Isolation methods and characterization of primary rat neurovascular cells.

BACKGROUND: There is significant interest in isolating cells of the blood-brain barrier (BBB) for use in in vitro screening of therapeutics and analyzing cell specific roles in neurovascular pathology. Primary brain cells play an advantageous role in BBB models; however, isolation procedures often do not produce cells at high enough yields for experiments. In addition, although numerous reports provide primary cell isolation methods, the field is lacking in documentation and detail of expected morphological changes that occur throughout culturing and there are minimal troubleshooting resources. Here, we present simplified, robust, and reproducible methodology for isolating astrocytes, pericytes, and endothelial cells, and demonstrate several morphological benchmarks for each cell type throughout the process and culture timeframe. We also analyze common considerations for developing neurovascular cell isolation procedures and recommend solutions for troubleshooting. RESULTS: The presented methodology isolated astrocytes, pericytes, and endothelial cells and enabled cell attachment, maturation, and cell viability. We characterized milestones in cell maturation over 12 days in culture, a common timeline for applications of these cell types in BBB models. Phase contrast microscopy was used to show initial cell plating, attachment, and daily growth of isolated cells. Confocal microscopy images were analyzed to determine the identity of cell types and changes to cell morphology. Nuclear staining was also used to show the viability and proliferation of glial cells at four time points. Astrocyte branches became numerous and complex with increased culture time. Microglia, oligodendrocytes, and neurons were present in mixed glial cultures for 12 days, though the percentage of microglia and neurons expectedly decreased after passaging, with microglia demonstrating a less branched morphology. CONCLUSIONS: Neurovascular cells can be isolated through our optimized protocols that minimize cell loss and encourage the adhesion and proliferation of isolated cells. By identifying timepoints of viable glia and neurons within an astrocyte-dominant mixed culture, these cells can be used to evaluate drug targeting, uptake studies, and response to pathological stimulus in the neurovascular unit.

Applications and Considerations for Microfluidic Systems To Model the Blood-Brain Barrier.

In a myriad of developmental and degenerative brain diseases, characteristic pathological biomarkers are often associated with cerebral blood flow and vasculature. However, the relationship between vascular dysfunction and markers of brain disease is not well-defined. Additionally, it is difficult to deliver effective therapeutics to the brain due to the highly regulated blood-brain barrier (BBB) at the microvasculature interface of the brain. This Review first covers the need for modeling the BBB and the challenges of modeling the BBB. In vitro models of the BBB enable the study of the relationship between vascular dysfunction, BBB function, and disease progression and can serve as a platform to screen therapeutics. In particular, microfluidic-based in vitro BBB models are useful for studying brain vasculature as they support cell culture within the presence of continuous perfusion, which mirrors the in vivo flow and associated stress conditions in the brain. Early microfluidic models of the BBB created the most simplistic models possible that still displayed some functional aspects of the in vivo BBB. Therefore, this Review also discusses the emerging unique ways in which microfluidics in tandem with recent advancements in cell culture, biomaterials, and in vitro modeling can be used to develop more complex and physiologically relevant models of the BBB. Finally, we discuss the current and future state-of-the-art application of microfluidic BBB models for drug development and disease modeling, and the ongoing areas of needed innovation in this field.

Disintegration testing augmented by computer Vision technology.

Oral solid dosage forms, specifically immediate release tablets, are prevalent in the pharmaceutical industry. Disintegration testing is often the first step of commercialization and large-scale production of these dosage forms. Current disintegration testing in the pharmaceutical industry, according to United States Pharmacopeia (USP) chapter 〈701〉, only gives information about the duration of the tablet disintegration process. This information is subjective, variable, and prone to human error due to manual or physical data collection methods via the human eye or contact disks. To lessen the data integrity risk associated with this process, efforts have been made to automate the analysis of the disintegration process using digital lens and other imaging technologies. This would provide a non-invasive method to quantitatively determine disintegration time through computer algorithms. The main challenges associated with developing such a system involve visualization of tablet pieces through cloudy and turbid liquid. The Computer Vision for Disintegration (CVD) system has been developed to be used along with traditional pharmaceutical disintegration testing devices to monitor tablet pieces and distinguish them from the surrounding liquid. The software written for CVD utilizes data captured by cameras or other lenses then uses mobile SSD and CNN, with an OpenCV and FRCNN machine learning model, to analyze and interpret the data. This technology is capable of consistently identifying tablets with ≥ 99.6% accuracy. Not only is the data produced by CVD more reliable, but it opens the possibility of a deeper understanding of disintegration rates and mechanisms in addition to duration.