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Predictions of tensile strength of binary tablets using linear and power law mixing rules.

There has recently been an increased interest in predicting the tensile strength of binary tablets from the properties of the individual components. In this paper, measurements are reported for tensile strength of tablets compressed from single-component and binary powder mixtures of lactose with microcrystalline cellulose (MCC), and lactose with two types of silicified microcrystalline cellulose (SMCC and SMCC-HD), which are different in compressibility. Measurements show the tensile strength increases with the relative density for single powders, and both with the relative density and the mass fraction of cellulose in the mixtures. It was also observed, for binary mixtures compacted at 50 and 150 MPa, that there was a slight variation in porosity with the mass fraction of celluloses. The predictions of the tensile strength of binary tablets from the characteristics of the single-components was analysed with the extended Ryshkewitch-Duckworth model by assuming both linear and power law mixing rules for the determination of the parameters "tensile strength at zero porosity and bonding capacity constant". As consequence, four models were analysed and compared with measurements using criteria based on the standard deviation from the mean values. Results showed a good prediction using a linear mixing rule combined with the power law. However, as the predictions of these models depend on the powders and the porosity range for the characterization of single-components, none of them can be systematically considered as being the best to predict binary behaviour from data for individual powders.

Cellulose↗

[Research on the nonlinear model of near infrared spectroscopy and the total sugar of tobacco samples].

Near infrared spectroscopy (NIR) is an instrumental method applied for rapidly measuring the NIR spectra of pulverized tobacco samples and computing the chemical compositions from the spectral data. In the present paper, a mixed algorithm was employed for building the nonlinear model of NIR and the total sugar of tobacco samples. The mixed algorithm was combined with Partial Least Squares (PLS) method and Artificial Neural Network (ANN). The model based on the mixed algorithm was divided into two parts: linear part and nonlinear part, and the corresponding model of each part was built respectively. Compared with the classical multivariate calibration methods such as Principle Component Regression (PCR), PLS and nonlinear PLS (NPLS), the proposed procedure performed much better. The results showed that the mixed algorithm could be used for the quantitative analysis of the total sugar in tobacco samples.

Calibration↗

Monomeric and polymeric anionic gemini surfactants and mixed surfactant systems in micellar electrokinetic chromatography. Part II: characterization of chemical selectivity using two linear solvation energy relationship models.

Sodium di(undecenyl) tartarate monomer (SDUT), a vesicle-forming amphiphilic compound possessing two hydrophilic carboxylate headgroups and two hydrophobic undecenyl chains, was prepared and polymerized to form a polymeric vesicle (i.e., poly-SDUT). The anionic surfactants of SDUT and poly-SDUT (carboxylate head group) and sodium dodecyl sulfate, SDS (sulfate head groups) as well as mixed surfactant systems (SDS/SDUT, SDS/poly-SDUT, and SDUT/poly-SDUT) were applied as pseudostationary phases in micellar electrokinetic chromatography (MEKC). Two linear solvation energy relationship (LSER) models, i.e., solvatochromic and solvation parameter models, were successfully applied to investigate the effect of the type and composition of pseudostationary phases on the retention mechanism and selectivity in MEKC. The solvatochromic and solvation parameter models were used to help understand the fundamental nature of the solute-pseudostationary phase interactions and to characterize the properties of the pseudostationary phases (e.g., solute size and hydrogen bond-accepting ability for all pseudostationary phases). The solute types were found to have a significant effect on the LSER system coefficients and on the predicted retention factors. Although both LSER models provide the same information, the solvation parameter model is found to provide much better results both statistically and chemically than the solvatochromic model.

Anions↗

Mixed graphical models for simultaneous model identification and control applied to the glucose-insulin metabolism.

In this paper a method for model identification of biological systems described by stochastic linear differential equations using a new computational technique for statistical Bayesian inference, namely mixed graphical models in the sense of Lauritzen and Wermuth, is presented. The model is identified in terms of biological model parameters and noise parameters. This non-linear estimation problem is solved by means of an exact inference algorithm. The parameter estimates are given as a-posteriori distributions which can be interpreted as fuzzy possibility distributions. For model-based simulations of the underlying biological system the model parameters are represented as uncertain parameters with the distributions obtained from the estimation procedure. We apply the presented methods to a model for the glucose-insulin metabolism: the Karlsburg model for type I diabetes.

Bayes Theorem↗

Macronutrient energy intake and adiposity in non obese prepubertal children aged 5-11 y (the Fleurbaix Laventie Ville Santé Study).

