The Experts below are selected from a list of 146853 Experts worldwide ranked by ideXlab platform

Neima Brauner - One of the best experts on this subject based on the ideXlab platform.

  • the srov Program for data analysis and Regression model identification
    Computers & Chemical Engineering, 2003
    Co-Authors: Mordechai Shacham, Neima Brauner
    Abstract:

    Abstract A new stepwise Regression Program (SROV) for the construction of optimal (stable and of highest possible accuracy) Regression models comprised of linear combination of independent variables and their non-linear functions is described. The Program uses for Regression QR decomposition based on Gram–Schmidth orthogonalization, which is highly resilient to numerical error propagation. Variables are selected to enter the Regression model according to their level of correlation with the dependent variable and they are removed from further consideration when their residual information gets below the noise level. The use of this Program is demonstrated in two examples. In both examples the Program identifies an optimal and stable Regression model and several sub-optimal models. The existence of sub-optimal models provides additional insight regarding the relationships that exist between the explanatory variables, between the explanatory variables and the dependent variable and information on model related uncertainties caused by sample size and experimental error.

Erik R Christensen - One of the best experts on this subject based on the ideXlab platform.

  • dose response Regressions for algal growth and similar continuous endpoints calculation of effective concentrations
    Environmental Toxicology and Chemistry, 2009
    Co-Authors: Erik R Christensen, Kresten Ole Kusk, Niels Nyholm
    Abstract:

    We derive equations for the effective concentration giving 10% inhibition (EC10) with 95% confidence limits for probit (log-normal), Weibull, and logistic dose-response models on the basis of experimentally derived median effective concentrations (EC50s) and the curve slope at the central point (50% inhibition). For illustration, data from closed, freshwater algal assays are analyzed using the green algaPseudokirchneriella subcapitata with growth rate as the response parameter. Dose-response Regressions for four test chemicals (tetraethylammonium bromide, musculamine, benzonitrile, and 4-4-(trifluoromethyl)phenoxy-phenol) with ranges of representative slopes at 50% response (0.54-2.62) and EC50s (2.20-357 mg/L) were selected. Reference EC50s and EC10s with 95% confidence limits using probit or Weibull models are calculated by nonlinear Regression on the whole dataset using a dose-response Regression Program with variance weighting and proper inverse estimation. The Weibull model provides the best fit to the data for all four chemicals. Predicted EC10s (95% confidence limits) from our derived equations are quite accurate; for example, with 4-4-(trifluoromethyl)phenoxy-phenol and the probit model, we obtain 1.40 (1.22-1.61) mg/L versus 1.40 (1.20- 1.64) mg/L obtained from the nonlinear Regression Program. The main advantage of the approach is that EC10 or ECx (where x 1-99) can be predicted from well-determined responses around EC20 to EC80 without experimental data in the low- or high- response range. Problems with the estimation of confidence interval for EClow,x (concentration predicted to cause x% inhibition) from algal growth inhibition also are addressed. Large confidence intervals may be the result of experimental error and lack of a well-defined reference response value. Keywords—Toxicity Pseudokirchneriella subcapitata Dose-response function Effective concentration

Sarah A Spinler - One of the best experts on this subject based on the ideXlab platform.

  • is the volume of distribution of digoxin reduced in patients with renal dysfunction determining digoxin pharmacokinetics by fluorescence polarization immunoassay
    Pharmacotherapy, 1997
    Co-Authors: Judy W M Cheng, Scott L Charland, Leslie M Shaw, S Kobrin, Stanley Goldfarb, Edward J Stanek, Sarah A Spinler
    Abstract:

