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PubMed2001

Structures of copper(II) and manganese(II) di(hydrogen malonate) dihydrate; effects of intensity profile truncation and background modelling on structure models.

The crystal structures of the title compounds were determined with net intensities I derived via the background-peak-background procedure. Least-squares optimizations reveal differences between the low-order (0 < s < 0.7 A(-1)) and high-order (0.7 < s < 1.0 A(-1)) structure models. The scale factors indicate discrepancies of up to 10% between the low-order and high-order reflection intensities. This observation is compound independent. It reflects the scan-angle-induced truncation error, because the applied scan angle (0.8 + 2.0 tan theta) degrees underestimates the wavelength dispersion in the monochromated X-ray beam. The observed crystal structures show pseudo-I-centred sublattices for three of its non-H atoms in the asymmetric unit. Our selection of observed intensities (I > 3 sigma) stresses that pseudo-symmetry. Model refinements on individual data sets with (h + k + l) = 2n and (h + k + l) = 2n + 1 illustrate the lack of model robustness caused by that pseudo-symmetry. To obtain a better balanced data set and thus a more robust structure we decided to exploit background modelling. We described the background intensities B(H-->) with an 11th degree polynomial in straight theta. This function predicts the local background b at each position H--> and defines the counting statistical distribution P(B), in which b serves as average and variance. The observation R defines P(R). This leads to P(I) = P(R)/P(B) and thus I = R - b and sigma(2)(I) = I so that the error sigma(I) is background independent. Within this framework we reanalysed the structure of the copper(II) derivative. Background modelling resulted in a structure model with an improved internal consistency. At the same time the unweighted R value based on all observations decreased from 10.6 to 8.4%. A redetermination of the structure at 120 K concluded the analysis.

Journal Article↗

PubMed1991

A three-dimensional motion model of loads on the lumbar spine: I. Model structure.

Traditionally most biomechanical models that are used to estimate the loading experienced by the spine during work focus on static, two-dimensional representations of the work. However, most work tasks impose loads on the lumbar spine under dynamic, three-dimensional conditions. The objective of this study was to describe the structure and logic of a model that is capable of producing estimates of spine loading under three-dimensional motion conditions. This model is intended for use primarily under laboratory conditions. The model was designed initially for workplace simulation in which the trunk is moving under symmetric and asymmetric constant velocity lifting conditions. Future embellishments may enable the model to be used under free dynamic conditions. The model predicts lumbar spine compression, shear, and torsional forces as well as trunk torque production continuously throughout the exertion. This information may be compared with spine tolerance limits so that the risk of causing a vertebral end-plate microfracture by workplace requirements could be determined.

Biomechanical Phenomena↗

PubMed1999

In vitro models of biological responses to implant microbiological models.

To study the etiology and explore possibilities for the therapy of implant-associated infections, investigators have developed and utilized various in vitro models. Major contributions have come from the non-oral medical field, where device-related infections can create life-threatening situations. Microbiological models may include (i) models to study the reaction of micro-organisms to the presence of implants, (ii) models to study the reaction of implant-associated micro-organisms to antimicrobial agents, and (iii) models to study the reaction of the host tissues to the presence of implants contaminated with micro-organisms. In evaluating the potential usefulness of these models for research in oral implantology, one must consider common features as well as important differences between implanted medical devices and oral implants. Although infections associated with implantable medical devices and oral peri-implant infections share a remarkable number of common features, there are also important differences that need attention when findings from in vitro experiments are extrapolated to clinical relevance.

Anti-Bacterial Agents↗

PubMed1995

Clarifying body-image disturbance: analysis of a multidimensional model using structural modeling.

A multidimensional model of body-image disturbance was tested. The model incorporated the concepts of body-size distortion, preference for thinness, body dissatisfaction, and fear of fatness as predictors of restrictive eating. The LISREL 7 program was used to perform a structural modeling analysis of the theoretical model. A total of 175 women participated in the study (54 eating-disordered patients and 121 undergraduate students). The results supported the hypothesized four-dimensional model relative to alternative one-, two-, and three-dimensional models. Body dissatisfaction appeared to be directly affected by both body-size distortion and preference for thinness. Fear of fatness was found to be the best predictor of restrictive eating. The results appeared consistent across the clinical and nonclinical samples. These data may help resolve many of the current controversies in the body-image literature. The results also suggested the need to develop more sound assessment instruments for fear of fatness.

