Mechanistic modelling of pilling. Part II: Individual-fibre computational model

A one-dimensional computational model of pilling of a fibre assembly has been created. The model follows a set of individual fibres, as free ends and loops appear as fuzz and arc progressively withdrawn from the body of the assembly, and entangle to form pills, which eventually break off or are pulled out. The time dependence of the computation is given by ticks, which correspond to cycles of a wear and laundering process. The movement of the fibres is treated as a reptation process. A set of standard values is used as inputs to the computation. Predictions arc given of the change with a number Of cycles of mass of fuzz, mass of pills, and mass removed from the assembly. Changes in the standard values allow sensitivity studies to be carried out.

A Bayesian hierarchical model for categorical longitudinal data from a social survey of immigrants

The paper investigates a Bayesian hierarchical model for the analysis of categorical longitudinal data from a large social survey of immigrants to Australia. Data for each subject are observed on three separate occasions, or waves, of the survey. One of the features of the data set is that observations for some variables are missing for at least one wave. A model for the employment status of immigrants is developed by introducing, at the first stage of a hierarchical model, a multinomial model for the response and then subsequent terms are introduced to explain wave and subject effects. To estimate the model, we use the Gibbs sampler, which allows missing data for both the response and the explanatory variables to be imputed at each iteration of the algorithm, given some appropriate prior distributions. After accounting for significant covariate effects in the model, results show that the relative probability of remaining unemployed diminished with time following arrival in Australia.

Population pharmacokinetics of hydroxychloroquine in patients with rheumatoid arthritis

Hydroxychloroquine (HCQ) is an antimalarial drug that is also used as a second-line treatment of rheumatoid arthritis (RA). Clinically, the use of HCQ is characterized by a long delay in the onset of action, and withdrawal of treatment is often a result of inefficacy rather than from toxicity. The slow onset of action can be attributed to the pharmacokinetics (PK) of HCQ, and wide interpatient variability is evident. Tentative relationships between concentration and effect have been made, but to date, no population PK model has been developed for HCQ. This study aimed to develop a population PK model including an estimation of the oral bioavailability of HCQ. In addition, the effects of the coadministration of methotrexate on the PK of HCQ were examined. Hydroxychloroquine blood concentration data were combined from previous pharmacokinetic studies in patients with rheumatoid arthritis. A total of 123 patients were studied, giving the data cohort from four previously published studies. Two groups of patients were included: 74 received hydroxychloroquine (HCQ) alone, and 49 received HCQ and methotrexate (MTX). All data analyses were carried out using the NONMEM program. A one-compartment PK model was supported, rather than a three-compartment model as previously published, probably because of the clustering of concentrations taken at the end of a dosing interval. The population estimate of bioavailability of 0.75 (0.07), n = 9, was consistent with literature values. The parameter values from the final model were: (Cl) over bar = 9.9 +/- 0.4 L/h, (V) over bar 605 +/- 91 L, (k(d)) over bar = 0.77 +/- 0.22 hours(-1), (t(tag)) over bar = 0.44 +/- 0.02 hours. Clearance was not affected by the presence of MTX, and, hence, steady-state drug concentrations and maintenance dosage requirements were similar. A population PK model was successfully developed for HCQ.

