17 research outputs found
Clinical characteristics of the subjects for the analyses regarding the risk of NAFLD.
<p>The data are the means ± standard deviation, median (range) for skewed variables, or the numbers of subjects (%) for categorical variables.</p><p><sup>a</sup> Fisher’s exact test.</p><p><sup>b</sup> Mann–Whitney U test (otherwise, Student’s t-test was used).</p><p>NAFLD, non-alcoholic fatty liver disease; BMI, body mass index; BP, blood pressure; eGFR, estimated glomerular filtration rate; LDL-C, low-density lipoprotein cholesterol; HDL-C, high-density lipoprotein cholesterol; TG, triglyceride; AST, aspartate aminotransferase; ALT, alanine aminotransferase; GGT, gamma-glutamyl transferase; PNPLA3, patatin-like phospholipase 3.</p><p>Clinical characteristics of the subjects for the analyses regarding the risk of NAFLD.</p
The longitudinal changes in the prevalence of NAFLD stratified by the <i>PNPLA3</i> genotype among normal weight subjects.
<p>The prevalence of NAFLD is shown as solid, dashed-dotted and dotted lines in the subjects with the <i>PNPLA3</i> C/C, C/G and G/G genotypes, respectively. NAFLD, non-alcoholic fatty liver disease; PNPLA3, patatin-like phospholipase 3.</p
Dynamics of silver elution from functionalised antimicrobial nanofiltration membranes
In an effort to mitigate biofouling on thin film composite membranes such as nanofiltration and reverse osmosis, a myriad of different surface modification strategies has been published. The use of silver nanoparticles (Ag-NPs) has emerged as being particularly promising. Nevertheless, the stability of these surface modifications is still poorly understood, particularly under permeate flux conditions. Leaching or elution of Ag-NPs from the membrane surface can not only affect the antimicrobial characteristics of the membrane, but could also potentially present an environmental liability when applied in industrial-scale systems. This study sought to investigate the dynamics of silver elution and the bactericidal effect of an Ag-NP functionalised NF270 membrane. Inductively coupled plasma-atomic emission spectroscopy was used to show that the bulk of leached silver occurred at the start of experimental runs, and was found to be independent of salt or permeate conditions used. Cumulative amounts of leached silver did, however, stabilise following the initial release, and were shown to have maintained the biocidal characteristics of the modified membrane, as observed by a higher fraction of structurally damaged Pseudomonas fluorescens cells. These results highlight the need to comprehensively assess the time-dependent nature of bactericidal membranes
Impact of the <i>Superoxide Dismutase 2</i> Val16Ala Polymorphism on the Relationship between Valproic Acid Exposure and Elevation of γ-Glutamyltransferase in Patients with Epilepsy: A Population Pharmacokinetic-Pharmacodynamic Analysis
<div><p>Background</p><p>There has been accumulating evidence that there are associations among γ-glutamyltransferase (γ-GT) elevation and all-cause mortality, cardiovascular diseases and metabolic diseases, including nonalcoholic fatty liver disease. The primary objective of this study was to evaluate the impact of the most common and potentially functional polymorphisms of antioxidant enzyme genes, i.e. <i>superoxide dismutase 2 (SOD2)</i>, <i>glutathione S-transferase M1</i> and <i>glutathione S-transferase T1</i>, on the γ-GT elevation during valproic acid (VPA) therapy.</p><p>Methods and Findings</p><p>This retrospective study included 237 and 169 VPA-treated Japanese patients with epilepsy for population pharmacokinetic and pharmacokinetic-pharmacodynamic analyses, respectively. A nonlinear mixed-effect model represented the pharmacokinetics of VPA and the relationships between VPA exposure and γ-GT elevation. A one-compartment model of the pharmacokinetic parameters of VPA adequately described the data; while the model for the probability of the γ-GT elevation was fitted using a logistic regression model, in which the logit function of the probability was a linear function of VPA exposure. The <i>SOD2</i> Val16Ala polymorphism and complication with intellectual disability were found to be significant covariates influencing the intercept of the logit function for the probability of an elevated γ-GT level. The predicted mean percentages of the subjects with γ-GT elevation were about 2- to 3-fold, 3- to 4-fold and 4- to 8-fold greater in patients with the <i>SOD2</i> Val/Val genotype but without any intellectual disability, those with the <i>SOD2</i> Val/Ala or Ala/Ala genotype and intellectual disability and those with the <i>SOD2</i> Val/Val genotype and intellectual disability, respectively, compared to those with the <i>SOD2</i> Val/Ala or Ala/Ala genotype without intellectual disability.</p><p>Conclusion</p><p>Our results showed that the <i>SOD2</i> Val16Ala polymorphism has an impact on the relationship between VPA exposure and γ-GT elevation in patients with epilepsy. These results suggest that determining the <i>SOD2</i> genotype could be helpful for preventing the VPA-induced γ-GT elevation.</p></div
Specific examples of the optimal trough concentration of VPA for simulated patients.
