Construction of 3D in vitro models by bioprinting human pluripotent stem cells: Challenges and opportunities

Three-dimensional (3D) printing of biological material, or 3D bioprinting, is a rapidly expanding field with interesting applications in tissue engineering and regenerative medicine. Bioprinters use cells and biocompatible materials as an ink (bioink) to build 3D structures representative of organs and tissues, in a controlled manner and with micrometric resolution. Human embryonic (hESCs) and induced (hiPSCs) pluripotent stem cells are ideally able to provide all cell types found in the human body. A limited, but growing, number of recent reports suggest that cells derived by differentiation of hESCs and hiPSCs can be used as building blocks in bioprinted human 3D models, reproducing the cellular variety and cytoarchitecture of real tissues. In this review we will illustrate these examples, which include hepatic, cardiac, vascular, corneal and cartilage tissues, and discuss challenges and opportunities of bioprinting more demanding cell types, such as neurons, obtained from human pluripotent stem cells

Neuromorphic-Based Neuroprostheses for Brain Rewiring: State-of-the-Art and Perspectives in Neuroengineering.

Neuroprostheses are neuroengineering devices that have an interface with the nervous system and supplement or substitute functionality in people with disabilities. In the collective imagination, neuroprostheses are mostly used to restore sensory or motor capabilities, but in recent years, new devices directly acting at the brain level have been proposed. In order to design the next-generation of neuroprosthetic devices for brain repair, we foresee the increasing exploitation of closed-loop systems enabled with neuromorphic elements due to their intrinsic energy efficiency, their capability to perform real-time data processing, and of mimicking neurobiological computation for an improved synergy between the technological and biological counterparts. In this manuscript, after providing definitions of key concepts, we reviewed the first exploitation of a real-time hardware neuromorphic prosthesis to restore the bidirectional communication between two neuronal populations in vitro. Starting from that 'case-study', we provide perspectives on the technological improvements for real-time interfacing and processing of neural signals and their potential usage for novel in vitro and in vivo experimental designs. The development of innovative neuroprosthetics for translational purposes is also presented and discussed. In our understanding, the pursuit of neuromorphic-based closed-loop neuroprostheses may spur the development of novel powerful technologies, such as 'brain-prostheses', capable of rewiring and/or substituting the injured nervous system

Design and Adsorption of Modular Engineered Proteins to Prepare Customized, Neuron-Compatible Coatings

Neural prosthetic implants are currently being developed for the treatment and study of both peripheral and central nervous system disorders. Effective integration of these devices upon implantation is a critical hurdle to achieving function. As a result, much attention has been directed towards the development of biocompatible coatings that prolong their in vivo lifespan. In this work, we present a novel approach to fabricate such coatings, which specifically involves the use of surface-adsorbed, nanoscale-designed protein polymers to prepare reproducible, customized surfaces. A nanoscale modular design strategy was employed to synthesize six engineered, recombinant proteins intended to mimic aspects of the extracellular matrix proteins fibronectin, laminin, and elastin as well as the cell–cell adhesive protein neural cell adhesion molecule. Physical adsorption isotherms were experimentally determined for these engineered proteins, allowing for direct calculation of the available ligand density present on coated surfaces. As confirmation that ligand density in these engineered systems impacts neuronal cell behavior, we demonstrate that increasing the density of fibronectin-derived RGD ligands on coated surfaces while maintaining uniform protein surface coverage results in enhanced neurite extension of PC-12 cells. Therefore, this engineered protein adsorption approach allows for the facile preparation of tunable, quantifiable, and reproducible surfaces for in vitro studies of cell–ligand interactions and for potential application as coatings on neural implants

The Technical Object and Somatic Thought. Theories of Gesture between Anthropology, Aesthetics and Cinema

This essay explores the lines of thought focused on the relationship between gesture and technique, examining the theories which have conceptualized the trans- fer of gestural matrices into inert matter, and understood technique as a result of this process. Although associated mainly with the writings of the palaeontologist Andr\ue9 Leroi-Gourhan, this thought actually predates his work, and consists of multiple branches: having first taken root at the end of the nineteenth century, it became dif- fused throughout the following decades in different forms. These nevertheless shared a constant reference to cinema, both as a privileged place that captures gestures, and as a technique that can absorb their quintessence. From Espinas to Simondon, via Jousse and Eisenstein, the theory of gestural transmission breaks down various polari- ties, such as body and environment, organic and inorganic, animated and inanimate, performativity and inner life. It foregrounds the imaginative logic of the body and the many forms of somatic thinking developed by man. Such forms lie at the heart of the creative processes and have found their highest appreciation in cinema, as a machine that, from its very origins, has been grafted not only on the eye but on the whole body

Optimized Real-Time Biomimetic Neural Network on FPGA for Bio-hybridization

Neurological diseases can be studied by performing bio-hybrid experiments using a real-time biomimetic Spiking Neural Network (SNN) platform. The Hodgkin-Huxley model offers a set of equations including biophysical parameters which can serve as a base to represent different classes of neurons and affected cells. Also, connecting the artificial neurons to the biological cells would allow us to understand the effect of the SNN stimulation using different parameters on nerve cells. Thus, designing a real-time SNN could useful for the study of simulations of some part of the brain. Here, we present a different approach to optimize the Hodgkin-Huxley equations adapted for Field Programmable Gate Array (FPGA) implementation. The equations of the conductance have been unified to allow the use of same functions with different parameters for all ionic channels. The low resources and high-speed implementation also include features, such as synaptic noise using the Ornstein–Uhlenbeck process and different synapse receptors including AMPA, GABAa, GABAb, and NMDA receptors. The platform allows real-time modification of the neuron parameters and can output different cortical neuron families like Fast Spiking (FS), Regular Spiking (RS), Intrinsically Bursting (IB), and Low Threshold Spiking (LTS) neurons using a Digital to Analog Converter (DAC). Gaussian distribution of the synaptic noise highlights similarities with the biological noise. Also, cross-correlation between the implementation and the model shows strong correlations, and bifurcation analysis reproduces similar behavior compared to the original Hodgkin-Huxley model. The implementation of one core of calculation uses 3% of resources of the FPGA and computes in real-time 500 neurons with 25,000 synapses and synaptic noise which can be scaled up to 15,000 using all resources. This is the first step toward neuromorphic system which can be used for the simulation of bio-hybridization and for the study of neurological disorders or the advanced research on neuroprosthesis to regain lost function