We have previously suggested a biologically-inspired natural dynamic controller for biped locomotion, which applies torque pulses to the different joints at particular phases of an internal phase variable. The parameters of the controller, including the timing and magnitude of the torque pulses and the dynamics of the phase variable, can be kept constant in open loop or adapted to the environment in closed loop. Here we demonstrate the implementation of this approach to a mono-ped robot and the optimization of the controller parameters to enhance robustness via policy gradient. Policy gradient was applied in simulations rather than the actual robot due to safety and hardware considerations. A grounded action transformation (GAT) was learned and used to facilitate the transfer of the learned policy from simulation to hardware. We demonstrate how GAT improves the match between simulations and experiments and how learning enhances the performance and robustness of the mono-ped robot. © 2020 IOP Publishing Ltd.Extracellular matrices (ECMs) are dynamically altered and remodeled during tissue development. How the dynamic remodeling of ECM affects stem cell functions remains poorly understood due to the difficulty of obtaining biomimetic ECMs. In this study, stepwise osteogenesis-mimicking ECM-deposited hybrid meshes were prepared by culturing human mesenchymal stem cells (hMSCs) in poly (lactic-co-glycolic acid) (PLGA)-collagen hybrid meshes and controlling the stages of the osteogenesis of hMSCs. Three types of hybrid mesh mimicking the ECMs that were secreted from stem cell stage of hMSCs (SC-ECM), early stage (EO-ECM) and late stage (LO-ECM) osteogenesis of hMSCs were prepared. The stepwise osteogenesis-mimicking ECM deposited PLGA-collagen hybrid meshes showed different ECM compositions associated with the stage of osteogenesis. Their effects on the osteogenic differentiation of hMSCs differed. EO-ECM scaffold increased and LO-ECM scaffold moderately promoted the osteogenic differentiation of hMSCs. However, SC-ECM scaffold inhibited the osteogenic differentiation of hMSCs. The novel PLGA-collagen-ECM hybrid meshes will provide useful tools for stem cell culture and tissue engineering.The field of bioprinting has made significant recent progress towards engineering tissues with increasing complexity and functionality. It remains challenging, however, to develop bioinks with optimal biocompatibility and good printing fidelity. Here, we demonstrate enhanced printability of a polymer-based bioink based on dynamic covalent linkages between nanoparticles (NPs) and polymers, which retains good biocompatibility. Amine-presenting silica NPs (ca. 45 nm) were added to a polymeric ink containing oxidized alginate (OxA). The formation of reversible imine bonds between amines on the NPs and aldehydes of OxA lead to significantly improved rheological properties and high printing fidelity. In particular, the yield stress increased with increasing amounts of NPs (14.5 Pa without NPs, 79 Pa with 2 wt% NPs). In addition, the presence of dynamic covalent linkages in the gel provided improved mechanical stability over 7 d compared to ionically crosslinked gels.  https://www.selleckchem.com/products/methylene-blue-trihydrate.html  The nanocomposite ink retained high printability and mechanical strength, resulting in generation of centimeter-scale porous constructs and an ear structure with overhangs and high structural fidelity. Furthermore, the nanocomposite ink supported both in vitro and in vivo maturation of bioprinted gels containing chondrocytes. This approach based on simple oxidation can be applied to any polysaccharide, thus the widely applicability of the method is expected to advance the field towards the goal of precision bioprinting.In this study, we conduct a comparison of three most recent statistical methods for joint variable selection and covariance estimation with application of detecting expression quantitative trait loci (eQTL) and gene network estimation, and introduce a new hierarchical Bayesian method to be included in the comparison. Unlike the traditional univariate regression approach in eQTL, all four methods correlate phenotypes and genotypes by multivariate regression models that incorporate the dependence information among phenotypes, and use Bayesian multiplicity adjustment to avoid multiple testing burdens raised by traditional multiple testing correction methods. We presented the performance of three methods (MSSL - Multivariate Spike and Slab Lasso, SSUR - Sparse Seemingly Unrelated Bayesian Regression, and OBFBF - Objective Bayes Fractional Bayes Factor), along with the proposed, JDAG (Joint estimation via a Gaussian Directed Acyclic Graph model) method through simulation experiments, and publicly available HapMap real data, taking asthma as an example. Compared with existing methods, JDAG identified networks with higher sensitivity and specificity under row-wise sparse settings. JDAG requires less execution in small-to-moderate dimensions, but is not currently applicable to high dimensional data. The eQTL analysis in asthma data showed a number of known gene regulations such as STARD3, IKZF3 and PGAP3, all reported in asthma studies. The code of the proposed method is freely available at GitHub (https//github.com/xuan-cao/Joint-estimation-for-eQTL).Maximum likelihood is a common method of estimating a phylogenetic tree based on a set of genetic data. However, models of evolution for certain types of genetic data are highly flawed in their specification, and this misspecification can have an adverse impact on phylogenetic inference. Our attention here is focused on extending an existing class of models for estimating phylogenetic trees from discrete morphological characters. The main advance of this work is a model that allows unequal equilibrium frequencies in the estimation of phylogenetic trees from discrete morphological character data using likelihood methods. Possible extensions of the proposed model will also be discussed.Background Gabapentinoids are known to reduce neuropathic pain. The aim of this experimental study was to investigate whether gabapentinoids exert anti-inflammatory and/or anti-nociceptive effects at the cellular level using primary cultures of rat dorsal root ganglia (DRG). Methods Cells from rat DRG were cultured in the presence of gabapentin or pregabalin, and we tested the effects of subsequent stimulation with lipopolysaccharide (LPS) on the expression of genes (real-time polymerase chain reaction) and production of tumor necrosis factor-α (TNFα) and interleukin-6 (IL-6) by specific bioassays. Using Ca2+ imaging, we further investigated in neurons the effects of gabapentinoids upon stimulation with the TRPV-1 agonist capsaicin. Results There is a small influence of gabapentinoids on the inflammatory response to LPS stimulation, namely, a significantly reduced expression of IL-6. Pregabalin and gabapentin further seem to exert a moderate inhibitory influence on capsaicin-induced Ca2+ signals in DRG neurons.