Model-based design of AM components to enable decentralized digital manufacturing systems

Additive manufacturing (AM) is a versatile technology that could add flexibility in manufacturing processes, whether implemented alone or along other technologies. This technology enables on-demand production and decentralized production networks, as production facilities can be located around the world to manufacture products closer to the final consumer (decentralized manufacturing). However, the wide adoption of additive manufacturing technologies is hindered by the lack of experience on its implementation, the lack of repeatability among different manufacturers and a lack of integrated production systems. The later, hinders the traceability and quality assurance of printed components and limits the understanding and data generation of the AM processes and parameters. In this article, a design strategy is proposed to integrate the different phases of the development process into a model-based design platform for decentralized manufacturing. This platform is aimed at facilitating data traceability and product repeatability among different AM machines. The strategy is illustrated with a case study where a car steering knuckle is manufactured in three different facilities in Sweden and Italy

Hydro-without-Hydro Framework for Simulations of Black Hole-Neutron Star Binaries

We introduce a computational framework which avoids solving explicitly hydrodynamic equations and is suitable to study the pre-merger evolution of black hole-neutron star binary systems. The essence of the method consists of constructing a neutron star model with a black hole companion and freezing the internal degrees of freedom of the neutron star during the course of the evolution of the space-time geometry. We present the main ingredients of the framework, from the formulation of the problem to the appropriate computational techniques to study these binary systems. In addition, we present numerical results of the construction of initial data sets and evolutions that demonstrate the feasibility of this approach.Comment: 16 pages, 7 figures. To appear in the Classical and Quantum Gravity special issue on Numerical Relativit

Functional Heterogeneity of Embryonic Stem Cells Revealed through Translational Amplification of an Early Endodermal Transcript

Detection of low-level, lineage-specific transcription aids in the identification of lineage-primed populations of ES cells provides a new framework for pluripotency

Microfluidic Perfusion for Regulating Diffusible Signaling in Stem Cells

Background Autocrine & paracrine signaling are widespread both in vivo and in vitro, and are particularly important in embryonic stem cell (ESC) pluripotency and lineage commitment. Although autocrine signaling via fibroblast growth factor-4 (FGF4) is known to be required in mouse ESC (mESC) neuroectodermal specification, the question of whether FGF4 autocrine signaling is sufficient, or whether other soluble ligands are also involved in fate specification, is unknown. The spatially confined and closed-loop nature of diffusible signaling makes its experimental control challenging; current experimental approaches typically require prior knowledge of the factor/receptor in order to modulate the loop. A new approach explored in this work is to leverage transport phenomena at cellular resolution to downregulate overall diffusible signaling through the physical removal of cell-secreted ligands. Methodology/Principal Findings We develop a multiplex microfluidic platform to continuously remove cell-secreted (autocrine\paracrine) factors to downregulate diffusible signaling. By comparing cell growth and differentiation in side-by-side chambers with or without added cell-secreted factors, we isolate the effects of diffusible signaling from artifacts such as shear, nutrient depletion, and microsystem effects, and find that cell-secreted growth factor(s) are required during neuroectodermal specification. Then we induce FGF4 signaling in minimal chemically defined medium (N2B27) and inhibit FGF signaling in fully supplemented differentiation medium with cell-secreted factors to determine that the non-FGF cell-secreted factors are required to promote growth of differentiating mESCs. Conclusions/Significance Our results demonstrate for the first time that flow can downregulate autocrine\paracrine signaling and examine sufficiency of extracellular factors. We show that autocrine\paracrine signaling drives neuroectodermal commitment of mESCs through both FGF4-dependent and -independent pathways. Overall, by uncovering autocrine\paracrine processes previously hidden in conventional culture systems, our results establish microfluidic perfusion as a technique to study and manipulate diffusible signaling in cell systems.National Institutes of Health (U.S.) (NIH grant No. EB007278)Swiss National Science FoundationSwiss National Science Foundatio

The Liberation of Embryonic Stem Cells

Mouse embryonic stem (ES) cells are defined by their capacity to self-renew and their ability to differentiate into all adult tissues including the germ line. Along with efficient clonal propagation, these properties have made them an unparalleled tool for manipulation of the mouse genome. Traditionally, mouse ES (mES) cells have been isolated and cultured in complex, poorly defined conditions that only permit efficient derivation from the 129 mouse strain; genuine ES cells have not been isolated from another species in these conditions. Recently, use of small molecule inhibitors of glycogen synthase kinase 3 (Gsk3) and the Fgf-MAPK signaling cascade has permitted efficient derivation of ES cells from all tested mouse strains. Subsequently, the first verified ES cells were established from a non-mouse species, Rattus norvegicus. Here, we summarize the advances in our understanding of the signaling pathways regulating mES cell self-renewal that led to the first derivation of rat ES cells and highlight the new opportunities presented for transgenic modeling on diverse genetic backgrounds. We also comment on the implications of this work for our understanding of pluripotent stem cells across mammalian species

Retinoic Acid-Dependent Signaling Pathways and Lineage Events in the Developing Mouse Spinal Cord

Studies in avian models have demonstrated an involvement of retinoid signaling in early neural tube patterning. The roles of this signaling pathway at later stages of spinal cord development are only partly characterized. Here we use Raldh2-null mouse mutants rescued from early embryonic lethality to study the consequences of lack of endogenous retinoic acid (RA) in the differentiating spinal cord. Mid-gestation RA deficiency produces prominent structural and molecular deficiencies in dorsal regions of the spinal cord. While targets of Wnt signaling in the dorsal neuronal lineage are unaltered, reductions in Fibroblast Growth Factor (FGF) and Notch signaling are clearly observed. We further provide evidence that endogenous RA is capable of driving stem cell differentiation. Raldh2 deficiency results in a decreased number of spinal cord derived neurospheres, which exhibit a reduced differentiation potential. Raldh2-null neurospheres have a decreased number of cells expressing the neuronal marker β-III-tubulin, while the nestin-positive cell population is increased. Hence, in vivo retinoid deficiency impaired neural stem cell growth. We propose that RA has separable functions in the developing spinal cord to (i) maintain high levels of FGF and Notch signaling and (ii) drive stem cell differentiation, thus restricting both the numbers and the pluripotent character of neural stem cells

Noise-processing by signaling networks

Signaling networks mediate environmental information to the cell nucleus. To perform this task effectively they must be able to integrate multiple stimuli and distinguish persistent signals from transient environmental fluctuations. However, the ways in which signaling networks process environmental noise are not well understood. Here we outline a mathematical framework that relates a network’s structure to its capacity to process noise, and use this framework to dissect the noise-processing ability of signaling networks. We find that complex networks that are dense in directed paths are poor noise processors, while those that are sparse and strongly directional process noise well. These results suggest that while cross-talk between signaling pathways may increase the ability of signaling networks to integrate multiple stimuli, too much cross-talk may compromise the ability of the network to distinguish signal from noise. To illustrate these general results we consider the structure of the signalling network that maintains pluripotency in mouse embryonic stem cells, and find an incoherent feedforward loop structure involving Stat3, Tfcp2l1, Esrrb, Klf2 and Klf4 is particularly important for noise-processing. Taken together these results suggest that noise-processing is an important function of signaling networks and they may be structured in part to optimize this task