Comparison of different numerical methods for the solution of the time-fractional reaction-diffusion equation with variable diffusion coefficient

In this work we perform a comparison of two different numerical schemes for the solution of the time-fractional diffusion equation with variable diffusion coefficient and a nonlinear source term. The two methods are the implicit numerical scheme presented in [M.L. Morgado, M. Rebelo, Numerical approximation of distributed order reaction- diffusion equations, Journal of Computational and Applied Mathematics 275 (2015) 216-227] that is adapted to our type of equation, and a colocation method where Chebyshev polynomials are used to reduce the fractional differential equation to a system of ordinary differential equations

Validation study of an automated wrist monitor, omron model HEM-608, compared with the standard methods for blood pressure measurement

OBJECTIVE - The aim of our study was to assess the profile of a wrist monitor, the Omron Model HEM-608, compared with the indirect method for blood pressure measurement. METHODS - Our study population consisted of 100 subjects, 29 being normotensive and 71 being hypertensive. Participants had their blood pressure checked 8 times with alternate techniques, 4 by the indirect method and 4 with the Omron wrist monitor. The validation criteria used to test this device were based on the internationally recognized protocols. RESULTS - Our data showed that the Omron HEM-608 reached a classification B for systolic and A for diastolic blood pressure, according to the one protocol. The mean differences between blood pressure values obtained with each of the methods were -2.3 +7.9mmHg for systolic and 0.97+5.5mmHg for diastolic blood pressure. Therefore, we considered this type of device approved according to the criteria selected. CONCLUSION - Our study leads us to conclude that this wrist monitor is not only easy to use, but also produces results very similar to those obtained by the standard indirect method.

Lagrangian methods for visualization and analysis of time-dependent vector fields

Magdeburg, Univ., Fak. für Informatik, Diss., 2013

Adolescent Drug Abuse Diagnosis (ADAD) vs. Health of Nation Outcome Scale for Children and Adolescents (HoNOSCA) in clinical outcome measurement.

BACKGROUND: The Adolescent Drug Abuse Diagnosis (ADAD) and Health of Nation Outcome Scales for Children and Adolescents (HoNOSCA) are both measures of outcome for adolescent mental health services. AIMS: To compare the ADAD with HoNOSCA; to examine their clinical usefulness. METHODS: Comparison of the ADAD and HoNOSCA outcome measures of 20 adolescents attending a psychiatric day care unit. RESULTS: ADAD change was positively correlated with HoNOSCA change. HoNOSCA assesses the clinic's day-care programme more positively than the ADAD. The ADAD detects a group for which the mean score remains unchanged whereas HoNOSCA does not. CONCLUSIONS: A good convergent validity emerges between the two assessment tools. The ADAD allows an evidence-based assessment and generally enables a better subject discrimination than HoNOSCA. HoNOSCA gives a less refined evaluation but is more economic in time and possibly more sensitive to change. Both assessment tools give useful information and enabled the Day-care Unit for Adolescents to rethink the process of care and of outcome, which benefited both the institution and the patients.

In vivo measurement of tissue oxygenation by time-resolved luminescence spectroscopy: advantageous properties of dichlorotris(1, 10-phenanthroline)-ruthenium(II) hydrate.

Measuring tissue oxygenation in vivo is of interest in fundamental biological as well as medical applications. One minimally invasive approach to assess the oxygen partial pressure in tissue (pO2) is to measure the oxygen-dependent luminescence lifetime of molecular probes. The relation between tissue pO2 and the probes' luminescence lifetime is governed by the Stern-Volmer equation. Unfortunately, virtually all oxygen-sensitive probes based on this principle induce some degree of phototoxicity. For that reason, we studied the oxygen sensitivity and phototoxicity of dichlorotris(1, 10-phenanthroline)-ruthenium(II) hydrate [Ru(Phen)] using a dedicated optical fiber-based, time-resolved spectrometer in the chicken embryo chorioallantoic membrane. We demonstrated that, after intravenous injection, Ru(Phen)'s luminescence lifetime presents an easily detectable pO2 dependence at a low drug dose (1 mg∕kg) and low fluence (120 mJ∕cm2 at 470 nm). The phototoxic threshold was found to be at 10 J∕cm2 with the same wavelength and drug dose, i.e., about two orders of magnitude larger than the fluence necessary to perform a pO2 measurement. Finally, an illustrative application of this pO2 measurement approach in a hypoxic tumor environment is presented.