<p>VPA, valproic acid; AED, antiepileptic drug; PHT, phenytoin; SCN1A, sodium channel neuronal type I alpha subunit.</p><p>Specific examples of the optimal trough concentration of VPA for simulated patients.</p
The predicted mean percentages of the subjects with γ-GT elevation and the mean odds ratios (95% CIs) for γ-GT elevation during VPA therapy according to the <i>SOD2</i> Val16Ala genotype and complication with intellectual disability when different daily doses of VPA were administered to patients without any co-treatment.
<p>γ-GT: γ-glutamyltransferase; VPA = valproic acid; Dose = daily dose of VPA; SOD2 = superoxide dismutase 2; CIs = confidence intervals; − = absent; + = present.</p><p>The predicted mean percentages of the subjects with γ-GT elevation and the mean odds ratios (95% CIs) for γ-GT elevation during VPA therapy according to the <i>SOD2</i> Val16Ala genotype and complication with intellectual disability when different daily doses of VPA were administered to patients without any co-treatment.</p
The median values of the PK parameter estimates of VPA in the final population PK models obtained using the NONMEM program and the bootstrap analysis.
<p>VPA = valproic acid; PK = pharmacokinetic; NONMEM = nonlinear mixed-effect model; CIs = confidence intervals; <i>ALAG</i> = absorption lag time; <i>Ka</i> = absorption rate constant; <i>Vd/F</i> = volume of distribution; <i>CL/F</i> = apparent oral clearance; Dose = daily dose of VPA; CBZ = carbamazepine; CLB = clobazam; GBP = gabapentine; PB = phenobarbital; PHT = phenytoin; ω = coefficient of variation of inter-individual variability; σ = coefficient of variation of intra-individual variability; – = data not available.</p><p>The median values of the PK parameter estimates of VPA in the final population PK models obtained using the NONMEM program and the bootstrap analysis.</p
The results of the visual predictive check of the population PK-PD model.
<p>The solid line represents the observed proportion with a more than 50% reduction in seizure frequency, and the solid area represents the 95% prediction interval. PK, pharmacokinetic; PD, pharmacodynamics; VPA, valproic acid.</p
A summary of the patient characteristics.
<p>PK = pharmacokinetic; PD = pharmacodynamic; N = number; SD = standard deviation; VPA = valproic acid; γ-GT: γ-glutamyltransferase; ALT: alanine aminotransferase; AST: aspartate aminotransferase; BUN = blood urea nitrogen; CBZ = carbamazepine; CLB = clobazam; GBP = gabapentine; PB = phenobarbital; PHT = phenytoin; TPM = topiramate; ZNS = zonisamide.</p><p>A summary of the patient characteristics.</p
The median values of the PD parameter estimates of VPA in the final population PK-PD models obtained using the NONMEM program and the bootstrap analysis.
<p>VPA = valproic acid; PD = pharmacodynamic; PK = pharmacokinetic; NONMEM = nonlinear mixed-effect model; RES = relative standard error; CIs = confidence intervals; Dose = daily dose of VPA; BASE = intercept; SLOPE = slope relating the AUC of VPA; SOD2 = superoxide dismutase 2; ω = coefficient of variation of inter-individual variability; logit (Pr) = logit function of probability of having an elevated γ-GT level.</p><p>The median values of the PD parameter estimates of VPA in the final population PK-PD models obtained using the NONMEM program and the bootstrap analysis.</p