OBJECTIVE: To investigate associations between adiposity indices and food intake in nonobese prepubertal free-living children. SUBJECTS: Five-hundred and one children, 280 boys and 221 girls aged 5-11 y in two little towns in northern France. DESIGN: Cross-sectional survey. MAIN OUTCOME MEASURES: Height and weight, four skinfolds (biceps, triceps, subscapular, suprailiac), waist and hip girths, were measured. Sum of skinfolds (SSF), body mass index (BMI), and relative weight (RW) were calculated. Energy intake (EI), percentage of energy intake ascribed to carbohydrates (%EIC), complex carbohydrates (%EICC), fats (%EIF), saturated fats (%EISF) and proteins (%EIP) were assessed by a single 24 h record. Basal metabolic rate (BMRI was estimated according to Schofield's equations. Obese (RW > or = 120%), and underreporting children according to Goldberg's and Black's equations were excluded. RESULTS: In multiple linear regressions analyses performed with hierarchical mixed models, adiposity indices were significantly and inversely associated in girls with %EIC (all P-values < 0.02), and positively with %EIF (all P-values < 0.05, waist girth and BMI excepted). Similar but non-significant trends were observed in boys. The relationships were not linear, and thresholds close to current dietary recommendations were highlighted. When %EIF was low, a lower percentage of energy intake ascribed to %EISF was associated with thinness. These associations remained after the exclusion of children who had an EI/BMR > or = 1.50. CONCLUSIONS: In nonobese prepubertal children aged 5-11 y, a high %EIC, close to dietary recommendations (> or = 55%), was associated with thinness. A high %EIF, over the upper dietary recommendation (< or = 35%), was associated with a greater adiposity thickness. There was no further increase in adiposity beyond this threshold. Reasons for the absence of a linear relationship pattern between adiposity and macronutrient intake remain to be determined.

Adipose Tissue↗

Mixture model equations for marker-assisted genetic evaluation.

Marker-assisted genetic evaluation needs to infer genotypes at quantitative trait loci (QTL) based on the information of linked markers. As the inference usually provides the probability distribution of QTL genotypes rather than a specific genotype, marker-assisted genetic evaluation is characterized by the mixture model because of the uncertainty of QTL genotypes. It is, therefore, necessary to develop a statistical procedure useful for mixture model analyses. In this study, a set of mixture model equations was derived based on the normal mixture model and the EM algorithm for evaluating linear models with uncertain independent variables. The derived equations can be seen as an extension of Henderson's mixed model equations to mixture models and provide a general framework to deal with the issues of uncertain incidence matrices in linear models. The mixture model equations were applied to marker-assisted genetic evaluation with different parameterizations of QTL effects. A sire-QTL-effect model and a founder-QTL-effect model were used to illustrate the application of the mixture model equations. The potential advantages of the mixture model equations for marker-assisted genetic evaluation were discussed. The mixed-effect mixture model equations are flexible in modelling QTL effects and show desirable properties in estimating QTL effects, compared with Henderson's mixed model equations.

Animals↗

Differential and trajectory methods for time course gene expression data.

MOTIVATION: The issue of high dimensionality in microarray data has been, and remains, a hot topic in statistical and computational analysis. Efficient gene filtering and differentiation approaches can reduce the dimensions of data, help to remove redundant genes and noises, and highlight the most relevant genes that are major players in the development of certain diseases or the effect of drug treatment. The purpose of this study is to investigate the efficiency of parametric (including Bayesian and non-Bayesian, linear and non-linear), non-parametric and semi-parametric gene filtering methods through the application of time course microarray data from multiple sclerosis patients being treated with interferon-beta-1a. The analysis of variance with bootstrapping (parametric), class dispersion (semi-parametric) and Pareto (non-parametric) with permutation methods are presented and compared for filtering and finding differentially expressed genes. The Bayesian linear correlated model, the Bayesian non-linear model the and non-Bayesian mixed effects model with bootstrap were also developed to characterize the differential expression patterns. Furthermore, trajectory-clustering approaches were developed in order to investigate the dynamic patterns and inter-dependency of drug treatment effects on gene expression. RESULTS: Results show that the presented methods performed significant differently but all were adequate in capturing a small number of the potentially relevant genes to the disease. The parametric method, such as the mixed model and two Bayesian approaches proved to be more conservative. This may because these methods are based on overall variation in expression across all time points. The semi-parametric (class dispersion) and non-parametric (Pareto) methods were appropriate in capturing variation in expression from time point to time point, thereby making them more suitable for investigating significant monotonic changes and trajectories of changes in gene expressions in time course microarray data. Also, the non-linear Bayesian model proved to be less conservative than linear Bayesian correlated growth models to filter out the redundant genes, although the linear model showed better fit than non-linear model (smaller DIC). We also report the trajectories of significant genes-since we have been able to isolate trajectories of genes whose regulations appear to be inter-dependent.