Prognostic accuracy of cerebral blood flow measurement by perfusion computed tomography, at the time of emergency room admission, in acute stroke patients.

The purpose of this study was to determine the prognostic accuracy of perfusion computed tomography (CT), performed at the time of emergency room admission, in acute stroke patients. Accuracy was determined by comparison of perfusion CT with delayed magnetic resonance (MR) and by monitoring the evolution of each patient's clinical condition. Twenty-two acute stroke patients underwent perfusion CT covering four contiguous 10mm slices on admission, as well as delayed MR, performed after a median interval of 3 days after emergency room admission. Eight were treated with thrombolytic agents. Infarct size on the admission perfusion CT was compared with that on the delayed diffusion-weighted (DWI)-MR, chosen as the gold standard. Delayed magnetic resonance angiography and perfusion-weighted MR were used to detect recanalization. A potential recuperation ratio, defined as PRR = penumbra size/(penumbra size + infarct size) on the admission perfusion CT, was compared with the evolution in each patient's clinical condition, defined by the National Institutes of Health Stroke Scale (NIHSS). In the 8 cases with arterial recanalization, the size of the cerebral infarct on the delayed DWI-MR was larger than or equal to that of the infarct on the admission perfusion CT, but smaller than or equal to that of the ischemic lesion on the admission perfusion CT; and the observed improvement in the NIHSS correlated with the PRR (correlation coefficient = 0.833). In the 14 cases with persistent arterial occlusion, infarct size on the delayed DWI-MR correlated with ischemic lesion size on the admission perfusion CT (r = 0.958). In all 22 patients, the admission NIHSS correlated with the size of the ischemic area on the admission perfusion CT (r = 0.627). Based on these findings, we conclude that perfusion CT allows the accurate prediction of the final infarct size and the evaluation of clinical prognosis for acute stroke patients at the time of emergency evaluation. It may also provide information about the extent of the penumbra. Perfusion CT could therefore be a valuable tool in the early management of acute stroke patients.

Stochastic time-concentration activity models for cytotoxicity in 3D brain cell cultures.

BACKGROUND: In vitro aggregating brain cell cultures containing all types of brain cells have been shown to be useful for neurotoxicological investigations. The cultures are used for the detection of nervous system-specific effects of compounds by measuring multiple endpoints, including changes in enzyme activities. Concentration-dependent neurotoxicity is determined at several time points. METHODS: A Markov model was set up to describe the dynamics of brain cell populations exposed to potentially neurotoxic compounds. Brain cells were assumed to be either in a healthy or stressed state, with only stressed cells being susceptible to cell death. Cells may have switched between these states or died with concentration-dependent transition rates. Since cell numbers were not directly measurable, intracellular lactate dehydrogenase (LDH) activity was used as a surrogate. Assuming that changes in cell numbers are proportional to changes in intracellular LDH activity, stochastic enzyme activity models were derived. Maximum likelihood and least squares regression techniques were applied for estimation of the transition rates. Likelihood ratio tests were performed to test hypotheses about the transition rates. Simulation studies were used to investigate the performance of the transition rate estimators and to analyze the error rates of the likelihood ratio tests. The stochastic time-concentration activity model was applied to intracellular LDH activity measurements after 7 and 14 days of continuous exposure to propofol. The model describes transitions from healthy to stressed cells and from stressed cells to death. RESULTS: The model predicted that propofol would affect stressed cells more than healthy cells. Increasing propofol concentration from 10 to 100 μM reduced the mean waiting time for transition to the stressed state by 50%, from 14 to 7 days, whereas the mean duration to cellular death reduced more dramatically from 2.7 days to 6.5 hours. CONCLUSION: The proposed stochastic modeling approach can be used to discriminate between different biological hypotheses regarding the effect of a compound on the transition rates. The effects of different compounds on the transition rate estimates can be quantitatively compared. Data can be extrapolated at late measurement time points to investigate whether costs and time-consuming long-term experiments could possibly be eliminated.

