Comprehensive Parent-Metabolite PBPK/PD Modeling Insights into Nicotine Replacement Therapy Strategies

Background Nicotine, the pharmacologically active substance in both tobacco and many electronic cigarette (e-cigarette) liquids, is responsible for the addiction that sustains cigarette smoking. With 8 million deaths worldwide annually, smoking remains one of the major causes of disability and premature death. However, nicotine also plays an important role in smoking cessation strategies. Objectives The aim of this study was to develop a comprehensive, whole-body, physiologically based pharmacokinetic/ pharmacodynamic (PBPK/PD) model of nicotine and its major metabolite cotinine, covering various routes of nicotine administration, and to simulate nicotine brain tissue concentrations after the use of combustible cigarettes, e-cigarettes, nicotine gums, and nicotine patches. Methods A parent–metabolite, PBPK/PD model of nicotine for a non-smoking and a smoking population was developed using 91 plasma and brain tissue concentration–time profles and 11 heart rate profles. Among others, cytochrome P450 (CYP) 2A6 and 2B6 enzymes were implemented, including kinetics for CYP2A6 poor metabolizers. Results The model is able to precisely describe and predict both nicotine plasma and brain tissue concentrations, cotinine plasma concentrations, and heart rate profles. 100% of the predicted area under the concentration–time curve (AUC) and maximum concentration (Cmax) values meet the twofold acceptance criterion with overall geometric mean fold errors of 1.12 and 1.15, respectively. The administration of combustible cigarettes, e-cigarettes, nicotine patches, and nicotine gums was successfully implemented in the model and used to identify diferences in steady-state nicotine brain tissue concentration patterns. Conclusions Our PBPK/PD model may be helpful in further investigations of nicotine dependence and smoking cessation strategies. As the model represents the frst nicotine PBPK/PD model predicting nicotine concentration and heart rate profles after the use of e-cigarettes, it could also contribute to a better understanding of the recent increase in youth e-cigarette use

Demographic and Psychological Predictors of Parent–Adolescent Communication About Sex: A Representative Statewide Analysis

Sexual communication is a principal means of transmitting sexual values, beliefs, expectations, and knowledge between parents and children. Although this area has received considerable research attention, more studies with representative samples are needed to assure that findings are reflective of populations of interest. A representative statewide sample of households with adolescents (N = 907) from a large and diverse state in the United States was employed to examine the content and extent of sexual communication between parents and their adolescents, and the influence of selected primary demographic (age and gender), socio-demographic (Hispanic ethnicity, education, and religious attendance), and psychological (self-reported comfort, knowledge, and sexual communication difficulties) factors on the number of topics discussed. More than two-thirds of the parents reported experiencing some type of sexual communication difficulty, such as developmental concerns and embarrassment. Hierarchical regression results indicated that self-reported comfort, knowledge, and sexual communication difficulties strongly predicted the number of topics discussed, beyond the effect of demographic variables. These findings reinforce the notion that sexual communication between parents and adolescents can be universally challenging, and parents of both genders, all ages, and all socio-demographic characteristics might benefit from education and support

Rule based classifier for the analysis of gene-gene and gene-environment interactions in genetic association studies

<p>Abstract</p> <p>Background</p> <p>Several methods have been presented for the analysis of complex interactions between genetic polymorphisms and/or environmental factors. Despite the available methods, there is still a need for alternative methods, because no single method will perform well in all scenarios. The aim of this work was to evaluate the performance of three selected rule based classifier algorithms, RIPPER, RIDOR and PART, for the analysis of genetic association studies.</p> <p>Methods</p> <p>Overall, 42 datasets were simulated with three different case-control models, a varying number of subjects (300, 600), SNPs (500, 1500, 3000) and noise (5%, 10%, 20%). The algorithms were applied to each of the datasets with a set of algorithm-specific settings. Results were further investigated with respect to a) the Model, b) the Rules, and c) the Attribute level. Data analysis was performed using WEKA, SAS and PERL.</p> <p>Results</p> <p>The RIPPER algorithm discovered the true case-control model at least once in >33% of the datasets. The RIDOR and PART algorithm performed poorly for model detection. The RIPPER, RIDOR and PART algorithm discovered the true case-control rules in more than 83%, 83% and 44% of the datasets, respectively. All three algorithms were able to detect the attributes utilized in the respective case-control models in most datasets.</p> <p>Conclusions</p> <p>The current analyses substantiate the utility of rule based classifiers such as RIPPER, RIDOR and PART for the detection of gene-gene/gene-environment interactions in genetic association studies. These classifiers could provide a valuable new method, complementing existing approaches, in the analysis of genetic association studies. The methods provide an advantage in being able to handle both categorical and continuous variable types. Further, because the outputs of the analyses are easy to interpret, the rule based classifier approach could quickly generate testable hypotheses for additional evaluation. Since the algorithms are computationally inexpensive, they may serve as valuable tools for preselection of attributes to be used in more complex, computationally intensive approaches. Whether used in isolation or in conjunction with other tools, rule based classifiers are an important addition to the armamentarium of tools available for analyses of complex genetic association studies.</p

Impact of a parent-child sexual communication campaign: results from a controlled efficacy trial of parents