Computer Simulation↗

Modeling of driver's collision avoidance maneuver based on controller switching model.

This paper presents a modeling strategy of human driving behavior based on the controller switching model focusing on the driver's collision avoidance maneuver. The driving data are collected by using the three-dimensional (3-D) driving simulator based on the CAVE Automatic Virtual Environment (CAVE), which provides stereoscopic immersive virtual environment. In our modeling, the control scenario of the human driver, that is, the mapping from the driver's sensory information to the operation of the driver such as acceleration, braking, and steering, is expressed by Piecewise Polynomial (PWP) model. Since the PWP model includes both continuous behaviors given by polynomials and discrete logical conditions, it can be regarded as a class of Hybrid Dynamical System (HDS). The identification problem for the PWP model is formulated as the Mixed Integer Linear Programming (MILP) by transforming the switching conditions into binary variables. From the obtained results, it is found that the driver appropriately switches the "control law" according to the sensory information. In addition, the driving characteristics of the beginner driver and the expert driver are compared and discussed. These results enable us to capture not only the physical meaning of the driving skill but the decision-making aspect (switching conditions) in the driver's collision avoidance maneuver as well.

Accidents, Traffic↗

Retention of basic science knowledge: a comparison between body system-based and clinical presentation curricula.

BACKGROUND: When the University of Calgary implemented the clinical presentation (CP) curriculum in 1994, it was prospectively decided to administer the National Board of Medical Examiner's Comprehensive Basic Science Exam (CBSE) as a measure of students' basic science knowledge retention. PURPOSE: The exam performance from 2 classes (1995, 1996) of the previous system-based (SB) curriculum was compared to exam performance of 2 classes (2000, 2002) of the CP curriculum. METHODS: Data analyses employed 2 statistical models (covariate multiple linear regression and hierarchical mixed effects), and effect sizes were computed. RESULTS: Differences between CBSE mean scores produced by students from the SB and CP curricula showed a curricular effect on students' retention of basic science knowledge. However, preexisting differences between groups were found to be in the small-to-medium range. CONCLUSION: Evidence supporting the potential of schemes within a CP curriculum and their relation to basic science knowledge retention was observed. Effect size for the CP curriculum on students' retention of basic science knowledge was substantial; however, a notable part of that difference can be accounted for by extraneous and confounding factors. Further research utilizing more rigorous designs to investigate the relation between schemes and basic science retention is warranted.

Alberta↗

[Modeling correlated data in epidemiology: mixed or marginal model?].

Correlated observations (within centers, families, subjects,.) are common in epidemiology. Even when one is only interested in the modeling of means according to risk factors, it is also necessary to model the variance-covariance matrix of the observations in order to make correct inferences on the parameters of interest. All the more so when the aim of the survey is the measurement of these correlations or of the variance of the random effects from which they are assumed to originate. We discuss, within the framework of the linear and of the logistic models, the implications of two choices for the modeling of covariances. The mixed model shows the unobserved elements responsible for the similarity between certain observations. In a longitudinal survey, for instance, one can use a random effect, specific to each subject, expressing how much a subject's trajectory is translated as compared to what is expected according to its characteristics (age, sex,.). The marginal approach leads to modeling separately the means and the covariance matrix of the observations. The distinction between these two approaches is important for non linear models, in particular the logistic one. We insist on the interconnection between a mixed model formulation and a marginal one, as well as on the implication of the choice in terms of the parameters' interpretation.

Epidemiologic Research Design↗

Copenhagen City Heart Study: longitudinal analysis of ventilatory capacity in diabetic and nondiabetic adults.

The natural history of lung function in diabetes is unknown due to the lack of longitudinal observations. The decline of forced expiratory volume in one second (FEV1) and forced vital capacity (FVC) was studied over 15 yrs in the 17,506 adult participants of The Copenhagen City Heart Study, which included 266 individuals with diabetes. Multiple linear regression and a mixed-effects model were used, taking into account correlation between repeated measurements and adjusting for relevant confounders. In both sexes, FEV1 and FVC were consistently lower in diabetic individuals, compared with healthy individuals, with an average reduction of approximately 8% of the predicted value. Longitudinal analyses showed that the decline of FEV1 and FVC in diabetic individuals was similar to that observed in nondiabetic subjects. It was concluded that although diabetic subjects have, on average, a lower forced expiratory volume in one second and forced vital capacity than individuals without diabetes, this deficit seems not to be progressive in the long term. These observations may be of importance with regard to diabetes treatment with inhaled pulmonary insulin, which is likely to become available within a few years.