Improving the accuracy of heat balance integral methods applied to thermal problems with time dependent boundary conditions

In this paper the two main drawbacks of the heat balance integral methods are examined. Firstly we investigate the choice of approximating function. For a standard polynomial form it is shown that combining the Heat Balance and Refined Integral methods to determine the power of the highest order term will either lead to the same, or more often, greatly improved accuracy on standard methods. Secondly we examine thermal problems with a time-dependent boundary condition. In doing so we develop a logarithmic approximating function. This new function allows us to model moving peaks in the temperature profile, a feature that previous heat balance methods cannot capture. If the boundary temperature varies so that at some time t & 0 it equals the far-field temperature, then standard methods predict that the temperature is everywhere at this constant value. The new method predicts the correct behaviour. It is also shown that this function provides even more accurate results, when coupled with the new CIM, than the polynomial profile. Analysis primarily focuses on a specified constant boundary temperature and is then extended to constant flux, Newton cooling and time dependent boundary conditions.

Antimalarial Drug Resistance: Surveillance and Molecular Methods for National Malaria Control Programmes

National malaria control programmes have the responsibility to develop a policy for malaria disease management based on a set of defined criteria as efficacy, side effects, costs and compliance. These will fluctuate over time and national guidelines will require periodic re-assessment and revision. Changing a drug policy is a major undertaking that can take several years before being fully operational. The standard methods on which a decision can be taken are the in vivo and the in vitro tests. The latter allow a quantitative measurement of the drug response and the assessment of several drugs at once. However, in terms of drug policy change its results might be difficult to interpret although they may be used as an early warning system for 2nd or 3rd line drugs. The new WHO 14-days in vivo test addresses mainly the problem of treatment failure and of haematological parameters changes in sick children. It gives valuable information on whether a drug still `works'. None of these methods are well suited for large-scale studies. Molecular methods based on detection of mutations in parasite molecules targeted by antimalarial drugs could be attractive tools for surveillance. However, their relationship with in vivo test results needs to be established

Adaptive filtering methods for identifying cross-frequency couplings in human EEG.

Oscillations have been increasingly recognized as a core property of neural responses that contribute to spontaneous, induced, and evoked activities within and between individual neurons and neural ensembles. They are considered as a prominent mechanism for information processing within and communication between brain areas. More recently, it has been proposed that interactions between periodic components at different frequencies, known as cross-frequency couplings, may support the integration of neuronal oscillations at different temporal and spatial scales. The present study details methods based on an adaptive frequency tracking approach that improve the quantification and statistical analysis of oscillatory components and cross-frequency couplings. This approach allows for time-varying instantaneous frequency, which is particularly important when measuring phase interactions between components. We compared this adaptive approach to traditional band-pass filters in their measurement of phase-amplitude and phase-phase cross-frequency couplings. Evaluations were performed with synthetic signals and EEG data recorded from healthy humans performing an illusory contour discrimination task. First, the synthetic signals in conjunction with Monte Carlo simulations highlighted two desirable features of the proposed algorithm vs. classical filter-bank approaches: resilience to broad-band noise and oscillatory interference. Second, the analyses with real EEG signals revealed statistically more robust effects (i.e. improved sensitivity) when using an adaptive frequency tracking framework, particularly when identifying phase-amplitude couplings. This was further confirmed after generating surrogate signals from the real EEG data. Adaptive frequency tracking appears to improve the measurements of cross-frequency couplings through precise extraction of neuronal oscillations.

