume loss and misshapening during the fixation and dehydration procedures. We report here a genetically engineered 9L cell line constitutively expressing green fluorescent protein that can be visualized using fluorescence microscopy without additional histological staining. The model developed in this study allows for the performance of simple and easy MVD counting, assuming that nonfluorescent "black spots" visible by fluorescence microscopy within the borders of the tumor tissue represent blood vessels. This assumption was confirmed by a comparative study utilizing conventional histological methods, anti-CD31 immunohistology, and Hoechst 33258 dye exclusion. This model is also useful for delineation of the true borders between tumor and normal brain tissue, including microscopic tumor extensions, without multiple histological staining. The suggested model allows quantification of tumor angiogenesis in tissue specimens, thus providing independent prognostic information about tumor growth and regression. It is expected to be most valuable in evaluating the efficacy of anti-angiogenic therapy.

Animals↗

The use of medical images in planning and delivery of radiation therapy.

The authors provide a survey of how images are used in radiation therapy to improve the precision of radiation therapy plans, and delivery of radiation treatment. In contrast to diagnostic radiology, where the focus is on interpretation of the images to decide if disease is present, radiation therapy quantifies the extent of the region to be treated, and relates it to the proposed treatment using a quantitative modeling system called a radiation treatment planning (RTP) system. This necessitates several requirements of image display and manipulation in radiation therapy that are not usually important in diagnosis. The images must have uniform spatial fidelity: i.e., the pixel size must be known and consistent throughout individual images, and between spatially related sets. The exact spatial relation of images in a set must be known. Radiation oncologists draw on images to define target volumes; dosimetrists use RTP systems to superimpose quantitative models of radiation beams and radiation dose distributions on the images and on the sets of organ and target contours derived from them. While this mainly uses transverse cross-sectional images, projected images are also important, both those produced by the radiation treatment simulator and the treatment machines, and so-called "digital reconstructed radiographs," computed from spatially related sets of cross-sectional images. These requirements are not typically met by software produced for radiologists but are addressed by RTP systems. This review briefly summarizes ongoing work on software development in this area at the University of Washington Department of Radiation Oncology.

Computer Communication Networks↗

Effects of fixation and substrate protection on the isoenzymes of aspartate aminotransferase studied in a quantitative cytochemical model system.

The cytochemical technique of Lee and Torack for the demonstration of aspartate aminotransferase activity was tested on a model system consisting of either total liver homogenate or the mitochondrial or soluble cytoplasmic fraction, incorporated in polyacrylamide film. After incubation of portions of film in a medium of alpha-ketoglutarate, L-aspartate, and lead nitrate, the lead oxaloacetate formed was converted to lead sulfide. The absorbance determined at 520 nm in a film spectrophotometer and expressed in terms of unit weight of film provided a measure of the contained enzymatic activity, and was directly proportional to the concentration of chemically determined oxaloacetate in the film. Both mitochondrial and "soluble" isozymes of aspartate aminotransferase reacted with the cytochemical media to a quantitatively similar degree, but were considerably inactivated after 15 min of treatment with 1% glutaraldehyde or 3.7% formaldehyde in imidazole buffer, the rate of inactivation being greater for the soluble isozyme. Application of the principle of substrate protection delayed inactivation. Thus, for both isozymes the rate of inactivation decreased if ketoglutarate was added to the fixative. Similarly, it was shown that the optimal incubation medium for the demonstration of the soluble isozyme must contain 4 mM of alpha-ketoglutarate and 20 mM of L-aspartate. Under these conditions the turnover-number for the cytochemical system is 70% of the value obtained from biochemical estimations. Cytochemical K(m) values differed for each isozyme and were in accord with values determined by biochemical techniques, indicating that the model system can be used as a link between biochemical and cytochemical data in enzymatic studies.

Aldehydes↗

Qualitative and quantitative experimental models to aid in risk assessment for immunotoxicology.

We have previously reported on the design and content of a screening battery using a "tier" approach for detecting potential immunosuppressive compounds in mice [1]. This battery was composed of various immune function, immunopathology and host resistance tests, the results of which could help establish the potential of chemical and biological agents to cause immunosuppression. The data from these studies, which now encompass over 50 compounds, have been analyzed in an attempt to improve future testing strategies and provide information to aid in the risk assessment process. Specifically, the following two issues will be addressed; what are the likelihood(s) for each of the individual tests and testing configurations to accurately identify immunotoxic compounds? and what are the quantitative and qualitative relationships between the immune tests and host resistance assays?

Animals↗

Chromosome territories, interchromatin domain compartment, and nuclear matrix: an integrated view of the functional nuclear architecture.

