GP5+/6+ SYBR Green methodology for simultaneous screening and quantification of human papillomavirus

Background: Detection and quantification of human papillomavirus (HPV) may help in predicting the evolution of HPV infection and progression of associated lesions. Objectives: We propose a novel protocol using consensus primers GP5+/6+ in a SYBR Green quantitative real-time (Q-RT) polymerase chain reaction (PCR). The strategy permits screening for HPV infection and viral load quantification simultaneously. Study design: DNA from 153 archived cervical samples, previously tested for HPV detection by GP5+/6+ PCR and typed by EIA-RLB (enzyme immunoassay-reverse line blot) or sequence analysis, was analysed using SYBR Green Q-RT PCR. Melting temperature assay (T(m)) and cycle threshold (C(t)) were used to evaluate HPV positivity and viral load. The T(m) in the range of 77-82 degrees C was considered to be positive for HPV-DNA. HPV results generated through GP5+/6+ conventional PCR were considered the gold standard against which sensitivity and specificity of our assay were measured. Results: Out of 104 HPV positive samples, 100 (96.2%) were also determined as positive by SYBR Green Q-RT PCR; of the 49 HPV-negative samples, all were determined as negative. There was an excellent positivity agreement (K = 0.94) between the SYBR Green Q-RT and the previous methods employed. The specificity and sensitivity were 100% and 96.2%, respectively. Comparison of SYBR Green Q-RT and TaqMan oligo-probe technologies gave an excellent concordance (pc = 0.95) which validated the proposed strategy. Conclusions: We propose a sensitive and easy-to-perform technique for HPV screening and viral load quantification simultaneously. (C) 2009 Elsevier B.V. All rights reserved.

The composite Euler method for stiff stochastic differential equations

In this paper we present the composite Euler method for the strong solution of stochastic differential equations driven by d-dimensional Wiener processes. This method is a combination of the semi-implicit Euler method and the implicit Euler method. At each step either the semi-implicit Euler method or the implicit Euler method is used in order to obtain better stability properties. We give criteria for selecting the semi-implicit Euler method or the implicit Euler method. For the linear test equation, the convergence properties of the composite Euler method depend on the criteria for selecting the methods. Numerical results suggest that the convergence properties of the composite Euler method applied to nonlinear SDEs is the same as those applied to linear equations. The stability properties of the composite Euler method are shown to be far superior to those of the Euler methods, and numerical results show that the composite Euler method is a very promising method. (C) 2001 Elsevier Science B.V. All rights reserved.

A flux ratio theorem for multicomponent linear diffusion equations

Ussing [1] considered the steady flux of a single chemical component diffusing through a membrane under the influence of chemical potentials and derived from his linear model, an expression for the ratio of this flux and that of the complementary experiment in which the boundary conditions were interchanged. Here, an extension of Ussing's flux ratio theorem is obtained for n chemically interacting components governed by a linear system of diffusion-migration equations that may also incorporate linear temporary trapping reactions. The determinants of the output flux matrices for complementary experiments are shown to satisfy an Ussing flux ratio formula for steady state conditions of the same form as for the well-known one-component case. (C) 2000 Elsevier Science Ltd. All rights reserved.

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.

Three-point boundary value problems for second-order, ordinary, differential equations

We establish existence results for solutions to three-point boundary value problems for nonlinear, second-order, ordinary differential equations with nonlinear boundary conditions. (C) 2001 Elsevier Science Ltd. All rights reserved.

Stiffly accurate Runge-Kutta methods for stiff stochastic differential equations

In this paper we discuss implicit methods based on stiffly accurate Runge-Kutta methods and splitting techniques for solving Stratonovich stochastic differential equations (SDEs). Two splitting techniques: the balanced splitting technique and the deterministic splitting technique, are used in this paper. We construct a two-stage implicit Runge-Kutta method with strong order 1.0 which is corrected twice and no update is needed. The stability properties and numerical results show that this approach is suitable for solving stiff SDEs. (C) 2001 Elsevier Science B.V. All rights reserved.