Prospective evaluation of a D-optimal designed population pharmacokinetic study

Recently, methods for computing D-optimal designs for population pharmacokinetic studies have become available. However there are few publications that have prospectively evaluated the benefits of D-optimality in population or single-subject settings. This study compared a population optimal design with an empirical design for estimating the base pharmacokinetic model for enoxaparin in a stratified randomized setting. The population pharmacokinetic D-optimal design for enoxaparin was estimated using the PFIM function (MATLAB version 6.0.0.88). The optimal design was based on a one-compartment model with lognormal between subject variability and proportional residual variability and consisted of a single design with three sampling windows (0-30 min, 1.5-5 hr and 11 - 12 hr post-dose) for all patients. The empirical design consisted of three sample time windows per patient from a total of nine windows that collectively represented the entire dose interval. Each patient was assigned to have one blood sample taken from three different windows. Windows for blood sampling times were also provided for the optimal design. Ninety six patients were recruited into the study who were currently receiving enoxaparin therapy. Patients were randomly assigned to either the optimal or empirical sampling design, stratified for body mass index. The exact times of blood samples and doses were recorded. Analysis was undertaken using NONMEM (version 5). The empirical design supported a one compartment linear model with additive residual error, while the optimal design supported a two compartment linear model with additive residual error as did the model derived from the full data set. A posterior predictive check was performed where the models arising from the empirical and optimal designs were used to predict into the full data set. This revealed the optimal'' design derived model was superior to the empirical design model in terms of precision and was similar to the model developed from the full dataset. This study suggests optimal design techniques may be useful, even when the optimized design was based on a model that was misspecified in terms of the structural and statistical models and when the implementation of the optimal designed study deviated from the nominal design.

NMR imaging of the diffusion of water at 37 degrees C into poly(2-hydroxyethyl methacrylate) containing aspirin or vitamin B-12

The ingress of water into poly(2-hydroxyethyl methacrylate), PHEMA, loaded with either one of two model drugs, vitamin B-12 or aspirin, was studied at 37 degreesC using three-dimensional NMR imaging. PHEMA was loaded with 5 and 10 wt % of the drugs. From the imaging profiles, it was observed that incorporation of vitamin B-12 into PHEMA resulted in enhanced crack formation on sorption of water and the crack healing behind the diffusion front was slower than for PHEMA without added drug. This was accounted for by the anti-plasticization of PHEMA by vitamin B-12. Crack formation was inhibited in the P-HEMA-aspirin systems because of the plasticizing effect of the aspirin on the PHEMA matrix. All of the polymers were found to absorb water according to an underlying Fickian diffusion mechanism. For PHEMA loaded with 5 wt % of aspirin or vitamin B-12, the best values of the water diffusion coefficients were both found to be 1.3 +/- 0.1 x 10(-11) m(2) s(-1) at 37 degreesC, while the values for the polymer loaded with 10 wt % of the drugs were slightly higher, 1.5 +/- 0.1 x 10(-11) m(2) s(-1).

Adsorption of ethylene on graphitized thermal carbon black and in slit pores: A computer simulation study

In this paper, we studied vapor-liquid equilibria (VLE) and adsorption of ethylene on graphitized thermal carbon black and in slit pores whose walls are composed of graphene layers. Simple models of a one-center Lennard-Jones (LJ) potential and a two-center united atom (UA)-LJ potential are investigated to study the impact of the choice of potential models in the description of VLE and adsorption behavior. Here, we used a Monte Carlo simulation method with grand canonical Monte Carlo (GCMC) and Gibbs ensemble Monte Carlo ensembles. The one-center potential model cannot describe adequately the VLE over the practical range of temperature from the triple point to the critical point. On the other hand, the two-center potential model (Wick et al. J. Phys. Chem. B 2000, 104, 8008-8016) performs well in the description of VLE (saturated vapor and liquid densities and vapor pressure) over the wide range of temperature. This UA-LJ model is then used in the study of adsorption of ethylene on graphitized thermal carbon black and in slit pores. Agreement between the GCMC simulation results and the experimental data on graphitized thermal carbon black for moderate temperatures is excellent, demonstrating that the potential of the GCMC method and the proper choice of potential model are essential to investigate adsorption. For slit pores of various sizes, we have found that the behavior of ethylene exhibits a number of features that are not manifested in the study of spherical LJ particles. In particular, the singlet density distribution versus distance across the pore and the angle between the molecular axis and the z direction provide rich information about the way molecules arrange themselves when the pore width is varied. Such an arrangement has been found to be very sensitive to the pore width.

