Physiologically-Based Pharmacokinetic Model on the Oral Drug Absorption in Roux-en-Y Gastric Bypass Bariatric Patients: Amoxicillin Tablet and Suspension.

The potential of a physiologically-based pharmacokinetic (PBPK) model to predict oral amoxicillin bioavailability, by considering the physiological changes after "Roux-en-Y gastric bypass" (RYGB) surgery in bariatric patients, was evaluated. A middle-out approach for parameter estimations was undertaken using in vitro, in situ, and in vivo data. The observed versus predicted plasma concentrations and the model sensitivity of the simulated parameters of AUC0-inf and Cmax of amoxicillin (AMX) were used to confirm the reliability of the estimation. The model considers that a drug-transporter (Transp) in the initial segments of the normal intestine plays a significant role in the AMX absorption. A lower fraction absorbed (Fabs) was observed in RYGB patients (54.43% for suspension and 45.21% for tablets) compared to healthy subjects (77.48% capsule). Furthermore, the tablet formulation presented a lower dissolved fraction (Fd) and Fabs compared to the suspension formulation of AMX in RYGB patients (91.70% and 45.21% versus 99.92% and 54.43%, respectively). The AUC0-inf and Cmax were sensitive to changes in Rtintestine, PeffAMX, and Transp for both healthy and RYGB models. Additionally, AUC0-inf and Cmax were also sensitive to changes in the tlag parameter for tablet formulation in RYGB patients. The PBPK model showed a reduction in AMX bioavailability as a consequence of reduced intestinal length after RYGB surgery. Additionally, the difference in the predicted Fd and Fabs between suspension and tablet suggests that liquid formulations are preferable in postbariatric patients.

Investigating population continuity with ancient DNA under a spatially explicit simulation framework.

BACKGROUND: Recent advances in sequencing technologies have allowed for the retrieval of ancient DNA data (aDNA) from skeletal remains, providing direct genetic snapshots from diverse periods of human prehistory. Comparing samples taken in the same region but at different times, hereafter called "serial samples", may indicate whether there is continuity in the peopling history of that area or whether an immigration of a genetically different population has occurred between the two sampling times. However, the exploration of genetic relationships between serial samples generally ignores their geographical locations and the spatiotemporal dynamics of populations. Here, we present a new coalescent-based, spatially explicit modelling approach to investigate population continuity using aDNA, which includes two fundamental elements neglected in previous methods: population structure and migration. The approach also considers the extensive temporal and geographical variance that is commonly found in aDNA population samples. RESULTS: We first showed that our spatially explicit approach is more conservative than the previous (panmictic) approach and should be preferred to test for population continuity, especially when small and isolated populations are considered. We then applied our method to two mitochondrial datasets from Germany and France, both including modern and ancient lineages dating from the early Neolithic. The results clearly reject population continuity for the maternal line over the last 7500 years for the German dataset but not for the French dataset, suggesting regional heterogeneity in post-Neolithic migratory processes. CONCLUSIONS: Here, we demonstrate the benefits of using a spatially explicit method when investigating population continuity with aDNA. It constitutes an improvement over panmictic methods by considering the spatiotemporal dynamics of genetic lineages and the precise location of ancient samples. The method can be used to investigate population continuity between any pair of serial samples (ancient-ancient or ancient-modern) and to investigate more complex evolutionary scenarios. Although we based our study on mitochondrial DNA sequences, diploid molecular markers of different types (DNA, SNP, STR) can also be simulated with our approach. It thus constitutes a promising tool for the analysis of the numerous aDNA datasets being produced, including genome wide data, in humans but also in many other species.

Simulated patterns of mitochondrial diversity are consistent with partial population turnover in Bronze Age Central Europe.

OBJECTIVES: The analysis of ancient mitochondrial DNA from osteological remains has challenged previous conclusions drawn from the analysis of mitochondrial DNA from present populations, notably by revealing an absence of genetic continuity between the Neolithic and modern populations in Central Europe. Our study investigates how to reconcile these contradictions at the mitochondrial level using a modeling approach. MATERIALS AND METHODS: We used a spatially explicit computational framework to simulate ancient and modern DNA sequences under various evolutionary scenarios of post Neolithic demographic events and compared the genetic diversity of the simulated and observed mitochondrial sequences. We investigated which-if any-scenarios were able to reproduce statistics of genetic diversity similar to those observed, with a focus on the haplogroup N1a, associated with the spread of early Neolithic farmers. RESULTS: Demographic fluctuations during the Neolithic transition or subsequent demographic collapses after this period, that is, due to epidemics such as plague, are not sufficient to explain the signal of population discontinuity detected on the mitochondrial DNA in Central Europe. Only a scenario involving a substantial genetic input due to the arrival of migrants after the Neolithic transition, possibly during the Bronze Age, is compatible with observed patterns of genetic diversity. DISCUSSION: Our results corroborate paleogenomic studies, since out of the alternative hypotheses tested, the best one that was able to recover observed patterns of mitochondrial diversity in modern and ancient Central European populations was one were immigration of populations from the Pontic steppes during the Bronze Age was explicitly simulated.

Bayesian estimation of partial population continuity using ancient DNA and spatially explicit simulations.

The retrieval of ancient DNA from osteological material provides direct evidence of human genetic diversity in the past. Ancient DNA samples are often used to investigate whether there was population continuity in the settlement history of an area. Methods based on the serial coalescent algorithm have been developed to test whether the population continuity hypothesis can be statistically rejected by analysing DNA samples from the same region but of different ages. Rejection of this hypothesis is indicative of a large genetic shift, possibly due to immigration occurring between two sampling times. However, this approach is only able to reject a model of full continuity model (a total absence of genetic input from outside), but admixture between local and immigrant populations may lead to partial continuity. We have recently developed a method to test for population continuity that explicitly considers the spatial and temporal dynamics of populations. Here, we extended this approach to estimate the proportion of genetic continuity between two populations, using ancient genetic samples. We applied our original approach to the question of the Neolithic transition in Central Europe. Our results confirmed the rejection of full continuity, but our approach represents an important step forward by estimating the relative contribution of immigrant farmers and of local hunter-gatherers to the final Central European Neolithic genetic pool. Furthermore, we show that a substantial proportion of genes brought by the farmers in this region were assimilated from other hunter-gatherer populations along the way from Anatolia, which was not detectable by previous continuity tests. Our approach is also able to jointly estimate demographic parameters, as we show here by finding both low density and low migration rate for pre-Neolithic hunter-gatherers. It provides a useful tool for the analysis of the numerous ancient DNA data sets that are currently being produced for many different species.