Advances in the specific fluorescent labeling of chromatin in fixed and living human cells in combination with three-dimensional (3D) and 4D (space plus time) fluorescence microscopy and image analysis have opened the way for detailed studies of the dynamic, higher-order architecture of chromatin in the human cell nucleus and its potential role in gene regulation. Several features of this architecture are now well established: 1. Chromosomes occupy distinct territories in the cell nucleus with preferred nuclear locations, although there is no evidence of a rigid suprachromosomal order. 2. Chromosome territories (CTs) in turn contain distinct chromosome arm domains and smaller chromatin foci or domains with diameters of some 300 to 800 nm and a DNA content in the order of 1 Mbp. 3. Gene-dense, early-replicating and gene-poor, middle-to-late-replicating chromatin domains exhibit different higher-order nuclear patterns that persist through all stages of interphase. In mitotic chromosomes early replicating chromatin domains give rise to Giemsa light bands, whereas middle-to-late-replicating domains form Giemsa dark bands and C-bands. In an attempt to integrate these experimental data into a unified view of the functional nuclear architecture, we present a model of a modular and dynamic chromosome territory (CT) organization. We propose that basically three nuclear compartments exist, an "open" higher-order chromatin compartment with chromatin domains containing active genes, a "closed" chromatin compartment comprising inactive genes, and an interchromatin domain (ICD) compartment (Cremer et al., 1993; Zirbel et al., 1993) that contains macromolecular complexes for transcription, splicing, DNA replication, and repair. Genes in "open," but not in "closed" higher-order chromatin compartments have access to transcription and splicing complexes located in the ICD compartment. Chromatin domains that build the "open" chromatin compartment are organized in a way that allows the direct contact of genes and nascent RNA to transcription and splicing complexes, respectively, preformed in the ICD compartment. In contrast, chromatin domains that belong to the "closed" compartment are topologically arranged and compacted in a way that precludes the accessibility of genes to transcription complexes. We argue that the content of the ICD compartment is highly enriched in DNA depleted biochemical matrix preparations. The ICD compartment may be considered as the structural and functional equivalent of the in vivo nuclear matrix. A matrix in this functional sense is compatible with but does not necessitate the concept of a 3D nuclear skeleton existing of long, extensively arborized filaments. In the absence of unequivocal evidence for such a structural matrix in the nucleus of living cells we keep an agnostic attitude about its existence and possible properties in maintaining the higher-order nuclear architecture. Quantitative modeling of the 3D and 4D human genome architecture in situ shows that such an assumption is not necessary to explain presently known aspects of the higher-order nuclear architecture. We expect that the interplay of quantitative modeling and experimental tests will result in a better understanding of the compartmentalized nuclear architecture and its functional consequences.

Animals↗

Pleiotropic models of quantitative variation.

It is widely held that each gene typically affects many characters, and that each character is affected by many genes. Moreover, strong stabilizing selection cannot act on an indefinitely large number of independent traits. This makes it likely that heritable variation in any one trait is maintained as a side effect of polymorphisms which have nothing to do with selection on that trait. This paper examines the idea that variation is maintained as the pleiotropic side effect of either deleterious mutation, or balancing selection. If mutation is responsible, it must produce alleles which are only mildly deleterious (s approximately 10(-3)), but nevertheless have significant effects on the trait. Balancing selection can readily maintain high heritabilities; however, selection must be spread over many weakly selected polymorphisms if large responses to artificial selection are to be possible. In both classes of pleiotropic model, extreme phenotypes are less fit, giving the appearance of stabilizing selection on the trait. However, it is shown that this effect is weak (of the same order as the selection on each gene): the strong stabilizing selection which is often observed is likely to be caused by correlations with a limited number of directly selected traits. Possible experiments for distinguishing the alternatives are discussed.

Alleles↗

Maintenance of the metabolic homeostasis of the heart: developing a systems analysis approach.

The heart is almost unique in the body with a constant requirement to conduct work well beyond the normal maintenance of cellular integrity. With this constant workload, it is not surprising that cardiac energy conversion is highly specialized to maintain a constant supply of energy. This maintenance of cellular metabolites during alterations in workload has been termed metabolic homeostasis. Here we discuss our efforts to understand the cellular and mitochondrial control network that orchestrates the metabolic homeostasis of the heart. This begins with a better definition of the metabolic pathways, acute posttranslational control sites, and proper kinetic evaluation of the reaction steps in the intact mitochondrial environment. First, a quantitative model of mitochondrial energy conversion is presented and demonstrates several serious gaps in our knowledge of this process. Toward filling these gaps, screens of the entire mitochondrial proteome have been conducted to establish the metabolic pathways that need to be considered. In addition, the dynamic phosphoproteome of intact mitochondria, using 2D gel electrophoresis coupled to (32)P labeling, has revealed a remarkably extensive protein phosphorylation network throughout the mitochondrial metabolic network that has essentially been overlooked. Initial studies on evaluating the functional significance of these protein phosphorylations and the kinase-phosphatase system involved will be reviewed. One of the major deficits in the consensus quantitative model of oxidative phosphorylation to explain intact mitochondria activities is in complex I, where even the initiation of Nicotinamide Adenine Dinucleotide (reduced) (NADH) oxidation is problematical using in vitro kinetic data. Studies will be described where the NADH binding and oxidation kinetics at complex I in the intact mitochondria were determined using fluorescence lifetime and enzyme dependent-fluorescence recovery after photo-oxidation (ED-FRAP) techniques. These later studies suggest that matrix NADH binding characteristics are much different (>10(3) binding constant errors) than isolated proteins. In addition, complex I is far from equilibrium and may play an important role in regulating the rate of reducing equivalent delivery to the cytochromes.

Animals↗