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Summary Cerebral organoids (COs) are rapidly accelerating the rate of translational neuroscience based on their potential to model complex features of the developing human brain. Several studies have examined the electrophysiological and neural network features of COs; however, no study has comprehensively investigated the developmental trajectory of electrophysiological properties in whole-brain COs and correlated these properties with developmentally linked morphological and cellular features. Here, we profiled the neuroelectrical activities of COs over the span of 5 months with a multi-electrode array platform and observed the emergence and maturation of several electrophysiologic properties, including rapid firing rates and network bursting events. To complement these analyses, we characterized the complex molecular and cellular development that gives rise to these mature neuroelectrical properties with immunohistochemical and single-cell transcriptomic analyses. This integrated approach highlights the value of COs as an emerging model system of human brain development and neurological disease., Highlights • CO electrophysiology can be quantified with a multi-electrode array method • CO electrophysiological trajectories correlate with molecular and cellular development • The neurotrophin/TRK signaling pathway is active in COs by 5 months in culture, Cerebral organoids (COs) have a unique advantage in modeling human-specific features of early brain development. Here, we profile their neuroelectrical activities with an MEA platform over time and correlate these activities with their increasingly complex molecular and cellular features. This integrated approach highlights the value of COs as an emerging model system of human brain development and neurological disease.

Cellular reprogramming, the conversion of one cell type to another, induces global changes in gene expression involving thousands of genes, and understanding how cells globally alter their gene expression profile during reprogramming is an ongoing problem. Here we reanalyze time-course data on cellular reprogramming from differentiated cell types to induced pluripotent stem cells (iPSCs) and show that gene expression dynamics during reprogramming follow a simple 1D reaction coordinate. This reaction coordinate is independent of both the time it takes to reach the iPSC state as well as the details of the experimental protocol used. Using Monte-Carlo simulations, we show that such a reaction coordinate emerges from epigenetic landscape models where cellular reprogramming is viewed as a 'barrier-crossing' process between cell fates. Overall, our analysis and model suggest that gene expression dynamics during reprogramming follow a canonical trajectory consistent with the idea of an 'optimal path' in gene expression space for reprogramming.

Cellular reprogramming, the conversion of one cell type to another, has fundamentally transformed our conception of cell types. Cellular reprogramming induces global changes in gene expression involving hundreds of transcription factors and thousands of genes and understanding how cells globally alter their gene expression profile during reprogramming is an open problem. Here we reanalyze time-series data on cellular reprogramming from differentiated cell types to induced pluripotent stem cells (iPSCs) and show that gene expression dynamics during reprogramming follow a simple one-dimensional reaction coordinate. This reaction coordinate is independent of both the time it takes to reach the iPSC state as well as the details of experimental protocol used. Using Monte-Carlo simulations, we show that such a reaction coordinate emerges naturally from epigenetic landscape models of cell identity where cellular reprogramming is viewed as a "barrier-crossing" between the starting and ending cell fates. The model also provides gene-level insight into reprogramming dynamics and resolves a debate in the stem cell field about the different phases of reprogramming dynamics. Overall, our analysis and model suggest that gene expression dynamics during reprogramming follow a canonical trajectory consistent with the idea of an "optimal path" in gene expression space for reprogramming., 19 pages, 15 figures

Graphene nanosheets have been successfully dispersed via surfactant-assisted exfoliation of graphite using sodium cholate (SC) and sodium deoxycholate (SDC) surfactants in aqueous media. The concentration of SC and SDC surfactants and saturated graphite concentration have been well optimized to highly disperse graphene in water. The concentration of dispersed graphene in water has been estimated to be 0.52 and 2.58 mg mL−1 for SC and SDC respectively. The absence of an oxygen molecule at the centre aromatic ring of SDC offers a flat and hydrophobic surface that helps to form uniform bilayer micelles on graphitic surfaces and facilitates efficient exfoliation of graphene in a short duration of sonication. The discrepancy in the electrostatic interaction of SC-G over SDC-G dispersions and its re-aggregation stability were compared by zeta potential measurements. The thermal analysis of surfactant covered graphene powders exhibit weak bonding of surfactants with graphitic surfaces through electrostatic interactions. FESEM and AFM images demonstrate the successful exfoliation of few layer graphene with uniform dispersion. Crystalline quality and the stacking of graphene sheets in SC-G and SDC-G dispersions were analyzed using micro-Raman scattering and photoluminescence spectra.