Effects of MRI scan acceleration on brain volume measurement consistency.

PURPOSE: To evaluate the effects of recent advances in magnetic resonance imaging (MRI) radiofrequency (RF) coil and parallel imaging technology on brain volume measurement consistency. MATERIALS AND METHODS: In all, 103 whole-brain MRI volumes were acquired at a clinical 3T MRI, equipped with a 12- and 32-channel head coil, using the T1-weighted protocol as employed in the Alzheimer's Disease Neuroimaging Initiative study with parallel imaging accelerations ranging from 1 to 5. An experienced reader performed qualitative ratings of the images. For quantitative analysis, differences in composite width (CW, a measure of image similarity) and boundary shift integral (BSI, a measure of whole-brain atrophy) were calculated. RESULTS: Intra- and intersession comparisons of CW and BSI measures from scans with equal acceleration demonstrated excellent scan-rescan accuracy, even at the highest acceleration applied. Pairs-of-scans acquired with different accelerations exhibited poor scan-rescan consistency only when differences in the acceleration factor were maximized. A change in the coil hardware between compared scans was found to bias the BSI measure. CONCLUSION: The most important findings are that the accelerated acquisitions appear to be compatible with the assessment of high-quality quantitative information and that for highest scan-rescan accuracy in serial scans the acquisition protocol should be kept as consistent as possible over time. J. Magn. Reson. Imaging 2012;36:1234-1240. ©2012 Wiley Periodicals, Inc.

Evaluation of two immunoassays for the measurement of human chorionic gonadotropin in urine for anti-doping purposes.

Background: Urinary human chorionic gonadotropin (hCG) concentration is routinely measured in all anti-doping laboratories to exclude the misuse of recombinant or urinary hCG preparations. In this study, extended validation of two commercial immunoassays for hCG measurements in urine was performed. Both tests were initially designed for hCG determination in human serum/plasma. Methods: Access (R) and Elecsys (R) 1010 are two automated immunoanalysers for central laboratories. The limits of detection and quantification, as well as intra-laboratory and inter-technique correlation, precision, and accuracy, were determined. Stability studies of hCG in urine following freezing and thawing cycles (n = 3) as well as storage conditions at room temperature, 4 degrees C and 20 degrees C, were performed. Results: Statistical evaluation of hCG concentrations in male urine samples (n = 2429) measured with the Elecsys (R) 1010 system enabled us to draw a skewed frequency histogram and establish a far outside value equal to 2.3 IU/L. This decision limit corresponds to the concentration at which a sportsman will be considered positive for hCG. Intra-assay precision for the Access (R) analyser was less than 4.0 A, whereas the inter-assay precision was closer to 4.5 % (concentrations of the official external controls contained between 5.5 and 195.0 IU/L). Intra and inter-assay precision for the Elecsys (R) 1010 analyser was slightly better. A good inter-technique correlation was obtained when measuring various urine samples (male and female). No urinary hCG loss was observed after two freeze/thaw cycles. On the other hand, time and inappropriate storage conditions, such as temperatures above 10 degrees C for more than 5 days, can deteriorate urinary hCG. Conclusions: Both analysers showed acceptable performances and are suitable for screening urine for anti-doping analyses. Each laboratory should validate and establish its own reference values because hCG concentrations measured in urine can be different from one immunoassay to another. The time delay between urine collection and analysis should be reduced as much as possible, and urine samples should be transported in optimal conditions to avoid a loss of hCG immunoreactivity.