    STUDY OBJECTIVE To determine digoxin pharmacokinetics in subjects with different degrees of renal function using fluorescence polarization immunoassay (FPIA), which is associated with less interference from digoxin-like immunoreactive substances (DLIS) than radioimmunoassay. SETTING University hospital clinical research center. PARTICIPANTS Eighteen subjects (mean age 44 yrs) with different degrees of renal function: group 1, creatinine clearance (Clcr) below 10 ml/minute; group 2, Clcr 10-50 ml/minute; and group 3, Clcr greater than 50 ml/minute (6 patients in each group). INTERVENTION Over 5-7 days, 15 serum samples were collected after a single intravenous dose of digoxin 7 or 10 micrograms/kg actual body weight (WT) for serum concentration measurements by FPIA. Two-compartment pharmacokinetic parameters (zero-time intercept of the concentration-time curve of the initial distribution phase [A], zero-time intercept of the concentration-time curve of the terminal elimination phase [B], initial distribution phase constant [alpha], terminal elimination rate constant [beta], volume of distribution in the central compartment [Vc] and at steady state [Vss], total body clearance [Cl], mean residence time [MRT], area under the concentration-time curve [AUC]) were determined using a nonlinear least squares Regression Program. MEASUREMENTS AND MAIN RESULTS No significant differences were found among groups for A, B, alpha, beta, beta-half-life Vc/WT, MRT, AUC, and Cl/WT. Significant differences were observed in Vss/WT (4.8 +/- 1.0, 6.6 +/- 0.5, 6.4 +/- 0.7 L/kg) between group 1 versus group 2 and group 1 versus group 3 (p < 0.01). Measured Clcr was correlated with Cl (r2 = 0.40, p < 0.01), Cl/WT (r2 = 0.29, p < 0.05), Vss (r2 = 0.35, p = 0.01), and Vss/WT (r2 = 0.24, p < 0.05). CONCLUSION This study confirmed that Vss is smaller in patients with chronic renal failure (Clcr < 10 ml/min) than those without chronic renal failure. Therefore, previous recommendations that lower digoxin loading doses should be administered in patients with renal failure are applicable to digoxin serum concentration monitoring using FPIA.

Mordechai Shacham - One of the best experts on this subject based on the ideXlab platform.

  • the srov Program for data analysis and Regression model identification
    Computers & Chemical Engineering, 2003
    Co-Authors: Mordechai Shacham, Neima Brauner
    Abstract:

    Abstract A new stepwise Regression Program (SROV) for the construction of optimal (stable and of highest possible accuracy) Regression models comprised of linear combination of independent variables and their non-linear functions is described. The Program uses for Regression QR decomposition based on Gram–Schmidth orthogonalization, which is highly resilient to numerical error propagation. Variables are selected to enter the Regression model according to their level of correlation with the dependent variable and they are removed from further consideration when their residual information gets below the noise level. The use of this Program is demonstrated in two examples. In both examples the Program identifies an optimal and stable Regression model and several sub-optimal models. The existence of sub-optimal models provides additional insight regarding the relationships that exist between the explanatory variables, between the explanatory variables and the dependent variable and information on model related uncertainties caused by sample size and experimental error.

Niels Nyholm - One of the best experts on this subject based on the ideXlab platform.

  • dose response Regressions for algal growth and similar continuous endpoints calculation of effective concentrations
    Environmental Toxicology and Chemistry, 2009
    Co-Authors: Erik R Christensen, Kresten Ole Kusk, Niels Nyholm
    Abstract:

    We derive equations for the effective concentration giving 10% inhibition (EC10) with 95% confidence limits for probit (log-normal), Weibull, and logistic dose-response models on the basis of experimentally derived median effective concentrations (EC50s) and the curve slope at the central point (50% inhibition). For illustration, data from closed, freshwater algal assays are analyzed using the green algaPseudokirchneriella subcapitata with growth rate as the response parameter. Dose-response Regressions for four test chemicals (tetraethylammonium bromide, musculamine, benzonitrile, and 4-4-(trifluoromethyl)phenoxy-phenol) with ranges of representative slopes at 50% response (0.54-2.62) and EC50s (2.20-357 mg/L) were selected. Reference EC50s and EC10s with 95% confidence limits using probit or Weibull models are calculated by nonlinear Regression on the whole dataset using a dose-response Regression Program with variance weighting and proper inverse estimation. The Weibull model provides the best fit to the data for all four chemicals. Predicted EC10s (95% confidence limits) from our derived equations are quite accurate; for example, with 4-4-(trifluoromethyl)phenoxy-phenol and the probit model, we obtain 1.40 (1.22-1.61) mg/L versus 1.40 (1.20- 1.64) mg/L obtained from the nonlinear Regression Program. The main advantage of the approach is that EC10 or ECx (where x 1-99) can be predicted from well-determined responses around EC20 to EC80 without experimental data in the low- or high- response range. Problems with the estimation of confidence interval for EClow,x (concentration predicted to cause x% inhibition) from algal growth inhibition also are addressed. Large confidence intervals may be the result of experimental error and lack of a well-defined reference response value. Keywords—Toxicity Pseudokirchneriella subcapitata Dose-response function Effective concentration