Journal Article↗

PubMed2005

Comparison of the University of California at Los Angeles Line-by-Line Equivalent Radiative Transfer Model and the Moderate-Resolution Transmission Model for accuracy assessment of the National Polar-Orbiting Operational Environmental Satellite System's Visible-Infrared Imager-Radiometer Suite cloud algorithms.

To support the verification and implementation of the National Polar-Orbiting Operational Environmental Satellite System's Visible-Infrared Imaging-Radiometric Suite (VIIRS) algorithms used for inferring cloud environmental data records, an intercomparison effort has been carried out to assess the consistency between the simulated cloudy radiances-reflectances from the University of California at Los Angeles Line-by-Line Equivalent Radiative Transfer Model and those from the Moderate-Resolution Transmission Model (MODTRAN) with the 16 stream Discrete Ordinate Radiative Transfer Model (DISORT) incorporated. For typical ice and water cloud optical depths and particle sizes, we found discrepancies in the visible and near-infrared reflectances from the two models, which presumably are due to the difference in phase function (nonspherical versus Henyey-Greenstein), different numbers of phase function expansion terms (16 versus 200 terms), and different treatment of forward peak truncation in each model. Using the MODTRAN4, we also found substantial differences in the infrared radiances for optically thick clouds. These differences led to the discovery by MODTRAN4 developers of an inconsistency in the MODTRAN4-DISORT interface. MODTRAN4 developers corrected the inconsistency, which provided dramatic reductions in the differences between the two radiative transfer models. The comparison not only affects the prospective test plan for the VIIRS cloud algorithms but also should lead to improvements in future MODTRAN releases.

Journal Article↗

PubMed2001

Modelling soft tissue for kinematic analysis of multi-segment human body models.

Traditionally biomechanical models represent the musculoskeletal system by a series of rigid links connected by rigidly defined rotational joints. More recently though the mechanics of joints and the action of soft tissues has come under closer scrutiny: biomechanical models might now include a full range of physiological structures. However, soft tissue representation, within multi-segment human body models, presents significant problems; not least in computational speed. We present a method for representing soft tissue physiology which provides for soft tissue wrapping around multiple bony objects; while showing forces at the insertion points, as well as normal reactions due to contact between the soft and bony tissues. These soft tissue representations may therefore be used to constrain the joint, as ligaments would, or to generate motion, like a muscle, so that joints may be modelled which more accurately simulate musculoskeletal motion in all degrees of freedom--rotational and translational. This method produces soft tissues that do not need to be tied to a certain path or route between the bony structures, but may move with the motion of the model; demonstrating a more realistic analysis of soft tissue activity in the musculoskeletal system. The combination of solid geometry models of the skeletal structure, and these novel soft tissue representations, may also provide a useful approach to synthesised human motion.

Biomechanical Phenomena↗

PubMed2001

Using features of Arden Syntax with object-oriented medical data models for guideline modeling.

Computer-interpretable guidelines (CIGs) can deliver patient-specific decision support at the point of care. CIGs base their recommendations on eligibility and decision criteria that relate medical concepts to patient data. CIG models use expression languages for specifying these criteria, and define models for medical data to which the expressions can refer. In developing version 3 of the GuideLine Interchange Format (GLIF3), we used existing standards as the medical data model and expression language. We investigated the object-oriented HL7 Reference Information Model (RIM) as a default data model. We developed an expression language, called GEL, based on Arden Syntax's logic grammar. Together with other GLIF constructs, GEL reconciles incompatibilities between the data models of Arden Syntax and the HL7 RIM. These incompatibilities include Arden's lack of support for complex data types and time intervals, and the mismatch between Arden's single primary time and multiple time attributes of the HL7 RIM.

Decision Making, Computer-Assisted↗

PubMed1999

Modelling the EuroQol data: a comparison of discrete choice conjoint and conditional preference modelling.

