Prevalence of single-nucleotide variants in twenty-five pharmacogenes from a Cuban sample cohort.

Introduction: The Cuban population is genetically diverse, and information on the prevalence of genetic variants is still limited. As complex admixture processes have occurred, we hypothesized that the frequency of pharmacogenetic variants and drug responses may vary within the country. The aims of the study were to describe the frequency distribution of 43 single-nucleotide variants (SNVs) from 25 genes of pharmacogenetic interest within the Cuba population and in relation to other populations, while taking into consideration some descriptive variables such as place of birth and skin color.

Overview of in vitro-in vivo extrapolation approaches for the risk assessment of nanomaterial toxicity.

Nanomaterials are increasingly used in many applications due to their enhanced properties. To ensure their safety for humans and the environment, nanomaterials need to be evaluated for their potential risk. The risk assessment analysis on the nanomaterials based on animal or in vivo studies is accompanied by several concerns, including animal welfare, time and cost needed for the studies.

Maternal perceived stress and green spaces during pregnancy are associated with adult offspring gene (NR3C1 and IGF2/H19) methylation patterns in adulthood: A pilot study.

Background: Changes in NR3C1 and IGF2/H19 methylation patterns have been associated with behavioural and psychiatric outcomes. Maternal mental state has been associated with offspring NR3C1 promotor and IGF2/H19 imprinting control region (ICR) methylation patterns. However, there is a lack of prospective studies with long-term follow-up.

Modeling the positive testing rate of COVID-19 in South Africa using a semi-parametric smoother for binomial data.

Identification and isolation of COVID-19 infected persons plays a significant role in the control of COVID-19 pandemic. A country's COVID-19 positive testing rate is useful in understanding and monitoring the disease transmission and spread for the planning of intervention policy. Using publicly available data collected between March 5th, 2020 and May 31st, 2021, we proposed to estimate both the positive testing rate and its daily rate of change in South Africa with a flexible semi-parametric smoothing model for discrete data.

Development of Microbiome Biomarkers in Intervention Studies.

Aims: There has been an increased interest in studying the association between microbial communities and different diseases and in discovering microbiome biomarkers. This association is pivotal to discover such biomarkers. In this paper, we present a unified modelling approach that can be used to detect and develop microbiome biomarkers for different clinical responses of interest at different levels of the microbiome ecosystem.