A new wavelet-based method for the solution of the population balance equation

A new wavelet-based method for solving population balance equations with simultaneous nucleation, growth and agglomeration is proposed, which uses wavelets to express the functions. The technique is very general, powerful and overcomes the crucial problems of numerical diffusion and stability that often characterize previous techniques in this area. It is also applicable to an arbitrary grid to control resolution and computational efficiency. The proposed technique has been tested for pure agglomeration, simultaneous nucleation and growth, and simultaneous growth and agglomeration. In all cases, the predicted and analytical particle size distributions are in excellent agreement. The presence of moving sharp fronts can be addressed without the prior investigation of the characteristics of the processes. (C) 2001 Published by Elsevier Science Ltd.

Simultaneous administration of a cocktail of markers to measure renal drug elimination pathways: absence of a pharmacokinetic interaction between fluconazole and sinistrin, p-aminohippuric acid and pindolol

Aims Previous studies suggest that estimated creatinine clearance, the conventional measure of renal function, does not adequately reflect charges in renal drug handling in some patients, including the immunosuppressed. The aim of this study was to develop and validate a cocktail of markers. to be given in a single administration, capable of detecting alterations in the renal elimination pathways of glomerular filtration, tubular secretion and tubular reabsorption. Methods Healthy male subjects (n = 12) received intravenously infused 2500 mg sinistrin (glomerular filtration) and 440 mg p-aminohippuric acid (PAH; anion secretion), and orally administered 100 mg fluconazole (reabsorption) and 15 mg rac-pindolol (cation secretion). The potential interaction between these markers was investigated in a pharmacokinetic study where markers (M) or fluconazole (F) were administered alone or together (M + F). Validated analytical methods were used to measure plasma and urine concentrations in order to quantify the renal handling of each marker. Plasma protein binding of fluconazole was measured by ultrafiltration. All subjects had an estimated creatinine clearance within the normal range. The renal clearance of each marker (Mean +/- s.d.) was calculated as the ratio of the amount excreted in urine and thearea-under-the-concentration-time curve. Statistical comparisons were made using a paired t-test and 95% confidence intervals were reported. Results The renal clearances of sinistrin (M: 119 +/- 31 ml min(-1); M + F: 130 +/- 40 ml min(-1); P = 0.32), PAH (M: 469 +/- 145 ml min(-1); M + F: 467 +/- 146 ml min(-1); P = 0.95), R-pindolol (M: 204 +/- 41 ml min(-1); M + F: 190 +/- 41 ml min(-1); P = 0.39; n = 11), S-pindolol (M: 225 +/- 55 ml min(-1); M + F: 209 +/- 60 ml min(-1); P = 0.27; n = 11) and fluconazole (F: 14.9 +/-3.8 ml min(-1); M + F: 13.6 +/- 3.4 ml min(-1); P = 0.16) were similar when the markers or fluconazole were administered alone (M or F) or as a cocktail (M + F). Conclusions This study found no interaction between markers and fluconazole in healthy male subjects, suggesting that a single administration of this cocktail of markers of different renal processes call be used to simultaneously investigate pathways of renal drug elimination.

Brief note on the variation of constants formula for fuzzy differential equations

This note gives a theory of state transition matrices for linear systems of fuzzy differential equations. This is used to give a fuzzy version of the classical variation of constants formula. A simple example of a time-independent control system is used to illustrate the methods. While similar problems to the crisp case arise for time-dependent systems, in time-independent cases the calculations are elementary solutions of eigenvalue-eigenvector problems. In particular, for nonnegative or nonpositive matrices, the problems at each level set, can easily be solved in MATLAB to give the level sets of the fuzzy solution. (C) 2002 Elsevier Science B.V. All rights reserved.

Theory and applications of fuzzy Volterra integral equations

Formulations of fuzzy integral equations in terms of the Aumann integral do not reflect the behavior of corresponding crisp models. Consequently, they are ill-adapted to describe physical phenomena, even when vagueness and uncertainty are present. A similar situation for fuzzy ODEs has been obviated by interpretation in terms of families of differential inclusions. The paper extends this formalism to fuzzy integral equations and shows that the resulting solution sets and attainability sets are fuzzy and far better descriptions of uncertain models involving integral equations. The investigation is restricted to Volterra type equations with mildly restrictive conditions, but the methods are capable of extensive generalization to other types and more general assumptions. The results are illustrated by integral equations relating to control models with fuzzy uncertainties.