Adult↗

Hospital- and patient-related characteristics determining maternity length of stay: a hierarchical linear model approach.

OBJECTIVES: The purpose of this study was to identify factors related to pregnancy and childbirth that might be predictive of a patient's length of stay after delivery and to model variations in length of stay. METHODS: California hospital discharge data on maternity patients (n = 499,912) were analyzed. Hierarchical linear modeling was used to adjust for patient case mix and hospital characteristics and to account for the dependence of outcome variables within hospitals. RESULTS: Substantial variation in length of stay among patients was observed. The variation was mainly attributed to delivery type (vaginal or cesarean section), the patient's clinical risk factors, and severity of complications (if any). Furthermore, hospitals differed significantly in maternity lengths of stay even after adjustment for patient case mix. CONCLUSIONS: Developing risk-adjusted models for length of stay is a complex process but is essential for understanding variation. The hierarchical linear model approach described here represents a more efficient and appropriate way of studying interhospital variations than the traditional regression approach.

Adult↗

Simultaneous determination of etoposide and its catechol metabolite in the plasma of pediatric patients by liquid chromatography/tandem mass spectrometry.

The anticancer drug etoposide is associated with leukemias with MLL gene translocations and other translocations as a treatment complication. The genotype of cytochrome P450 3A4 (CYP3A4), which converts etoposide to its catechol metabolite, influences the risk. In order to perform pharmacokinetic studies aimed at further elucidation of the translocation mechanism, we have developed and validated a liquid chromatography/electrospray/tandem mass spectrometry assay for the simultaneous analysis of etoposide and its catechol metabolite in human plasma. The etoposide analog teniposide was used as the internal standard. Liquid chromatography was performed on a YMC ODS-AQ column. Simultaneous determination of etoposide and its catechol metabolite was achieved using a small volume of plasma, so that the method is suitable for pediatric patients. The limits of detection were 200 ng ml(-1) etoposide and 10 ng ml(-1) catechol metabolite in human plasma and 25 ng ml(-1) etoposide and 2.5 ng ml(-1) catechol metabolite in protein-free plasma, respectively. Acceptable precision and accuracy were obtained for concentrations in the calibration curve ranges 0.2--100 microg ml(-1) etoposide and 10--5000 ng ml(-1) catechol metabolite in human plasma. Acceptable precision and accuracy for protein-free human plasma in the range 25--15 000 ng ml(-1) etoposide and 2.5--1500 ng ml(-1) etoposide catechol were also achieved. This method was selective and sensitive enough for the simultaneous quantitation of etoposide and its catechol as a total and protein-free fraction in small plasma volumes from pediatric cancer patients receiving etoposide chemotherapy. A pharmacokinetic model has been developed for future studies in large populations.

Antineoplastic Agents, Phytogenic↗

[Individual variability in the duration of the second phase of the mixed dentition].

With a collection of dental casts from a longitudinal study of 175 orthodontically untreated probands (100 children without and 75 children with premature loss of deciduous molars and/or canines) serving as a base, the duration of the second period of mixed dentition was determined to be in relation to the probands the period of time between the gingival emergence of the first permanent buccal tooth and the full eruption of the set of teeth. The second period of mixed dentition in boys without premature loss of deciduous molars and canines lasts on an average 3.6 +/- 1.1 years and in girls 3.8 +/- 1.0 years. In cases of premature loss of deciduous molars and/or canines, the period of dentition is distinctly longer than under normal development conditions. The outside parameters (boys: Xmin = 0.9 years, Xmax = 6.2 years; girls: Xmin = 2.6 years, Xmax = 8.6 years), reflect a high degree of variability. The duration of the second period of mixed dentition is significantly affected by "the point in time of inception" and by the criteria "morphologically intact support zones" and "premature loss of deciduous molars and/or canines". Even given such data, however, it is not possible to make a sufficiently reliable prediction on an individual basis of the duration of the dentition.

Child↗

Morphine pharmacokinetics during venoarterial extracorporeal membrane oxygenation in neonates.