This article compares two measurement strategies for measuring EuroQol health state preferences: (a) conditional preference modelling, implemented using rating scale and standard gamble scaling methods and (b) discrete choice conjoint modelling. The nature of the model form of the EuroQol health status preference function and the predictive ability of each measurement strategy formed the basis of the comparison. Data were collected via personal interviews with 140 US patients, 139 of whom provided usable responses. Both strategies supported a multiplicative model form as representative of the EuroQol health status preference function and were acceptable in terms of predictive ability. The agreement of the two measurement strategies on the nature of the model form provides evidence of the convergent validity of the multiplicative nature of the EuroQol health status preference function in this patient population. Since both strategies were found to be acceptable in terms of predictive ability, further research comparing preference scores and measuring respondent evaluations of the methodologies is necessary to illustrate the relative strengths and weaknesses of different health state preference measurement methodologies.

Aged↗

PubMed2006

Model-based clustering of binary longitudinal atopic dermatitis disease histories by latent class mixture models.

Atopic dermatitis is a skin disease which affects mainly children, has a very strong genetical component, and manifests itself clinically as flexural excema in connection with torturing itching. The course of disease is notoriously changeable and runs in phases, therefore it is difficult to predict the future course of disease. To improve prediction it would be interesting to identify clusters of children with different disease histories because this would shed light on common genetic and environmental risk factors. We use, relying on previous work of Nagin, a Latent class mixture model to estimate, in a data-dependent and model-based fashion, a clustering of typical binary atopic dermatitis disease histories in children. The data were collected from 1990 to 1997 in the so called MAS-study, a prospective cohort study of 1314 children in five German cities. The original method of Nagin is extended in two different aspects, first we use bootstrap confidence intervals to account for uncertainty in curve fitting, and second, we propose to model covariates for cluster membership by Anderson's Stereotype regression model. We feel that the Latent class mixture model is a valuable tool for assessing the course of atopic dermatitis, yielding a wealth of communicable and graphically displayable results.

Algorithms↗

PubMed2002

Flexible parametric proportional-hazards and proportional-odds models for censored survival data, with application to prognostic modelling and estimation of treatment effects.

Modelling of censored survival data is almost always done by Cox proportional-hazards regression. However, use of parametric models for such data may have some advantages. For example, non-proportional hazards, a potential difficulty with Cox models, may sometimes be handled in a simple way, and visualization of the hazard function is much easier. Extensions of the Weibull and log-logistic models are proposed in which natural cubic splines are used to smooth the baseline log cumulative hazard and log cumulative odds of failure functions. Further extensions to allow non-proportional effects of some or all of the covariates are introduced. A hypothesis test of the appropriateness of the scale chosen for covariate effects (such as of treatment) is proposed. The new models are applied to two data sets in cancer. The results throw interesting light on the behaviour of both the hazard function and the hazard ratio over time. The tools described here may be a step towards providing greater insight into the natural history of the disease and into possible underlying causes of clinical events. We illustrate these aspects by using the two examples in cancer.

Antineoplastic Agents↗

PubMed2004

Modelling associations between time-to-event responses in pilot cancer clinical trials using a Plackett-Dale model.

This work was motivated by the need to find surrogate endpoints for survival of patients in oncology studies. The goal of this article is to determine associations between five time-to-event outcomes coming from three clinical trials for non-small cell lung cancer. To this end, we propose to use the multivariate Dale model for time-to-event data introduced by Tibaldi et al. (Stat. Med. 2003). We fit the model to these data, using a pseudo-likelihood approach to estimate the model parameters. We evaluate and compare the performance of different dimensional models and we relate the Dale model association parameter, i.e. the odds ratio, to well-known quantities such as Kendall's tau and Spearman's rho. Finally, the results are discussed with a perspective on surrogate marker validation. Some suggestions are made regarding further studies in this field.

Adjuvants, Immunologic↗

PubMed2001

Latent class marginal regression models for modelling youthful drug involvement and its suspected influences.

