Sampling times for monitoring tacrolimus in stable adult liver transplant recipients

The aim of this study was to determine the most informative sampling time(s) providing a precise prediction of tacrolimus area under the concentration-time curve (AUC). Fifty-four concentration-time profiles of tacrolimus from 31 adult liver transplant recipients were analyzed. Each profile contained 5 tacrolimus whole-blood concentrations (predose and 1, 2, 4, and 6 or 8 hours postdose), measured using liquid chromatography-tandem mass spectrometry. The concentration at 6 hours was interpolated for each profile, and 54 values of AUC(0-6) were calculated using the trapezoidal rule. The best sampling times were then determined using limited sampling strategies and sensitivity analysis. Linear mixed-effects modeling was performed to estimate regression coefficients of equations incorporating each concentration-time point (C0, C1, C2, C4, interpolated C5, and interpolated C6) as a predictor of AUC(0-6). Predictive performance was evaluated by assessment of the mean error (ME) and root mean square error (RMSE). Limited sampling strategy (LSS) equations with C2, C4, and C5 provided similar results for prediction of AUC(0-6) (R-2 = 0.869, 0.844, and 0.832, respectively). These 3 time points were superior to C0 in the prediction of AUC. The ME was similar for all time points; the RMSE was smallest for C2, C4, and C5. The highest sensitivity index was determined to be 4.9 hours postdose at steady state, suggesting that this time point provides the most information about the AUC(0-12). The results from limited sampling strategies and sensitivity analysis supported the use of a single blood sample at 5 hours postdose as a predictor of both AUC(0-6) and AUC(0-12). A jackknife procedure was used to evaluate the predictive performance of the model, and this demonstrated that collecting a sample at 5 hours after dosing could be considered as the optimal sampling time for predicting AUC(0-6).

Quantification of lean bodyweight

Background: Lean bodyweight (LBW) has been recommended for scaling drug doses. However, the current methods for predicting LBW are inconsistent at extremes of size and could be misleading with respect to interpreting weight-based regimens. Objective: The objective of the present study was to develop a semi-mechanistic model to predict fat-free mass (FFM) from subject characteristics in a population that includes extremes of size. FFM is considered to closely approximate LBW. There are several reference methods for assessing FFM, whereas there are no reference standards for LBW. Patients and methods: A total of 373 patients (168 male, 205 female) were included in the study. These data arose from two populations. Population A (index dataset) contained anthropometric characteristics, FFM estimated by dual-energy x-ray absorptiometry (DXA - a reference method) and bioelectrical impedance analysis (BIA) data. Population B (test dataset) contained the same anthropometric measures and FFM data as population A, but excluded BIA data. The patients in population A had a wide range of age (18-82 years), bodyweight (40.7-216.5kg) and BMI values (17.1-69.9 kg/m(2)). Patients in population B had BMI values of 18.7-38.4 kg/m(2). A two-stage semi-mechanistic model to predict FFM was developed from the demographics from population A. For stage 1 a model was developed to predict impedance and for stage 2 a model that incorporated predicted impedance was used to predict FFM. These two models were combined to provide an overall model to predict FFM from patient characteristics. The developed model for FFM was externally evaluated by predicting into population B. Results: The semi-mechanistic model to predict impedance incorporated sex, height and bodyweight. The developed model provides a good predictor of impedance for both males and females (r(2) = 0.78, mean error [ME] = 2.30 x 10(-3), root mean square error [RMSE] = 51.56 [approximately 10% of mean]). The final model for FFM incorporated sex, height and bodyweight. The developed model for FFM provided good predictive performance for both males and females (r(2) = 0.93, ME = -0.77, RMSE = 3.33 [approximately 6% of mean]). In addition, the model accurately predicted the FFM of subjects in population B (r(2) = 0.85, ME -0.04, RMSE = 4.39 [approximately 7% of mean]). Conclusions: A semi-mechanistic model has been developed to predict FFM (and therefore LBW) from easily accessible patient characteristics. This model has been prospectively evaluated and shown to have good predictive performance.