Therapeutic drug monitoring of imatinib: Bayesian and alternative methods to predict trough levels

Background: The imatinib trough plasma concentration (C(min)) correlates with clinical response in cancer patients. Therapeutic drug monitoring (TDM) of plasma C(min) is therefore suggested. In practice, however, blood sampling for TDM is often not performed at trough. The corresponding measurement is thus only remotely informative about C(min) exposure. Objectives: The objectives of this study were to improve the interpretation of randomly measured concentrations by using a Bayesian approach for the prediction of C(min), incorporating correlation between pharmacokinetic parameters, and to compare the predictive performance of this method with alternative approaches, by comparing predictions with actual measured trough levels, and with predictions obtained by a reference method, respectively. Methods: A Bayesian maximum a posteriori (MAP) estimation method accounting for correlation (MAP-ρ) between pharmacokinetic parameters was developed on the basis of a population pharmacokinetic model, which was validated on external data. Thirty-one paired random and trough levels, observed in gastrointestinal stromal tumour patients, were then used for the evaluation of the Bayesian MAP-ρ method: individual C(min) predictions, derived from single random observations, were compared with actual measured trough levels for assessment of predictive performance (accuracy and precision). The method was also compared with alternative approaches: classical Bayesian MAP estimation assuming uncorrelated pharmacokinetic parameters, linear extrapolation along the typical elimination constant of imatinib, and non-linear mixed-effects modelling (NONMEM) first-order conditional estimation (FOCE) with interaction. Predictions of all methods were finally compared with 'best-possible' predictions obtained by a reference method (NONMEM FOCE, using both random and trough observations for individual C(min) prediction). Results: The developed Bayesian MAP-ρ method accounting for correlation between pharmacokinetic parameters allowed non-biased prediction of imatinib C(min) with a precision of ±30.7%. This predictive performance was similar for the alternative methods that were applied. The range of relative prediction errors was, however, smallest for the Bayesian MAP-ρ method and largest for the linear extrapolation method. When compared with the reference method, predictive performance was comparable for all methods. The time interval between random and trough sampling did not influence the precision of Bayesian MAP-ρ predictions. Conclusion: Clinical interpretation of randomly measured imatinib plasma concentrations can be assisted by Bayesian TDM. Classical Bayesian MAP estimation can be applied even without consideration of the correlation between pharmacokinetic parameters. Individual C(min) predictions are expected to vary less through Bayesian TDM than linear extrapolation. Bayesian TDM could be developed in the future for other targeted anticancer drugs and for the prediction of other pharmacokinetic parameters that have been correlated with clinical outcomes.

Assessing the Relationship between the Baseline Value of a Continuous Variable and Subsequent Change over Time

Analyzing the relationship between the baseline value and subsequent change of a continuous variable is a frequent matter of inquiry in cohort studies. These analyses are surprisingly complex, particularly if only two waves of data are available. It is unclear for non-biostatisticians where the complexity of this analysis lies and which statistical method is adequate.With the help of simulated longitudinal data of body mass index in children,we review statistical methods for the analysis of the association between the baseline value and subsequent change, assuming linear growth with time. Key issues in such analyses are mathematical coupling, measurement error, variability of change between individuals, and regression to the mean. Ideally, it is better to rely on multiple repeated measurements at different times and a linear random effects model is a standard approach if more than two waves of data are available. If only two waves of data are available, our simulations show that Blomqvist's method - which consists in adjusting for measurement error variance the estimated regression coefficient of observed change on baseline value - provides accurate estimates. The adequacy of the methods to assess the relationship between the baseline value and subsequent change depends on the number of data waves, the availability of information on measurement error, and the variability of change between individuals.

Moderating effects of management control systems and innovation on performance. Simple methods for correcting the effects of measurement error for interaction effects in small samples

In the accounting literature, interaction or moderating effects are usually assessed by means of OLS regression and summated rating scales are constructed to reduce measurement error bias. Structural equation models and two-stage least squares regression could be used to completely eliminate this bias, but large samples are needed. Partial Least Squares are appropriate for small samples but do not correct measurement error bias. In this article, disattenuated regression is discussed as a small sample alternative and is illustrated on data of Bisbe and Otley (in press) that examine the interaction effect of innovation and style of use of budgets on performance. Sizeable differences emerge between OLS and disattenuated regression