The emergence of single cell technologies provides the opportunity to characterize complex immune/central nervous system cell assemblies in multiple sclerosis (MS) and to study their cell population structures, network activation and dynamics at unprecedented depths. In this review, we summarize the current knowledge of astrocyte subpopulations in MS tissue and discuss the challenges associated with resolving astrocyte heterogeneity with single-nucleus RNA-sequencing (snRNA-seq). We further discuss multiplexed imaging techniques as tools for defining population clusters within a spatial context. Finally, we will provide an outlook on how these technologies may aid in answering unresolved questions in MS, such as the glial phenotypes that drive MS progression and/or neuropathological differences between different clinical MS subtypes.

Among the greatest general challenges in bioengineering is to mimic human physiology. Advanced efforts in tissue engineering have led to sophisticated ‘brain-on-chip’ (BoC) microfluidic devices that can mimic structural and functional aspects of brain tissue. BoC may be used to understand the biochemical pathways of neurolgical pathologies and assess promising therapeutic agents for facilitating regenerative medicine. We evaluated the potential of microfluidic BoC devices in various neurological pathologies, such as Alzheimer's, glioblastoma, traumatic brain injury, stroke and epilepsy. We also discuss the principles, limitations and future considerations of BoC technology. Results suggest that BoC models can help understand complex neurological pathologies and augment drug testing efforts for regenerative applications. However, implementing organ-on-chip technology to clinical practice has some practical limitations that warrant greater attention to improve large-scale applicability. Nevertheless, they remain to be versatile and powerful tools that can broaden our understanding of pathophysiological and therapeutic uncertainties to neurological diseases.

LIDAR (from "light detection and ranging" or "laser imaging, detection, and ranging") is an evolving threedimensional scanning technology with historical applications in various fields. However, the applicability of LIDAR in the field of medicine has mostly not been examined thus far. Here, we review the basic principles governing LIDAR and its potential to be used in three notable use cases in the context of remote patient monitoring: geriatric fall prevention, postoperative recovery monitoring, and home safety assessment. For assisting geriatric populations, LIDAR can create 3D renderings of their home environments and classify which objects may be associated with risk for falls. These risk factors can then be forwarded to both patients and providers in order for them to discuss how to make the patient's environment safer. LIDAR is also capable of mapping the range of extremity motion in patients undergoing postoperative recovery. Such LIDAR data is simple to acquire and record for these patients and could enable unique metrics to be developed to assess patient outcomes in postoperative recovery. Finally, LIDAR can also reproduce 3D home models to identify attributes of their environments that could be harmful to infants. Given the recent momentum in telehealth following the events of the coronavirus 2019 disease (COVID-19) pandemic, LIDAR may also be a powerful tool in driving new insights from quality improvement initiatives through remote patient monitoring.