Controlled Delivery of Sonic Hedgehog Morphogen and Its Potential for Cardiac Repair

The morphogen Sonic hedgehog (Shh) holds great promise for repair or regeneration of tissues suffering ischemic injury, however clinical translation is limited by its short half-life in the body. Here, we describe a coacervate delivery system which incorporates Shh, protects it from degradation, and sustains its release for at least 3 weeks. Shh released from the coacervate stimulates cardiac fibroblasts to upregulate the expression of multiple trophic factors including VEGF, SDF-1α, IGF-1, and Shh itself, for at least 48 hours. Shh coacervate also demonstrates cytoprotective effects for cardiomyocytes in a hydrogen peroxide-induced oxidative stress environment. In each of these studies the bioactivity of the Shh coacervate is enhanced compared to free Shh. These results warrant further investigation of the in vivo efficacy of Shh coacervate for cardiac repair. © 2013 Johnson, Wang

Isolation of 10 cyclosporine metabolites from human bile

Ten metabolites of cyclosporine were isolated from the ethyl ether extract of bile from four liver transplant patients receiving cyclosporine. Two of the metabolites were unique and previously unidentified. Liquid-liquid partitioning into diethyl ether with subsequent defatting with n-hexane was used for the initial extraction form bile. Separation of the individual metabolites (A-J) was performed using a Sephadex LH-20 column and a gradient high performance liquid chromatographic method. The molecular weights of the isolated metabolites were determined by fast atom bombardment/mass spectrometry. Gas chromatography with mass spectrometic amino acid analysis was also used to identify the amino acid composition and the hydroxylation position of metabolites A, B, C, D, and G. Proton nuclear magnetic resonance spectra were utilized to disinguish the chemical shifts of N-CH3 singlets and NH doublets of metabolites A, B, C, and D. Metabolites A, E, F, H, I, and J were reported previously in human urine and animal bile. Metabolites C and D are dihydroxylated compounds which cannot be clearly described as previously isolated compounds. Metabolites B and G are novel metabolites with a mass fragment which corresponded to a loss of 131 Da from the protonated molecular ion (MH+) in the fast atom bombardment/mass spectrometry, suggesting that the double bond in amino acid 1 has been modified. Metabolites B and G were primarily isolated from the bile of one of the liver transplant patients which contained abnormally high concentrations of these two metabolites. The method described is an efficient procedure for isolating milligram quantities of the major metabolites with greater than 95% purity

Transcriptional profiling reveals altered biological characteristics of chorionic stem cells from women with gestational diabetes

Background Gestational diabetes (GDM) is a common complication of pregnancy. The impact of pregnancy complications on placental function suggests that extraembryonic stem cells in the placenta may also be affected during pregnancy. Neonatal tissue-derived stem cells, with the advantages of their differentiation capacity and non-invasive isolation processes, have been proposed as a promising therapeutic avenue for GDM management through potential cell therapy approaches. However, the influence of GDM on autologous stem cells remains unclear. Thus, studies that provide comprehensive understanding of stem cells isolated from women with GDM are essential to guide future clinical applications. Methods Human chorionic membrane-derived stem cells (CMSCs) were isolated from placentas of healthy and GDM pregnancies. Transcriptional profiling was performed by DNA microarray, and differentially regulated genes between GDM- and Healthy-CMSCs were used to analyse molecular functions, differentiation, and pathway enrichment. Altered genes and biological functions were validated via real-time PCR and in vitro assays. Results GDM-CMSCs displayed, vs. Healthy-CMSCs, 162 upregulated genes associated with increased migration ability, epithelial development, and growth factor-associated signal transduction while the 269 downregulated genes were strongly linked to angiogenesis and cellular metabolic processes. Notably, significantly reduced expression of detoxification enzymes belonging to the aldehyde dehydrogenase gene families (ALDH1A1/1A2, ALDH2, ALDH3) accounted for downregulation across several metabolic pathways. ALDH activity and inhibitor assays indicated that reduced gene expression of ALDHs affected ALDH enzymatic functions and resulted in oxidative stress dysregulation in GDM-CMSCs. Conclusion Our combined transcriptional analysis and in vitro functional characterisation have provided novel insights into fundamental biological differences in GDM- and Healthy-CMSCs. Enhanced mobility of GDM-CMSCs may promote MSC migration toward injured sites; however, impaired cellular metabolic activity may negatively affect any perceived benefit

Fuzzy decision-making fuser (FDMF) for integrating human-machine autonomous (HMA) systems with adaptive evidence sources

© 2017 Liu, Pal, Marathe, Wang and Lin. A brain-computer interface (BCI) creates a direct communication pathway between the human brain and an external device or system. In contrast to patient-oriented BCIs, which are intended to restore inoperative or malfunctioning aspects of the nervous system, a growing number of BCI studies focus on designing auxiliary systems that are intended for everyday use. The goal of building these BCIs is to provide capabilities that augment existing intact physical and mental capabilities. However, a key challenge to BCI research is human variability; factors such as fatigue, inattention, and stress vary both across different individuals and for the same individual over time. If these issues are addressed, autonomous systems may provide additional benefits that enhance system performance and prevent problems introduced by individual human variability. This study proposes a human-machine autonomous (HMA) system that simultaneously aggregates human and machine knowledge to recognize targets in a rapid serial visual presentation (RSVP) task. The HMA focuses on integrating an RSVP BCI with computer vision techniques in an image-labeling domain. A fuzzy decision-making fuser (FDMF) is then applied in the HMA system to provide a natural adaptive framework for evidence-based inference by incorporating an integrated summary of the available evidence (i.e., human and machine decisions) and associated uncertainty. Consequently, the HMA system dynamically aggregates decisions involving uncertainties from both human and autonomous agents. The collaborative decisions made by an HMA system can achieve and maintain superior performance more efficiently than either the human or autonomous agents can achieve independently. The experimental results shown in this study suggest that the proposed HMA system with the FDMF can effectively fuse decisions from human brain activities and the computer vision techniques to improve overall performance on the RSVP recognition task. This conclusion demonstrates the potential benefits of integrating autonomous systems with BCI systems

