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.

Orientation of the genetic variance-covariance matrix and the fitness surface for multiple male sexually selected traits

Stabilizing selection has been predicted to change genetic variances and covariances so that the orientation of the genetic variance-covariance matrix (G) becomes aligned with the orientation of the fitness surface, but it is less clear how directional selection may change G. Here we develop statistical approaches to the comparison of G with vectors of linear and nonlinear selection. We apply these approaches to a set of male sexually selected cuticular hydrocarbons (CHCs) of Drosophila serrata. Even though male CHCs displayed substantial additive genetic variance, more than 99% of the genetic variance was orientated 74.9degrees away from the vector of linear sexual selection, suggesting that open-ended female preferences may greatly reduce genetic variation in male display traits. Although the orientation of G and the fitness surface were found to differ significantly, the similarity present in eigenstructure was a consequence of traits under weak linear selection and strong nonlinear ( convex) selection. Associating the eigenstructure of G with vectors of linear and nonlinear selection may provide a way of determining what long-term changes in G may be generated by the processes of natural and sexual selection.

Peptide quantification by matrix-assisted laser desorption ionisation time-of-flight mass spectrometry: Investigations of the cyclotide kalata B1 in biological fluids

A rapid method has been developed for the quantification of the prototypic cyclotide kalata B I in water and plasma utilizing matrix-assisted laser desorption ionisation time-of-flight (MALDI-TOF) mass spectrometry. The unusual structure of the cyclotides means that they do not ionise as readily as linear peptides and as a result of their low ionisation efficiency, traditional LC/MS analyses were not able to reach the levels of detection required for the quantification of cyclotides in plasma for pharmacokinetic studies. MALDI-TOF-MS analysis showed linearity (R-2 > 0.99) in the concentration range 0.05-10 mu g/mL with a limit of detection of 0.05 mu g/mL (9 fmol) in plasma. This paper highlights the applicability of MALDI-TOF mass spectrometry for the rapid and sensitive quantification of peptides in biological samples without the need for extensive extraction procedures. (c) 2005 Elsevier B.V. All rights reserved.

Spatial and ontogenetic variation in growth of nursery-bound juvenile lemon sharks, Negaprion brevirostris: a comparison of two age-assigning techniques

We compared growth rates of the lemon shark, Negaprion brevirostris, from Bimini, Bahamas and the Marquesas Keys (MK), Florida using data obtained in a multi-year annual census. We marked new neonate and juvenile sharks with unique electronic identity tags in Bimini and in the MK we tagged neonate and juvenile sharks. Sharks were tagged with tiny, subcutaneous transponders, a type of tagging thought to cause little, if any disruption to normal growth patterns when compared to conventional external tagging. Within the first 2 years of this project, no age data were recorded for sharks caught for the first time in Bimini. Therefore, we applied and tested two methods of age analysis: ( 1) a modified 'minimum convex polygon' method and ( 2) a new age-assigning method, the 'cut-off technique'. The cut-off technique proved to be the more suitable one, enabling us to identify the age of 134 of the 642 previously unknown aged sharks. This maximised the usable growth data included in our analysis. Annual absolute growth rates of juvenile, nursery-bound lemon sharks were almost constant for the two Bimini nurseries and can be best described by a simple linear model ( growth data was only available for age-0 sharks in the MK). Annual absolute growth for age-0 sharks was much greater in the MK than in either the North Sound (NS) and Shark Land (SL) at Bimini. Growth of SL sharks was significantly faster during the first 2 years of life than of the sharks in the NS population. However, in MK, only growth in the first year was considered to be reliably estimated due to low recapture rates. Analyses indicated no significant differences in growth rates between males and females for any area.

Determining the effective dimensionality of the genetic variance-covariance matrix

Determining the dimensionality of G provides an important perspective on the genetic basis of a multivariate suite of traits. Since the introduction of Fisher's geometric model, the number of genetically independent traits underlying a set of functionally related phenotypic traits has been recognized as an important factor influencing the response to selection. Here, we show how the effective dimensionality of G can be established, using a method for the determination of the dimensionality of the effect space from a multivariate general linear model introduced by AMEMIYA (1985). We compare this approach with two other available methods, factor-analytic modeling and bootstrapping, using a half-sib experiment that estimated G for eight cuticular hydrocarbons of Drosophila serrata. In our example, eight pheromone traits were shown to be adequately represented by only two underlying genetic dimensions by Amemiya's approach and factor-analytic modeling of the covariance structure at the sire level. In, contrast, bootstrapping identified four dimensions with significant genetic variance. A simulation study indicated that while the performance of Amemiya's method was more sensitive to power constraints, it performed as well or better than factor-analytic modeling in correctly identifying the original genetic dimensions at moderate to high levels of heritability. The bootstrap approach consistently overestimated the number of dimensions in all cases and performed less well than Amemiya's method at subspace recovery.

