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3D dynamic point clouds provide a natural discrete representation of real-world objects or scenes in motion, with a wide range of applications in immersive telepresence, autonomous driving, surveillance, etc . Nevertheless, dynamic point clouds are often perturbed by noise due to hardware, software or other causes. While a plethora of methods have been proposed for static point cloud denoising, few efforts are made for the denoising of dynamic point clouds, which is quite challenging due to the irregular sampling patterns both spatially and temporally. In this paper, we represent dynamic point clouds naturally on spatial-temporal graphs, and exploit the temporal consistency with respect to the underlying surface (manifold). In particular, we define a manifold-to-manifold distance and its discrete counterpart on graphs to measure the variation-based intrinsic distance between surface patches in the temporal domain, provided that graph operators are discrete counterparts of functionals on Riemannian manifolds. Then, we construct the spatial-temporal graph connectivity between corresponding surface patches based on the temporal distance and between points in adjacent patches in the spatial domain. Leveraging the initial graph representation, we formulate dynamic point cloud denoising as the joint optimization of the desired point cloud and underlying graph representation, regularized by both spatial smoothness and temporal consistency. We reformulate the optimization and present an efficient algorithm. Experimental results show that the proposed method significantly outperforms independent denoising of each frame from state-of-the-art static point cloud denoising approaches, on both Gaussian noise and simulated LiDAR noise.

Summary The specification of the hepatic identity during human liver development is strictly controlled by extrinsic signals, yet it is still not clear how cells respond to these exogenous signals by activating secretory cascades, which are extremely relevant, especially in 3D self-organizing systems. Here, we investigate how the proteins secreted by human pluripotent stem cells (hPSCs) in response to developmental exogenous signals affect the progression from endoderm to the hepatic lineage, including their competence to generate nascent hepatic organoids. By using microfluidic confined environment and stable isotope labeling with amino acids in cell culture-coupled mass spectrometry (SILAC-MS) quantitative proteomic analysis, we find high abundancy of extracellular matrix (ECM)-associated proteins. Hepatic progenitor cells either derived in microfluidics or exposed to exogenous ECM stimuli show a significantly higher potential of forming hepatic organoids that can be rapidly expanded for several passages and further differentiated into functional hepatocytes. These results prove an additional control over the efficiency of hepatic organoid formation and differentiation for downstream applications., Graphical Abstract, Highlights • Microfluidic confined environment enhances hepatic differentiation of hPSCs • SILAC-based proteomic analysis reveals high abundance of secreted ECM proteins • ECM deposition and remodeling correlate with cell-ECM receptor overexpression • Either endogenous or exogenous ECM enhances organoid formation and differentiation, Michielin et al. investigate the secretome of human pluripotent stem cells undergoing hepatic differentiation by coupling microfluidics with SILAC proteomic analysis. They reveal a role of soluble ECM protein accumulation and deposition and leverage these insights to efficiently and robustly derive hepatic organoids from hiPSCs.

Organoids have extensive therapeutic potential and are increasingly opening up new avenues within regenerative medicine. However, their clinical application is greatly limited by the lack of effective GMP-compliant systems for organoid expansion in culture. Here, we envisage that the use of extracellular matrix (ECM) hydrogels derived from decellularized tissues (DT) can provide an environment capable of directing cell growth. These gels possess the biochemical signature of tissue-specific ECM and have the potential for clinical translation. Gels from decellularized porcine small intestine (SI) mucosa/submucosa enable formation and growth of endoderm-derived human organoids, such as gastric, hepatic, pancreatic, and SI. ECM gels can be used as a tool for direct human organoid derivation, for cell growth with a stable transcriptomic signature, and for in vivo organoid delivery. The development of these ECM-derived hydrogels opens up the potential for human organoids to be used clinically., Organoid cultures have been developed from multiple tissues, opening new possibilities for regenerative medicine. Here the authors demonstrate the derivation of GMP-compliant hydrogels from decellularized porcine small intestine which support formation and growth of human gastric, liver, pancreatic and small intestinal organoids.