Mass uptake study of the diffusion of water and SBF into poly(2-hydroxyethyl methacrylate-co-tetrahydrofurfuryI methacrylate) containing aspirin or vitamin B-12

The ingress of water and Kokubo simulated body fluid (SBF) into poly (2-hydroxyethyl methacrylate) (PHEMA), and its co-polymers with tetrahydrofurduryl methacrylate (THFMA), loaded with either one of two model drugs, vitamin 1312 or aspirin, was studied by mass uptake over the temperature range 298-318 K. The polymers were studied as cylinders and were loaded with either 5 wt% or 10 wt% of the drugs. From DSC studies it was observed that vitamin B-12 behaved as a physical cross-linker restricting chain segmental mobility, and so had a small anti-plasticisation effect on PHEMA and the co-polymers rich in HEMA, but almost no effect on the T-g of co-polymers rich in THFMA. On the other hand, aspirin exhibited a plasticising effect on PHEMA and the copolymers. All of the polymers were found to absorb water and SBF according to a Fickian diffusion mechanism. The polymers were all found to swell to a greater extent in SBF than in water, which was attributed to the presence of Tris buffer in the SBF. The sorptions of the two penetrants were found to follow Fickian kinetics in all cases and the diffusion coefficients at 310 K for SBF were found to be smaller than those for water, except for the polymers containing aspirin where the diffusion coefficients were higher than for the other systems. For example, for sorption into PHEMA the diffusion coefficient for water was 1.41 X 10(-11) m(2)/s and for SBF was 0.79 x 10-11 m(2)/s, but in the presence of 5 wt% aspirin the corresponding values were 1.27 x 10(-1)1 m(2)/s and 1.25 x 10(-11) m(2)/s, respectively. The corresponding values for PHEMA loaded with 5 wt% B-12 were 1.25 x 10(-11) m(2)/s and 0.74 x 10(-11) m(2)/s, respectively.

Accelerating, hyperaccelerating, and decelerating networks

Many growing networks possess accelerating statistics where the number of links added with each new node is an increasing function of network size so the total number of links increases faster than linearly with network size. In particular, biological networks can display a quadratic growth in regulator number with genome size even while remaining sparsely connected. These features are mutually incompatible in standard treatments of network theory which typically require that every new network node possesses at least one connection. To model sparsely connected networks, we generalize existing approaches and add each new node with a probabilistic number of links to generate either accelerating, hyperaccelerating, or even decelerating network statistics in different regimes. Under preferential attachment for example, slowly accelerating networks display stationary scale-free statistics relatively independent of network size while more rapidly accelerating networks display a transition from scale-free to exponential statistics with network growth. Such transitions explain, for instance, the evolutionary record of single-celled organisms which display strict size and complexity limits.

NMR imaging of the diffusion of water at 310 K into poly[(2-hydroxyethyl methacrylate)-co-(tetrahydrofurfuryl methacrylate)] containing vitamin B12 or aspirin

The ingress of water into copolymers of 2-hydroxyethyl methacrylate (HEMA) and tetrahydrofurfuryl methacrylate (THFMA) loaded with either one of two model drugs, ie vitamin B-12 or aspirin, was studied at 310 K using three-dimensional nuclear magnetic resonance (3D NMR) imaging. The poly(HEMA) was loaded with 5 wt% of the drugs. From the imaging profiles it was observed that incorporation of vitamin B-12 into the polymers rich in HEMA resulted in crack formation at the interface between the rubbery region and the glassy core on sorption of water, although these cracks were 'healed' behind the diffusion front. However, for the copolymers with low HEMA contents and for those containing aspirin, no evidence for similar crack formation was found. For the copolymers loaded with 5 wt% of aspirin or vitamin B-12 the values of the water diffusion coefficients, determined by curve-fitting the relative water concentration profiles from magnetic resonance imaging (MRI) measurements, were found to be smaller than those obtained from a mass uptake study. (C) 2004 Society of Chemical Industry.