OBJECTIVE: To study morphine pharmacokinetics in neonates undergoing venoarterial ECMO and to quantify differences between these neonates and neonates subjected to noncardiac major surgery. DESIGN AND SETTING: Observational study in a level III referral center. PATIENTS AND METHODS: Pharmacokinetic estimates from 14 neonates undergoing ECMO were compared with findings from a previous study in 0- to 3-year-olds after noncardiac major surgery using a nonlinear mixed effect model. A one-compartment linear disposition model with zero-order input (infusion) and first-order elimination was used to describe all data. RESULTS: Clearance in neonates (age <7 days) at the start of ECMO (2.2 l per hour per 70 kg) was lower than that in postoperative neonates (10.5 l per hour per 70 kg) but increased rapidly (maturation half-life 30 and 70 days, respectively) and equaled that of the postoperative group after 14 days. Clearance was affected by size and age only. Exchange transfusion, when used, contributed only 1.1% (CV 46%) of total clearance. Distribution volume increased with age and was 2.5 times (CV 102%) greater in ECMO children than in postoperative children. The between-subject variability values for volume of distribution and clearance were 49.4% and 38.7%. Weight and age information explained 83% of the overall clearance variability and 60% of overall distribution volume variability. CONCLUSIONS: Morphine clearance is reduced in infants requiring ECMO, possibly reflecting severity of illness. Clearance maturation on ECMO is rapid and normalizes within 2 weeks. Initial morphine dosing may be guided by age and weight, but clearance and distribution volume changes (and their variability) during prolonged ECMO suggests that morphine therapy should be subsequently guided by clinical monitoring.

Chi-Square Distribution↗

Evaluation and comparison of alternatives to Protein A chromatography Mimetic and hydrophobic charge induction chromatographic stationary phases.

In this paper Protein A mimetic and hydrophobic charge induction chromatographic (HCIC) stationary phases are characterized in terms of their protein adsorption characteristics and their selectivity is compared with Protein A chromatography using a set of Chinese hamster ovary-derived monoclonal antibodies and Fc-fusion proteins. Linear retention experiments were employed to compare the selectivities of these resins for both non-IgG model proteins as well as antibodies and the fusion proteins. While none of the non-IgG model proteins were observed to bind to the Protein A resin, most of them did in fact bind to the alternative resins. In addition, while the elution pH was similar for the model proteins and antibodies on the HCIC resin, the mimetic resins did exhibit higher binding for the antibodies under these linear pH gradient conditions. A mixed mode preparative isotherm model previously developed for HCIC was shown to accurately describe the adsorption behavior of the mimetic materials as well. Host cell protein clearance profiles were also investigated under preparative conditions using complex biological feeds and the results indicated that while some selectivity was observed for both the HCIC and the mimetic materials, the purification factors were in general significantly less than those obtained with Protein A. It is important to note, however, that the selectivity of the mimetic and HCIC materials was also observed to be antibody specific indicating that further optimization may well result in increased selectivities for these materials.

Animals↗

A retrospective chart review of the clinical effects of atypical antipsychotic drugs on glycemic control in institutionalized patients with schizophrenia and comorbid diabetes mellitus.

BACKGROUND: The association between schizophrenia and onset of type 2 diabetes mellitus (DM) is well documented. It is unclear whether this association is due to inherent risk factors in individuals with schizophrenia or to treatment with antipsychotic drugs, particularly atypical antipsychotic agents. OBJECTIVES: The goals of this retrospective, observational study were the following: (1) to determine whether adequate glycemic control could be achieved in patients with schizophrenia and comorbid DM who were undergoing treatment with atypical antipsychotic drugs, (2) to identify inherent risk factors that may affect glycemic control in this patient population, and (3) to consider the possibility that combined medication and inherent risk factors may affect glycemic control. METHODS: This was a retrospective, observational chart review that evaluated institutionalized patients in a New Jersey mental institution with concurrent diagnoses of schizophrenia and type 1 or 2 DM who were being treated with atypical antipsychotic agents (ie, olanzapine, risperidone, clozapine, or quetiapine) and were referred by their hospital internists to a weekly, half-day, in-hospital DM clinic. All patients with initial and end-point data for the efficacy measure (ie, change in glycosylated hemoglobin [HbA(1c)]) were included in the analysis. Mixed-effects linear and least-squares models were used to test whether a specific comorbidity had an effect on the change in HbA(1c) adjusted for the duration of the observation. RESULTS: A total of 72 patients met entry criteria. Among the 38 patients with baseline and end-point data (20 treated with olanzapine and 18 treated with risperidone), mean (SD) HbA(1c) decreased from 8.21% (2.4%) to 7.62% (1.7%). The only baseline demographic characteristic or comorbidity that predicted significant worsening in the adjusted HbA(1c) change was hepatitis (P = 0.003). CONCLUSIONS: Using appropriate, aggressive antidiabetic therapy, glycemic control was achieved in this group of patients with schizophrenia and comorbid DM who were treated with atypical antipsychotic agents.

Adult↗