Predicting residue-wise contact orders in proteins by support vector regression

Background: The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. Results: We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. Conclusion: The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

Evaluation of various pre-treatments for the dehydration of banana and selection of suitable drying models

The thin-layer drying behaviour of bananas in a beat pump dehumidifier dryer was examined. Four pre-treatments (blanching, chilling, freezing and combined blanching and freezing) were applied to the bananas, which were dried at 50 degreesC with an air velocity of 3.1 m s(-1) and with the relative humidity of the inlet air of 10-35%. Three drying models, the simple model, the two-term exponential model and the Page model were examined. All models were evaluated using three statistical measures, correlation coefficient, root means square error, and mean absolute percent error. Moisture diffusivity was calculated based on the diffusion equation for an infinite cylindrical shape using the slope method. The rate of drying was higher for the pre-treatments involving freezing. The sample which was blanched only did not show any improvement in drying rate. In fact, a longer drying time resulted due to water absorption during blanching. There was no change in the rate for the chilled sample compared with the control. While all models closely fitted the drying data, the simple model showed greatest deviation from the experimental results. The two-term exponential model was found to be the best model for describing the drying curves of bananas because its parameters represent better the physical characteristics of the drying process. Moisture diffusivities of bananas were in the range 4.3-13.2 x 10(-10) m(2)s(-1). (C) 2002 Published by Elsevier Science Ltd.

An electromyographic analysis of the deep cervical flexor muscles in performance of craniocervical flexion

Background and Purpose. This study evaluated an electromyographic technique for the measurement of muscle activity of the deep cervical flexor (DCF) muscles. Electromyographic signals were detected from the DCF, sternocleidomastoid (SCM), and anterior scalene (AS) muscles during performance of the craniocervical flexion (CCF) test, which involves performing 5 stages of increasing craniocervical flexion range of motion-the anatomical action of the DCF muscles. Subjects. Ten volunteers without known pathology or impairment participated in this study. Methods. Root-mean-square (RMS) values were calculated for the DCF, SCM, and AS muscles during performance of the CCF test. Myoelectric signals were recorded from the DCF muscles using bipolar electrodes placed over the posterior oropharyngeal wall. Reliability estimates of normalized RMS values were obtained by evaluating intraclass correlation coefficients and the normalized standard error of the mean (SEM). Results. A linear relationship was evident between the amplitude of DCF muscle activity and the incremental stages of the CCF test (F=239.04, df=36, P<.0001). Normalized SEMs in the range 6.7% to 10.3% were obtained for the normalized RMS values for the DCF muscles, providing evidence of reliability for these variables. Discussion and Conclusion. This approach for obtaining a direct measure of the DCF muscles, which differs from those previously used, may be useful for the examination of these muscles in future electromyographic applications.

Mean anisotropy of homogeneous Gaussian random fields and anisotropic norms of linear translation-invariant operators on multidimensional integer lattices

Sensitivity of output of a linear operator to its input can be quantified in various ways. In Control Theory, the input is usually interpreted as disturbance and the output is to be minimized in some sense. In stochastic worst-case design settings, the disturbance is considered random with imprecisely known probability distribution. The prior set of probability measures can be chosen so as to quantify how far the disturbance deviates from the white-noise hypothesis of Linear Quadratic Gaussian control. Such deviation can be measured by the minimal Kullback-Leibler informational divergence from the Gaussian distributions with zero mean and scalar covariance matrices. The resulting anisotropy functional is defined for finite power random vectors. Originally, anisotropy was introduced for directionally generic random vectors as the relative entropy of the normalized vector with respect to the uniform distribution on the unit sphere. The associated a-anisotropic norm of a matrix is then its maximum root mean square or average energy gain with respect to finite power or directionally generic inputs whose anisotropy is bounded above by a≥0. We give a systematic comparison of the anisotropy functionals and the associated norms. These are considered for unboundedly growing fragments of homogeneous Gaussian random fields on multidimensional integer lattice to yield mean anisotropy. Correspondingly, the anisotropic norms of finite matrices are extended to bounded linear translation invariant operators over such fields.

High-resolution bulk density images, using calibrated X-ray radiography of impregnated soil slices

Bulk density of undisturbed soil samples can be measured using computed tomography (CT) techniques with a spatial resolution of about 1 mm. However, this technique may not be readily accessible. On the other hand, x-ray radiographs have only been considered as qualitative images to describe morphological features. A calibration procedure was set up to generate two-dimensional, high-resolution bulk density images from x-ray radiographs made with a conventional x-ray diffraction apparatus. Test bricks were made to assess the accuracy of the method. Slices of impregnated soil samples were made using hardsetting seedbeds that had been gamma scanned at 5-mm depth increments in a previous study. The calibration procedure involved three stages: (i) calibration of the image grey levels in terms of glass thickness using a staircase made from glass cover slips, (ii) measurement of ratio between the soil and resin mass attenuation coefficients and the glass mass attenuation coefficient, using compacted bricks of known thickness and bulk density, and (iii) image correction accounting for the heterogeneity of the irradiation field. The procedure was simple, rapid, and the equipment was easily accessible. The accuracy of the bulk density determination was good (mean relative error 0.015), The bulk density images showed a good spatial resolution, so that many structural details could be observed. The depth functions were consistent with both the global shrinkage and the gamma probe data previously obtained. The suggested method would be easily applied to the new fuzzy set approach of soil structure, which requires generation of bulk density images. Also, it would be an invaluable tool for studies requiring high-resolution bulk density measurement, such as studies on soil surface crusts.

