A Novel Approach to Increase Glial Cell Populations in Brain Microphysiological Systems.

Brain microphysiological systems (bMPS) recapitulate human brain cellular architecture and functionality more closely than traditional monolayer cultures and have become increasingly relevant for the study of neurological function in health and disease. Existing 3D brain models vary in reflecting the relative populations of different cell types present in the human brain. Most models consist mainly of neurons, while glial cells represent a smaller portion of the cell populations. Here, by means of a chemically defined glial-enriched medium (GEM), an improved method to expand the population of astrocytes and oligodendrocytes without compromising neuronal differentiation in bMPS, is presented. An important finding is that astrocytes also change in morphology when cultured in GEM, more closely recapitulating primary culture astrocytes. GEM bMPS are electro-chemically active and show different patterns of calcium staining and flux. Synaptic vesicles and terminals observed by electron microscopy are also present. No significant changes in neuronal differentiation are observed by gene expression, however, GEM enhanced neurite outgrowth and cell migration, and differentially modulated neuronal maturation in two different cell lines. These results have the potential to significantly improve functionality of bMPS for the study of neurological diseases and drug discovery, contributing to the unmet need for safe human models.

First Organoid Intelligence (OI) workshop to form an OI community.

The brain is arguably the most powerful computation system known. It is extremely efficient in processing large amounts of information and can discern signals from noise, adapt, and filter faulty information all while running on only 20 watts of power. The human brain's processing efficiency, progressive learning, and plasticity are unmatched by any computer system. Recent advances in stem cell technology have elevated the field of cell culture to higher levels of complexity, such as the development of three-dimensional (3D) brain organoids that recapitulate human brain functionality better than traditional monolayer cell systems. Organoid Intelligence (OI) aims to harness the innate biological capabilities of brain organoids for biocomputing and synthetic intelligence by interfacing them with computer technology. With the latest strides in stem cell technology, bioengineering, and machine learning, we can explore the ability of brain organoids to compute, and store given information (input), execute a task (output), and study how this affects the structural and functional connections in the organoids themselves. Furthermore, understanding how learning generates and changes patterns of connectivity in organoids can shed light on the early stages of cognition in the human brain. Investigating and understanding these concepts is an enormous, multidisciplinary endeavor that necessitates the engagement of both the scientific community and the public. Thus, on Feb 22-24 of 2022, the Johns Hopkins University held the first Organoid Intelligence Workshop to form an OI Community and to lay out the groundwork for the establishment of OI as a new scientific discipline. The potential of OI to revolutionize computing, neurological research, and drug development was discussed, along with a vision and roadmap for its development over the coming decade.