Heterogeneous formic acid production by hydrogenation of CO₂ catalyzed by Ir‐bpy embedded in polyphenylene porous organic polymers

Heterogeneous immobilized molecular catalysis has gained significant attention as a platform for creating more efficient and selective catalysts. A promising type of immobilized molecular catalysts are made from porous organic polymers (POPs) due to their high stability, porosity, and ability to mimic the catalytic activity and selectivity of homogeneous organometallic catalysts. These properties of the POP-based systems make them very attractive as heterogeneous catalysts for hydrogenation of CO2 to formate, where predominately homogeneous systems have been applied. In this study, five POPs were synthesized and assessed in the hydrogenation of CO2 where the active catalysts were made in-situ by mixing IrCl3 and the POPs. One of the Ir/POP catalysts provided a turn-over number (TON) >20,000, which is among the highest for POP-based systems. Thorough characterization (CO2- and N2-physisorption, TGA, CHN-analysis, XRD, XPS, SEM, STEM and TEM) was performed. Notably, the developed Ir/POP system also showed catalytic activity for the decomposition of formic acid into H2 enabling the use of formic acid as a renewable energy carrier

Exploring Covert States of Brain Dynamics via Fuzzy Inference Encoding.

Human brain inherently exhibits latent mental processes which are likely to change rapidly over time. A framework that adopts a fuzzy inference system is proposed to model the dynamics of the human brain. The fuzzy inference system is used to encode real-world data to represent the salient features of the EEG signals. Then, an unsupervised clustering is conducted on the extracted feature space to identify the brain (external and covert) states that respond to different cognitive demands. To understand the human state change, a state transition diagram is introduced, allowing visualization of connectivity patterns between every pair of states. We compute the transition probability between every pair of states to represent the relationships between the states. This state transition diagram is named as the Fuzzy Covert State Transition Diagram (FCOSTD), which helps the understanding of human states and human performance. We then apply FCOSTD on distracted driving experiments. FCOSTD successfully discovers the external and covert states, faithfully reveals the transition of the brain between states, and the route of the state change when humans are distracted during a driving task. The experimental results demonstrate that different subjects have similar states and inter-state transition behaviour (establishing the consistency of the system) but different ways to allocate brain resources as different actions are being taken

Space- and Time-Efficient Storage of LiDAR Point Clouds

LiDAR devices obtain a 3D representation of a space. Due to the large size of the resulting datasets, there already exist storage methods that use compression and present some properties that resemble those of compact data structures. Specifically, LAZ format allows accesses to a given datum or portion of the data without having to decompress the whole dataset and provides indexation of the stored data. However, LAZ format still have some drawbacks that should be faced. In this work, we propose a new compact data structure for the representation of a cloud of LiDAR points that supports efficient queries, providing indexing capabilities that are superior to those of LAZ format.Comment: This research has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sk{\l}odowska-Curie Actions H2020-MSCA-RISE-2015 BIRDS GA No. 69094

A Rule-Based Approach to Analyzing Database Schema Objects with Datalog

Database schema elements such as tables, views, triggers and functions are typically defined with many interrelationships. In order to support database users in understanding a given schema, a rule-based approach for analyzing the respective dependencies is proposed using Datalog expressions. We show that many interesting properties of schema elements can be systematically determined this way. The expressiveness of the proposed analysis is exemplarily shown with the problem of computing induced functional dependencies for derived relations. The propagation of functional dependencies plays an important role in data integration and query optimization but represents an undecidable problem in general. And yet, our rule-based analysis covers all relational operators as well as linear recursive expressions in a systematic way showing the depth of analysis possible by our proposal. The analysis of functional dependencies is well-integrated in a uniform approach to analyzing dependencies between schema elements in general.Comment: Pre-proceedings paper presented at the 27th International Symposium on Logic-Based Program Synthesis and Transformation (LOPSTR 2017), Namur, Belgium, 10-12 October 2017 (arXiv:1708.07854

The role of TcdB and TccC subunits in secretion of the photorhabdus Tcd toxin complex

The Toxin Complex (TC) is a large multi-subunit toxin encoded by a range of bacterial pathogens. The best-characterized examples are from the insect pathogens Photorhabdus, Xenorhabdus and Yersinia. They consist of three large protein subunits, designated A, B and C that assemble in a 5:1:1 stoichiometry. Oral toxicity to a range of insects means that some have the potential to be developed as pest control technology. The three subunit proteins do not encode any recognisable export sequences and as such little progress has been made in understanding their secretion. We have developed heterologous TC production and secretion models in E. coli and used them to ascribe functions to different domains of the crucial B+C sub-complex. We have determined that the B and C subunits use a secretion mechanism that is either encoded by the proteins themselves or employ an as yet undefined system common to laboratory strains of E. coli. We demonstrate that both the N-terminal domains of the B and C subunits are required for secretion of the whole complex. We propose a model whereby the N-terminus of the C-subunit toxin exports the B+C sub-complex across the inner membrane while that of the B-subunit allows passage across the outer membrane. We also demonstrate that even in the absence of the B-subunit, that the C-subunit can also facilitate secretion of the larger A-subunit. The recognition of this novel export system is likely to be of importance to future protein secretion studies. Finally, the identification of homologues of B and C subunits in diverse bacterial pathogens, including Burkholderia and Pseudomonas, suggests that these toxins are likely to be important in a range of different hosts, including man