Hepatic disposition and metabolite kinetics of a homologous series of diflunisal esters

The hepatic disposition and metabolite kinetics of a homologous series of diflunisal O-acyl esters (acetyl, butanoyl, pentanoyl, anti hexanoyl) were determined using a single-pass perfused in situ rat liver preparation. The experiments were conducted using 2% BSA Krebs-Henseleit buffer (pH 7.4), and perfusions were performed at 30 mL/min in each liver. O-Acyl esters of diflunisal and pregenerated diflunisal were injected separately into the portal vein. The venous outflow samples containing the esters and metabolite diflunisal were analyzed by high performance liquid chromatography (HPLC). The normalized outflow concentration-time profiles for each parent ester and the formed metabolite, diflunisal, were analyzed using statistical moments analysis and the two-compartment dispersion model. Data (presented as mean +/- standard error for triplicate experiments) was compared using ANOVA repeated measures, significance level P < 0.05. The hepatic availability (AUC'), the fraction of the injected dose recovered in the outflowing perfusate, for O-acetyldiflunisal (C2D = 0.21 +/- 0.03) was significantly lower than the other esters (0.34-0.38). However, R-N/f(u), the removal efficiency number R-N divided by the unbound fraction in perfusate f(u), which represents the removal efficiency of unbound ester by the liver, was significantly higher for the most lipophilic ester (O-hexanoyldiflunisal, C6D = 16.50 +/- 0.22) compared to the other members of the series (9.57 to 11.17). The most lipophilic ester, C6D, had the largest permeability surface area (PS) product (94.52 +/- 38.20 mt min-l g-l liver) and tissue distribution value VT (35.62 +/- 11.33 mL g(-1) liver) in this series. The MTT of these O-acyl esters of diflunisal were not significantly different from one another. However, the metabolite diflunisal MTTs tended to increase with the increase in the parent ester lipophilicity (11.41 +/- 2.19 s for C2D to 38.63 +/- 9.81 s for C6D). The two-compartment dispersion model equations adequately described the outflow profiles for the parent esters and the metabolite diflunisal formed from the O-acyl esters of diflunisal in the liver.

The HI Parkes All Sky Survey: southern observations, calibration and robust imaging

The acquisition of HI Parkes All Shy Survey (HIPASS) southern sky data commenced at the Australia Telescope National Facility's Parkes 64-m telescope in 1997 February, and was completed in 2000 March. HIPASS is the deepest HI survey yet of the sky south of declination +2 degrees, and is sensitive to emission out to 170 h(75)(-1) Mpc. The characteristic root mean square noise in the survey images is 13.3 mJy. This paper describes the survey observations, which comprise 23 020 eight-degree scans of 9-min duration, and details the techniques used to calibrate and image the data. The processing algorithms are successfully designed to be statistically robust to the presence of interference signals, and are particular to imaging point (or nearly point) sources. Specifically, a major improvement in image quality is obtained by designing a median-gridding algorithm which uses the median estimator in place of the mean estimator.

Ischaemic preconditioning in the rat brain: a longitudinal magnetic resonance imaging (MRI) study

Ischaemic preconditioning in rats was studied using MRI. Ischaemic preconditioning was induced, using an intraluminal filament method, by 30 min middle cerebral artery occlusion (MCAO), and imaged 24 h later. The secondary insult of 100 min MCAO was induced 3 days following preconditioning and imaged 24 and 72 h later. Twenty four hours following ischaemic preconditioning most rats showed small sub-cortical hyperintense regions not seen in sham-preconditioned rats. Twenty-four hours and 72 h following the secondary insult preconditioned animals showed significantly smaller lesions (24 h = 112 +/- 31 mm(3), mean +/- standard error; 72 h = 80 +/- 35 mm(3)) which were confined to the striatum, than controls (24 h = 234 +/- 32 mm(3), p = 0.026; 72 h = 275 +/- 37 mm(3), p = 0.003). In addition during Lesion maturation from 24 to 72 h post-secondary MCAO, preconditioned rats displayed an average reduction in lesion size as measured by MRI whereas sham-preconditioned rats displayed increases in lesion size; this is the first report of such differential lesion volume evolution in cerebral ischaemic preconditioning. Copyright (C) 2001 John Wiley & Sons, Ltd.