High speed DSC (hyper-DSC) as a tool to measure the solubility of a drug within a solid or semi-solid matrix

Conventional differential scanning calorimetry (DSC) techniques are commonly used to quantify the solubility of drugs within polymeric-controlled delivery systems. However, the nature of the DSC experiment, and in particular the relatively slow heating rates employed, limit its use to the measurement of drug solubility at the drug's melting temperature. Here, we describe the application of hyper-DSC (HDSC), a variant of DSC involving extremely rapid heating rates, to the calculation of the solubility of a model drug, metronidazole, in silicone elastomer, and demonstrate that the faster heating rates permit the solubility to be calculated under non-equilibrium conditions such that the solubility better approximates that at the temperature of use. At a heating rate of 400°C/min (HDSC), metronidazole solubility was calculated to be 2.16 mg/g compared with 6.16 mg/g at 20°C/min. © 2005 Elsevier B.V. All rights reserved.

Approximate Bayesian techniques for inference in stochastic dynamical systems

This thesis is concerned with approximate inference in dynamical systems, from a variational Bayesian perspective. When modelling real world dynamical systems, stochastic differential equations appear as a natural choice, mainly because of their ability to model the noise of the system by adding a variant of some stochastic process to the deterministic dynamics. Hence, inference in such processes has drawn much attention. Here two new extended frameworks are derived and presented that are based on basis function expansions and local polynomial approximations of a recently proposed variational Bayesian algorithm. It is shown that the new extensions converge to the original variational algorithm and can be used for state estimation (smoothing). However, the main focus is on estimating the (hyper-) parameters of these systems (i.e. drift parameters and diffusion coefficients). The new methods are numerically validated on a range of different systems which vary in dimensionality and non-linearity. These are the Ornstein-Uhlenbeck process, for which the exact likelihood can be computed analytically, the univariate and highly non-linear, stochastic double well and the multivariate chaotic stochastic Lorenz '63 (3-dimensional model). The algorithms are also applied to the 40 dimensional stochastic Lorenz '96 system. In this investigation these new approaches are compared with a variety of other well known methods such as the ensemble Kalman filter / smoother, a hybrid Monte Carlo sampler, the dual unscented Kalman filter (for jointly estimating the systems states and model parameters) and full weak-constraint 4D-Var. Empirical analysis of their asymptotic behaviour as a function of observation density or length of time window increases is provided.

A solvent-free matrix application method for matrix-assisted laser desorption/ionization imaging of small molecules

Matrix application continues to be a critical step in sample preparation for matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI). Imaging of small molecules such as drugs and metabolites is particularly problematic because the commonly used washing steps to remove salts are usually omitted as they may also remove the analyte, and analyte spreading is more likely with conventional wet matrix application methods. We have developed a method which uses the application of matrix as a dry, finely divided powder, here referred to as dry matrix application, for the imaging of drug compounds. This appears to offer a complementary method to wet matrix application for the MALDI-MSI of small molecules, with the alternative matrix application techniques producing different ion profiles, and allows the visualization of compounds not observed using wet matrix application methods. We demonstrate its value in imaging clozapine from rat kidney and 4-bromophenyl-1,4-diazabicyclo(3.2.2)nonane-4-carboxylic acid from rat brain. In addition, exposure of the dry matrix coated sample to a saturated moist atmosphere appears to enhance the visualization of a different set of molecules.

Techniques to improve forecasting models: applications to energy demand and price

This thesis is a study of three techniques to improve performance of some standard fore-casting models, application to the energy demand and prices. We focus on forecasting demand and price one-day ahead. First, the wavelet transform was used as a pre-processing procedure with two approaches: multicomponent-forecasts and direct-forecasts. We have empirically compared these approaches and found that the former consistently outperformed the latter. Second, adaptive models were introduced to continuously update model parameters in the testing period by combining ?lters with standard forecasting methods. Among these adaptive models, the adaptive LR-GARCH model was proposed for the fi?rst time in the thesis. Third, with regard to noise distributions of the dependent variables in the forecasting models, we used either Gaussian or Student-t distributions. This thesis proposed a novel algorithm to infer parameters of Student-t noise models. The method is an extension of earlier work for models that are linear in parameters to the non-linear multilayer perceptron. Therefore, the proposed method broadens the range of models that can use a Student-t noise distribution. Because these techniques cannot stand alone, they must be combined with prediction models to improve their performance. We combined these techniques with some standard forecasting models: multilayer perceptron, radial basis functions, linear regression, and linear regression with GARCH. These techniques and forecasting models were applied to two datasets from the UK energy markets: daily electricity demand (which is stationary) and gas forward prices (non-stationary). The results showed that these techniques provided good improvement to prediction performance.

