Physical activity is considered a promising preventive intervention to reduce the risk of developing Alzheimer’s disease (AD). However, the positive effect of therapeutic administration of physical activity has not been proven conclusively yet, likely due to confounding factors such as varying activity regimens and life or disease stages. To examine the impact of different routines of physical activity in the early disease stages, we subjected young 5xFAD and wild-type mice to 1-day (acute) and 30-day (chronic) voluntary wheel running and compared them with age-matched sedentary controls. We observed a significant increase in brain lactate levels in acutely trained 5xFAD mice relative to all other experimental groups. Subsequent brain RNA-seq analysis did not reveal major differences in transcriptomic regulation between training durations in 5xFAD mice. In contrast, acute training yielded substantial gene expression changes in wild-type animals relative to their chronically trained and sedentary counterparts. The comparison of 5xFAD and wild-type mice showed the highest transcriptional differences in the chronic and sedentary groups, whereas acute training was associated with much fewer differentially expressed genes. In conclusion, our results suggest that different training durations did not affect the global transcriptome of 3-month-old 5xFAD mice, whereas acute running seemed to induce a similar transcriptional stress state in wild-type animals as already known for 5xFAD mice.

In vitro model systems of the blood–brain barrier (BBB) play an essential role in pharmacological research, specifically during the development and preclinical evaluation of new drug candidates. Within the past decade, the trend in research and further development has moved away from models based on primary cells of animal origin towards differentiated models derived from human induced pluripotent stem cells (hiPSs). However, this logical progression towards human model systems from renewable cell sources opens up questions about the transferability of results generated in the primary cell models. In this study, we have evaluated both models with identical experimental parameters and achieved a directly comparable characterisation showing no significant differences in protein expression or permeability even though the achieved transendothelial electrical resistance (TEER) values showed significant differences. In the course of this investigation, we also determined a significant deviation of both model systems from the in vivo BBB circumstances, specifically concerning the presence or absence of serum proteins in the culture media. Thus, we have further evaluated both systems when confronted with an in vivo-like distribution of serum and found a notable improvement in the differential permeability of hydrophilic and lipophilic compounds in the hiPS-derived BBB model. We then transferred this model into a microfluidic setup while maintaining the differential serum distribution and evaluated the permeability coefficients, which showed good comparability with values in the literature. Therefore, we have developed a microfluidic hiPS-based BBB model with characteristics comparable to the established primary cell-based model.

Static in vitro permeation experiments are commonly used to gain insights into the permeation properties of drug substances but exhibit limitations due to missing physiologic cell stimuli. Thus, fluidic systems integrating stimuli, such as physicochemical fluxes, have been developed. However, as fluidic in vitro studies display higher complexity compared to static systems, analysis of experimental readouts is challenging. Here, the integration of in silico tools holds the potential to evaluate fluidic experiments and to investigate specific simulation scenarios. This study aimed to develop in silico models that describe and predict the permeation and disposition of two model substances in a static and fluidic in vitro system. For this, in vitro permeation studies with a 16HBE cellular barrier under both static and fluidic conditions were performed over 72 h. In silico models were implemented and employed to describe and predict concentration–time profiles of caffeine and diclofenac in various experimental setups. For both substances, in silico modeling identified reduced apparent permeabilities in the fluidic compared to the static cellular setting. The developed in vitro–in silico modeling framework can be expanded further, integrating additional cell tissues in the fluidic system, and can be employed in future studies to model pharmacokinetic and pharmacodynamic drug behavior.