Implicit Taylor methods for stiff stochastic differential equations

In this paper we discuss implicit Taylor methods for stiff Ito stochastic differential equations. Based on the relationship between Ito stochastic integrals and backward stochastic integrals, we introduce three implicit Taylor methods: the implicit Euler-Taylor method with strong order 0.5, the implicit Milstein-Taylor method with strong order 1.0 and the implicit Taylor method with strong order 1.5. The mean-square stability properties of the implicit Euler-Taylor and Milstein-Taylor methods are much better than those of the corresponding semi-implicit Euler and Milstein methods and these two implicit methods can be used to solve stochastic differential equations which are stiff in both the deterministic and the stochastic components. Numerical results are reported to show the convergence properties and the stability properties of these three implicit Taylor methods. The stability analysis and numerical results show that the implicit Euler-Taylor and Milstein-Taylor methods are very promising methods for stiff stochastic differential equations.

Sonographic estimation of fetal weight in macrosomic fetuses: diabetic versus non-diabetic pregnancies

The objective of this study is to compare the accuracy of sonographic estimation of fetal weight of macrosomic babies in diabetic vs non-diabetic pregnancies. Ali babies weighing 4000 g or more at birth, and who had ultrasound scans performed within one week of delivery were included in this retrospective study. Pregnancies with diabetes mellitus were compared to those without diabetes mellitus. The mean simple error (actual birthweight - estimated fetal weight); mean standardised absolute error (absolute value of simple error (g)/actual birthweight (kg)); and the percentage of estimated birthweight falling within 15% of the actual birthweight between the two groups were compared. There were 9516 deliveries during the study period. Of this total 1211 (12.7 %) babies weighed 4000 g or more. A total of 56 non-diabetic pregnancies and 19 diabetic pregnancies were compared. The average sonographic estimation of fetal weight in diabetic pregnancies was 8 % less than the actual birthweight, compared to 0.2 % in the non-diabetic group (p < 0.01). The estimated fetal weight was within 15% of the birthweight in 74 % of the diabetic pregnancies, compared to 93 % of the non-diabetic pregnancies (p < 0.05). In the diabetic group, 26.3 % of the birthweights were underestimated by more than 15 %, compared to 5.4 % in the non-diabetic group (p < 0.05). In conclusion, the prediction accuracy of fetal weight estimation using standard formulae in macrosomic fetuses is significantly worse in diabetic pregnancies compared to non-diabetic pregnancies. When sonographic fetal weight estimation is used to influence the mode of delivery for diabetic women, a more conservative cut-off needs to be considered.

Model specification tests in nonparametric stochastic regression models

In this paper, we consider testing for additivity in a class of nonparametric stochastic regression models. Two test statistics are constructed and their asymptotic distributions are established. We also conduct a small sample study for one of the test statistics through a simulated example. (C) 2002 Elsevier Science (USA).

Quadriceps concentric and eccentric exercise 1: Changes in contractile and electrical activity following eccentric and concentric exercise

The purpose of this study was to determine whether or not losses of strength or endurance following eccentric and concentric exercise are associated with reduced excitation. The effects of eccentric and concentric work on maximal voluntary isometric contraction (MVC) and surface electromyogram (EMG) of the quadriceps were studied in 10 healthy male subjects following bench-stepping for 20 min with a constant leading leg. Prior to stepping and at 0, 0.25, 0.50, 0.75, 1, 3. 24 and 48 h afterwards the subjects performed a 30 s leg extension MVC with each leg during which the isometric force and the root mean square voltage of the EMG were recorded. In the eccentrically exercised muscles (ECC), MVC0-3 (force during the first 3 s of contraction) fen immediately after the bench-stepping exercise to 88 +/- 2% (mean SE) of the pre-exercise value and remained significantly lower than the concentrically exercised muscles (p < 0.05). The muscle weakness in the ECC could not be attributed to central fatigue as surface EMG amplitude at MVC0-3 increased during the recovery period. Muscle weakness after eccentric exercise appears to be due to contractile failure, which is not associated with a reduction in excitation as assessed by surface EMG. Muscular fatigue over 30 s did not change in the two muscle groups after exercise (p = 0.79), indicating that the ECC were weaker but not more fatiguable after exercise.