In longitudinal behavioural studies, it is common to have multiple categorical indicators for measuring a theoretical construct of interest. A latent class model is presented that accounts for the structure in a set of correlated, categorical variables measured at discrete time periods, drawing information from these variables to form a smaller number of latent classes. The dependence of the resulting latent class model parameters on suspected factors over time is simultaneously modelled using a baseline-category logistic regression model. Estimation of the model parameters is achieved using an estimating equations procedure. A motivating example is provided from a longitudinal study of suspected linkages between monitoring or supervision by parents and the occurrence of drug use behaviours in an epidemiologic sample of school-attending youths.

Adolescent↗

PubMedDate not supplied

Retroviral transduction models of Ph+ leukemia: advantages and limitations for modeling human hematological malignancies in mice.

There are two commonly used approaches to modeling human leukemia in mice: generation of mutant mice by traditional transgenic or knock-out/knock-in methods and retroviral bone marrow transduction and transplantation. For modeling leukemia, the retroviral model system has some distinct advantages over transgenic mice. Testing different forms and mutants of a given oncogene is much easier with the retroviral system and avoids the potential deleterious effects of expression of a transgene in nonhematopoietic tissues and during development. The retroviral provirus serves as a clonal marker of a transduced cell, facilitating analysis of clonality and transplantability of the malignancy. Finally, the retroviral system allows the assessment of the action of an oncogene in different subsets of hematopoietic precursor cells in the bone marrow, which is difficult or impossible with transgenic models. This article summarizes recent progress in modeling human Philadelphia-positive leukemia in mice with the retroviral bone marrow transduction/transplantation system and emphasizes the advantages and limitations of this approach with examples from the BCR-ABL leukemogenesis literature.

Animals↗

PubMed2005

Kinetic and mechanistic data needs for a human phsiologically based pharmacokinetic (PBPK) model for acrylamide: pharmacokinetic model for acrylamide.

A pharmacokinetic (PBPK) model has been developed for acrylamide (AMD) and its oxidative metabolite, glycidamide (GLY), in the rat based on available information. Despite gaps and limitations to the database, model parameters have been estimated to provide a relatively consistent description of the kinetics of acrylamide and glycidamide using a single set of values (with minor adjustments in some cases). Future kinetic and mechanistic studies will need to focus on the collection of key data for refining certain model parameters and for model validation, as well as for conducting studies that elucidate the mechanism of action. Development of a validated human AMD/GLY PBPK model capable of predicting target tissue doses at relevant dietary AMD exposures, in combination with expanding data on modes of action, should allow for a substantive improvement in the risk assessment of acrylamide in food.

Acrylamide↗

PubMed2005

Controlling acrylamide in French fry and potato chip models and a mathematical model of acrylamide formation: acrylamide: acidulants, phytate and calcium.

We previously reported that in potato chip and French fry models, the formation of acrylamide can be reduced by controlling pH during processing steps, either by organic (acidulants) or inorganic acids. Use of phytate, a naturally occurring chelator, with or without Ca++ (or divalent ions), can reduce acrylamide formation in both models. However, since phytate itself is acidic, the question remains as to whether the effect of phytate is due to pH alone or to additional effects. In the French fry model, the effects on acrylamide formation of pH, phytate, and/or Ca++ in various combinations were tested in either blanching or soaking (after blanching) steps. All treatments significantly reduced acrylamide levels compared to control. Among variables tested, pH may be the single most important factor for reducing acrylamide levels, while there were independent effects of phytate and/or Ca++ in this French fry model. We also developed a mathematical formula to estimate the final concentration of acrylamide in a potato chip model, using variables that can affect acrylamide formation: glucose and asparagine concentrations, cut potato surface area and shape, cooking temperature and time, and other processing conditions.

Acids↗

PubMed2003

The "two-headed" latent inhibition model of schizophrenia: modeling positive and negative symptoms and their treatment.

