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This study employed descriptive statistics and correlation analysis to examine the influence of stress on smartphone addiction as well as the mediating effects of self-control, neuroticism, and extraversion using 400 men and women in their 20s to 40s followed by structural equation analysis. Our findings indicate that stress had a significant influence on smartphone addiction, and self-control mediates the influence of stress on smartphone addiction. As stress increases, self-control decreases, which subsequently leads to increased smartphone addiction. Self-control was confirmed as an important factor in the prevention of smartphone addiction. Finally, among personality factors, neuroticism, and extraversion mediate the influence of stress on smartphone addiction.

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Abstract. This study investigated the effects of genetic polymorphisms in organic cation transporter (OCT) genes, such as OCT1-3, OCTN1, MATE1, and MATE2-K, on metformin pharmacokinetics. Of particular interest was the influence of genetic polymorphisms as covariates on the variability in the population pharmacokinetics (PPK) of metformin using nonlinear mixed effects modeling (NONMEM). In a retrospective data analysis, data on subjects from five independent metformin bioequivalence studies that used the same protocol were assembled and compared with 96 healthy control subjects who were administered a single oral 500 mg dose of metformin. Genetic polymorphisms of OCT2-808 G>T and OCTN1-917C>T had a significant (P<0.05) effect on metformin pharmacokinetics, yielding a higher peak concentration with a larger area under the serum time-concentration curve. The values obtained were 102± 34.5 L/h for apparent oral clearance (CL/F), 447±214 L for volume of distribution (V d /F), and 3.1±0.9 h for terminal half-life (mean±SD) by non-compartmental analysis. The NONMEM method gives similar results. The metformin serum levels were obtained by setting the one-compartment model to a first-order absorption and lag time. In the PPK model, the effects of OCT2-808 G>T and OCTN1-917C>T variants on the CL/F were significant (P<0.001 and P<0.05, respectively). Thus, genetic variants of OCTN1-917C>T, along with OCT2-808 G>T genetic polymorphisms, could be useful in titrating the optimal metformin dose.

Extrapolation of pharmacokinetic (PK) parameters from in vitro or in vivo animal to human is one of the main tasks in the drug development process. Translational approaches provide evidence for go or no-go decision-making during drug discovery and the development process, and the prediction of human PKs prior to the first-in-human clinical trials. In vitro-in vivo extrapolation and allometric scaling are the choice of method for projection to human situations. Although these methods are useful tools for the estimation of PK parameters, it is a challenge to apply these methods since underlying biochemical, mathematical, physiological, and background knowledge of PKs are required. In addition, it is difficult to select an appropriate methodology depending on the data available. Therefore, this review covers the principles of PK parameters pertaining to the clearance, volume of distribution, elimination half-life, absorption rate constant, and prediction method from the original idea to recently developed models in order to introduce optimal models for the prediction of PK parameters.

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WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT• The interindividual variability of the pharmacokinetic parameters of cilostazol is relatively large.• Cilostazol undergoes extensive hepatic metabolism via the P450 enzymes, primarily CYP3A and, to a lesser extent, CYP2C19.• Indeed, <1% of the administered dose of cilostazol is excreted unchanged in the urine. WHAT THIS STUDY ADDS• A population pharmacokinetic analysis of cilostazol was conducted to evaluate the impact of CYP3A, CYP2C19 and ABCB1 polymorphisms on cilostazol disposition in vivo.• Genetic polymorphisms of CYP3A5 and CYP2C19 explain the substantial interindividual variability in the pharmacokinetics of cilostazol.• ABCB1 genotypes do not to appear to be associated with the disposition of cilostazol. AIMSTo investigate the influence of genetic polymorphisms in the CYP3A5, CYP2C19 and ABCB1 genes on the population pharmacokinetics of cilostazol in healthy subjects. METHODSSubjects who participated in four separate cilostazol bioequivalence studies with the same protocols were included in this retrospective analysis. One hundred and four healthy Korean volunteers were orally administered a single 50-or 100-mg dose of cilostazol. We estimated the population pharmacokinetics of cilostazol using a nonlinear mixed effects modelling (NONMEM) method and explored the possible influence of genetic polymorphisms in CYP3A (CYP3A5*3), CYP2C19 (CYP2C19*2 and CYP2C19*3) and ABCB1 (C1236T, G2677T/A and C3435T) on the population pharmacokinetics of cilostazol. RESULTSA two-compartment model with a first-order absorption and lag time described the cilostazol serum concentrations well. The apparent oral clearance (CL/F) was estimated to be 12.8 l h . Absorption rate constant was estimated at 0.24 h -1 and lag time was predicted at 0.57 h. The genetic polymorphisms of CYP3A5 had a significant (P < 0.001) influence on the CL/F of cilostazol. When CYP2C19 was evaluated, a significant difference (P < 0.01) was observed among the three genotypes (extensive metabolizers, intermediate metabolizers and poor metabolizers) for the CL/F. In addition, a combination of CYP3A5 and CYP2C19 genotypes was found to be associated with a significant difference (P < 0.005) in the CL/F. When including these genotypes, the interindividual variability of the CL/F was reduced from 34.1% in the base model to 27.3% in the final model. However, no significant differences between the ABCB1 genotypes and cilostazol pharmacokinetic parameters were observed. CONCLUSIONSThe results of the present study indicate that CYP3A5 and CYP2C19 polymorphisms explain the substantial interindividual variability that occurs in the metabolism of cilostazol.

These results suggest that Gadd45beta is a key player in ischaemia/hypoxia-induced apoptotic cardiomyocyte death, and that strategies based on its inhibition might be of benefit in the treatment of acute ischaemic heart disease.