Some considerations on the design of population pharmacokinetic studies

The goal of this manuscript is to introduce a framework for consideration of designs for population pharmacokinetic orpharmacokinetic-pharmacodynamic studies. A standard one compartment pharmacokinetic model with first-order input and elimination is considered. A series of theoretical designs are considered that explore the influence of optimizing the allocation of sampling times, allocating patients to elementary designs, consideration of sparse sampling and unbalanced designs and also the influence of single vs. multiple dose designs. It was found that what appears to be relatively sparse sampling (less blood samples per patient than the number of fixed effects parameters to estimate) can also be highly informative. Overall, it is evident that exploring the population design space can yield many parsimonious designs that are efficient for parameter estimation and that may not otherwise have been considered without the aid of optimal design theory.

Lifetime prevalence estimates of major depression: An indirect estimation method and a quantification of recall bias

The measurement of lifetime prevalence of depression in cross-sectional surveys is biased by recall problems. We estimated it indirectly for two countries using modelling, and quantified the underestimation in the empirical estimate for one. A microsimulation model was used to generate population-based epidemiological measures of depression. We fitted the model to 1-and 12-month prevalence data from the Netherlands Mental Health Survey and Incidence Study (NEMESIS) and the Australian Adult Mental Health and Wellbeing Survey. The lowest proportion of cases ever having an episode in their life is 30% of men and 40% of women, for both countries. This corresponds to a lifetime prevalence of 20 and 30%, respectively, in a cross-sectional setting (aged 15-65). The NEMESIS data were 38% lower than these estimates. We conclude that modelling enabled us to estimate lifetime prevalence of depression indirectly. This method is useful in the absence of direct measurement, but also showed that direct estimates are underestimated by recall bias and by the cross-sectional setting.

Comparison of blast furnace raceway size with theory

A previously developed one-dimensional mathematical model, to explain raceway hysteresis, is used to predict the raceway diameter in operating blast furnaces and hot models. Raceway size obtained from the open literature under various conditions for various blast furnaces are compared with computed predictions. In addition the predictions are also compared with published outcomes from other hot models. Simulated results on raceway diameter are in very good agreement with published operating blast furnace and hot model data. The effect of various parameters such as tuyere and hearth diameter, coke size and density, void fraction and bed height on raceway diameter has been studied.

Entangled-state cycles from conditional quantum evolution

A system of cascaded qubits interacting via the one-way exchange of photons is studied. While for general operating conditions the system evolves to a superposition of Bell states (a dark state) in the long-time limit, under a particular resonance condition no steady state is reached within a finite time. We analyze the conditional quantum evolution (quantum trajectories) to characterize the asymptotic behavior under this resonance condition. A distinct bimodality is observed: for perfect qubit coupling, the system either evolves to a maximally entangled Bell state without emitting photons (the dark state) or executes a sustained entangled-state cycle-random switching between a pair of Bell states while emitting a continuous photon stream; for imperfect coupling, two entangled-state cycles coexist, between which a random selection is made from one quantum trajectory to another.

Spin exchange and superconductivity in a t-J(')-V model for two-dimensional quarter-filled systems

The effect of antiferromagnetic spin fluctuations on two-dimensional quarter-filled systems is studied theoretically. An effective t-J(')-V model on a square lattice which accounts for checkerboard charge fluctuations and next-nearest-neighbor antiferromagnetic spin fluctuations is considered. From calculations based on large-N theory on this model it is found that the exchange interaction J(') increases the attraction between electrons in the d(xy) channel only, so that both charge and spin fluctuations work cooperatively to produce d(xy) pairing.

Critical behavior of one-particle spectral weights in the transverse Ising model

We investigate the critical behavior of the spectral weight of a single quasiparticle, one of the key observables in experiment, for the particular case of the transverse Ising model. Series expansions are calculated for the linear chain and the square and simple cubic lattices. For the chain model, a conjectured exact result is discovered. For the square and simple cubic lattices, series analyses are used to estimate the critical exponents. The results agree with the general predictions of Sachdev [Quantum Phase Transitions (Cambridge University Press, Cambridge, England, 1999)].