<p>Abstract</p> <p>Background</p> <p>Prior research supports the notion that parents have the ability to influence their children's decisions regarding sexual behavior. Yet parent-based approaches to curbing teen pregnancy and STDs have been relatively unexplored. The Parents Speak Up National Campaign (PSUNC) is a multimedia campaign that attempts to fill this void by targeting parents of teens to encourage parent-child communication about waiting to have sex. The campaign follows a theoretical framework that identifies cognitions that are targeted in campaign messages and theorized to influence parent-child communication. While a previous experimental study showed PSUNC messages to be effective in increasing parent-child communication, it did not address how these effects manifest through the PSUNC theoretical framework. The current study examines the PSUNC theoretical framework by 1) estimating the impact of PSUNC on specific cognitions identified in the theoretical framework and 2) examining whether those cognitions are indeed associated with parent-child communication</p> <p>Methods</p> <p>Our study consists of a randomized efficacy trial of PSUNC messages under controlled conditions. A sample of 1,969 parents was randomly assigned to treatment (PSUNC exposure) and control (no exposure) conditions. Parents were surveyed at baseline, 4 weeks, 6 months, 12 months, and 18 months post-baseline. Linear regression procedures were used in our analyses. Outcome variables included self-efficacy to communicate with child, long-term outcome expectations that communication would be successful, and norms on appropriate age for sexual initiation. We first estimated multivariable models to test whether these cognitive variables predict parent-child communication longitudinally. Longitudinal change in each cognitive variable was then estimated as a function of treatment condition, controlling for baseline individual characteristics.</p> <p>Results</p> <p>Norms related to appropriate age for sexual initiation and outcome expectations that communication would be successful were predictive of parent-child communication among both mothers and fathers. Treatment condition mothers exhibited larger changes than control mothers in both of these cognitive variables. Fathers exhibited no exposure effects.</p> <p>Conclusions</p> <p>Results suggest that within a controlled setting, the "wait until older norm" and long-term outcome expectations were appropriate cognitions to target and the PSUNC media materials were successful in impacting them, particularly among mothers. This study highlights the importance of theoretical frameworks for parent-focused campaigns that identify appropriate behavioral precursors that are both predictive of a campaign's distal behavioral outcome and sensitive to campaign messages.</p

Pharmacogenetic considerations in the treatment of co-infections with HIV/AIDS, tuberculosis and malaria in Congolese populations of Central Africa

Background: HIV-infection, tuberculosis and malaria are the big three communicable diseases that plague sub-Saharan Africa. If these diseases occur as co-morbidities they require polypharmacy, which may lead to severe drug-drug-gene interactions and variation in adverse drug reactions, but also in treatment outcomes. Polymorphisms in genes encoding drug-metabolizing enzymes are the major cause of these variations, but such polymorphisms may support the prediction of drug efficacy and toxicity. There is little information on allele frequencies of pharmacogenetic variants of enzymes involved in the metabolism of drugs used to treat HIV-infection, TB and malaria in the Republic of Congo (ROC). The aim of this study was therefore to investigate the occurrence and allele frequencies of 32 pharmacogenetic variants localized in absorption distribution, metabolism and excretion (ADME) and non-ADME genes and to compare the frequencies with population data of Africans and non-Africans derived from the 1000 Genomes Project. Results: We found significant differences in the allele frequencies of many of the variants when comparing the findings from ROC with those of non-African populations. On the other hand, only a few variants showed significant differences in their allele frequencies when comparing ROC with other African populations. In addition, considerable differences in the allele frequencies of the pharmacogenetic variants among the African populations were observed. Conclusions: The findings contribute to the understanding of pharmacogenetic variants involved in the metabolism of drugs used to treat HIV-infection, TB and malaria in ROC and their diversity in different populations. Such knowledge helps to predict drug efficacy, toxicity and ADRs and to inform individual and population-based decisions

Comprehensive Parent-Metabolite PBPK/PD Modeling Insights into Nicotine Replacement Therapy Strategies.

BackgroundNicotine, the pharmacologically active substance in both tobacco and many electronic cigarette&nbsp;(e-cigarette) liquids, is responsible for the addiction that sustains cigarette smoking. With 8 million deaths worldwide annually, smoking remains one of the major causes of disability and premature death. However, nicotine also plays an important role in smoking cessation strategies.ObjectivesThe aim of this study was to develop a comprehensive, whole-body, physiologically based pharmacokinetic/pharmacodynamic&nbsp;(PBPK/PD) model of nicotine and its major metabolite cotinine, covering various routes of nicotine administration, and to simulate nicotine brain tissue concentrations after the use of combustible cigarettes, e-cigarettes, nicotine gums, and nicotine patches.MethodsA parent-metabolite, PBPK/PD model of nicotine for a non-smoking and a smoking population was developed using 91 plasma and brain tissue concentration-time profiles and 11 heart rate profiles. Among others, cytochrome P450&nbsp;(CYP) 2A6 and 2B6 enzymes were implemented, including kinetics for CYP2A6 poor metabolizers.ResultsThe model is able to precisely describe and predict both nicotine plasma and brain tissue concentrations, cotinine plasma concentrations, and heart rate profiles. 100% of the predicted area under the concentration-time curve&nbsp;(AUC) and maximum concentration&nbsp;(Cmax) values meet the twofold acceptance criterion with overall geometric mean fold errors of 1.12 and 1.15, respectively. The administration of combustible cigarettes, e-cigarettes, nicotine patches, and nicotine gums was successfully implemented in the model and used to identify differences in steady-state nicotine brain tissue concentration patterns.ConclusionsOur PBPK/PD model may be helpful in further investigations of nicotine dependence and smoking cessation strategies. As the model represents the first nicotine PBPK/PD&nbsp;model predicting nicotine concentration and heart rate profiles after the use of e-cigarettes, it could also contribute to a better understanding of the recent increase in youth e-cigarette use