Cost-exergy optimisation of linear Fresnel reflectors

This paper presents a new method for the optimisation of the mirror element spacing arrangement and operating temperature of linear Fresnel reflectors (LFR). The specific objective is to maximise available power output (i.e. exergy) and operational hours whilst minimising cost. The method is described in detail and compared to an existing design method prominent in the literature. Results are given in terms of the exergy per total mirror area (W/m2) and cost per exergy (US $/W). The new method is applied principally to the optimisation of an LFR in Gujarat, India, for which cost data have been gathered. It is recommended to use a spacing arrangement such that the onset of shadowing among mirror elements occurs at a transversal angle of 45°. This results in a cost per exergy of 2.3 $/W. Compared to the existing design approach, the exergy averaged over the year is increased by 9% to 50 W/m2 and an additional 122 h of operation per year are predicted. The ideal operating temperature at the surface of the absorber tubes is found to be 300 °C. It is concluded that the new method is an improvement over existing techniques and a significant tool for any future design work on LFR systems

Interactions at the head-tape interface of a linear tape system

Many of the recent improvements in the capacity of data cartridge systems have been achieved through the use of narrower tracks, higher linear densities and continuous servo tracking with multi-channel heads. These changes have produced new tribological problems at the head/tape interface. It is crucial that the tribology of such systems is understood and this will continue since increasing storage capacities and faster transfer rates are constantly being sought. Chemical changes in the surface of single and dual layer MP tape have been correlated to signal performance. An accelerated tape tester, consisting of a custom made cycler ("loop tester"), was used to ascertain if results could be produced that were representative of a real tape drive system. A second set of experiments used a modified tape drive (Georgens cycler), which allowed the effects of the tape transport system on the tape surface to be studied. To isolate any effects on the tape surface due to the head/tape interface, read/write heads were not fitted to the cycler. Two further sets of experiments were conducted which included a head in the tape path. This allowed the effects of the head/tape interface on the physical and chemical properties of the head and tape surfaces to be investigated. It was during the final set of experiments that the effect on the head/tape interface, of an energised MR element, was investigated. The effect of operating each cycler at extreme relative humidity and temperature was investigated through the use of an environmental chamber. Extensive use was made of surface specific analytical techniques such as XPS, AFM, AES, and SEM to study the physical and chemical changes that occur at the head/tape interface. Results showed that cycling improved the signal performance of all the tapes tested. The data cartridge drive belt had an effect on the chemical properties of the tape surface on which it was in contact. Also binder degradation occurred for each tape and appeared to be greater at higher humidity. Lubricant was generally seen to migrate to the tape surface with cycling. Any surface changes likely to affect signal output occurred at the head surface rather than the tape.

Advanced optical techniques for high capacity transmission

This thesis presents several advanced optical techniques that are crucial for improving high capacity transmission systems. The basic theory of optical fibre communications are introduced before optical solitons and their usage in optically amplified fibre systems are discussed. The design, operation, limitations and importance of the recirculating loop are illustrated. The crucial role of dispersion management in the transmission systems is then considered. Two of the most popular dispersion compensation methods - dispersion compensating fibres and fibre Bragg gratings - are emphasised. A tunable dispersion compensator is fabricated using the linear chirped fibre Bragg gratings and a bending rig. Results show that it is capable of compensating not only the second order dispersion, but also higher order dispersion. Stimulated Raman Scattering (SRS) are studied and discussed. Different dispersion maps are performed for all Raman amplified standard fibre link to obtain maximum transmission distances. Raman amplification is used in most of our loop experiments since it improves the optical signal-to-noise ratio (OSNR) and significantly reduces the nonlinear intrachannel effects of the transmission systems. The main body of the experimental work is concerned with nonlinear optical switching using the nonlinear optical loop mirrors (NOLMs). A number of different types of optical loop mirrors are built, tested and implemented in the transmission systems for noise suppression and 2R regeneration. Their results show that for 2R regeneration, NOLM does improve system performance, while NILM degrades system performance due to its sensitivity to the input pulse width, and the NALM built is unstable and therefore affects system performance.

Statnote 19: non-linear regression: fitting an exponential curve to data

Non-linear relationships are common in microbiological research and often necessitate the use of the statistical techniques of non-linear regression or curve fitting. In some circumstances, the investigator may wish to fit an exponential model to the data, i.e., to test the hypothesis that a quantity Y either increases or decays exponentially with increasing X. This type of model is straight forward to fit as taking logarithms of the Y variable linearises the relationship which can then be treated by the methods of linear regression.

Data methods in optometry. Part 10: non-linear regression analysis

1. The techniques associated with regression, whether linear or non-linear, are some of the most useful statistical procedures that can be applied in clinical studies in optometry. 2. In some cases, there may be no scientific model of the relationship between X and Y that can be specified in advance and the objective may be to provide a ‘curve of best fit’ for predictive purposes. In such cases, the fitting of a general polynomial type curve may be the best approach. 3. An investigator may have a specific model in mind that relates Y to X and the data may provide a test of this hypothesis. Some of these curves can be reduced to a linear regression by transformation, e.g., the exponential and negative exponential decay curves. 4. In some circumstances, e.g., the asymptotic curve or logistic growth law, a more complex process of curve fitting involving non-linear estimation will be required.