RATIONALE: Latent inhibition (LI), namely, poorer performance on a learning task involving a previously pre-exposed non-reinforced stimulus, is disrupted in the rat by the dopamine (DA) releaser amphetamine which produces and exacerbates psychotic (positive) symptoms, and this is reversed by treatment with typical and atypical antipsychotic drugs (APDs) which on their own potentiate LI. These phenomena are paralleled by disrupted LI in normal amphetamine-treated humans, in high schizotypal humans, and in schizophrenia patients in the acute stages of the disorder, as well as by potentiated LI in normal humans treated with APDs. Consequently, disrupted LI is considered to provide an animal model of positive symptoms of schizophrenia with face, construct and predictive validity. OBJECTIVES: To review most of the rodent data on the neural substrates of LI as well as on the effects of APDs on this phenomenon with an attempt to interpret and integrate these data within the framework of the switching model of LI; to show that there are two distinct LI models, disrupted and abnormally persistent LI; to relate these findings to the clinical condition. RESULTS: The nucleus accumbens (NAC) and its DA innervation form a crucial component of the neural circuitry of LI, and are involved at the conditioning stage. There is a clear functional differentiation between the NAC shell and core subregions whereby damage to the shell disrupts LI and damage to the core renders LI abnormally persistent under conditions that disrupt LI in normal rats. The effects of shell and core lesions parallel those produced by lesions to the major sources of input to the NAC: entorhinal cortex lesion, like shell lesion, disrupts LI, whereas hippocampal lesion, like core lesion, produces persistent LI with changes in context, and basolateral amygdala (BLA) lesion, like core lesion, produces persistent LI with extended conditioning. Systemically induced blockade of glutamatergic as well as DA transmission produce persistent LI via effects exerted at the conditioning stage, whereas enhancement of DA transmission disrupts LI via effects at the conditioning stage. Serotonergic manipulations can disrupt or potentiate LI via effects at the pre-exposure stage. Both typical and atypical APDs potentiate LI via effects at conditioning whereas atypical APDs in addition disrupt LI via effects at pre-exposure. Schizophrenia patients can exhibit disrupted or normal LI as a function of the state of the disorder (acute versus chronic), as well as persistent LI. CONCLUSIONS: Different drug and lesion manipulations produce two poles of abnormality in LI, namely, disrupted LI under conditions which lead to LI in normal rats, and abnormally persistent LI under conditions which disrupt it in normal rats. Disrupted and persistent LI are differentially responsive to APDs, with the former reversed by both typical and atypical APDs and the latter selectively reversed by atypical APDs. It is suggested that this "two-headed LI model" mimics two extremes of deficient cognitive switching seen in schizophrenia, excessive and retarded switching between associations, mediated by dysfunction of different brain circuitries, and can serve to model positive symptoms of schizophrenia and typical antipsychotic action, as well as negative symptoms of schizophrenia and atypical antipsychotic action.

Animals↗

PubMed1991

A multi-dimensional coalescent process applied to multi-allelic selection models and migration models.

For a sample of two genes from a population divided into an arbitrary number of allele classes, a general mathematical framework is developed to address the expectation and variance of the time of the most recent common ancestor. Depending on the meaning of allele classes and the manner in which genes can change among them, this framework can be applied to a diversity of population genetic models. By adoption of the infinite sites model, the effect on heterozygosity is modelled for balancing selection among allele classes, mutation between allele classes, migration among populations, and gene conversion between loci. Most results are described for a continuous time approximation to a discrete generation model. It is also shown how the discrete generation model can be used to study the hitch-hiking effect of favorable mutations.

Alleles↗

PubMed2006

Genetic mouse models of schizophrenia: from hypothesis-based to susceptibility gene-based models.

Translation of human genetic mutations into genetic mouse models is an important strategy to study the pathogenesis of schizophrenia, identify potential drug targets, and test new drugs for new antipsychotic treatments. Although it is impossible to recapitulate the full spectrum of schizophrenia symptoms in animal models, hypothesis-driven genetic mouse models have been successful in reproducing several schizophrenia-like behaviors and uncovering the roles of specific genes in dopamine and glutamine neurotransmission systems in mediating schizophrenia-like behaviors. Recent discoveries of susceptibility genes for schizophrenia and recognition of cognitive dysfunction as a core feature of schizophrenia and a phenotype of susceptibility for schizophrenia offer opportunities to develop newer genetic mouse models based on susceptibility. This new generation of genetic mouse models could shed light on the etiology of schizophrenia and lead us to new hypotheses, novel diagnostic tools, and more effective therapy.

Animals↗