Adipose-derived mesenchymal stem cells improve glucose homeostasis in high-fat diet-induced obese mice

Introduction Effective therapies for obesity and diabetes are still lacking. The aim of this study was to evaluate whether a single intravenous infusion of syngeneic adipose-derived mesenchymal stem cells (ASCs) can reduce obesity, lower insulin resistance, and improve glucose homeostasis in a high-fat diet-induced obese (DIO) mouse model. Methods Seven-week-old C57BL/6 mice were fed a high-fat diet for 20 weeks to generate the DIO mouse model. Mice were given a single intravenous infusion of ex vivo expanded syngeneic ASCs at 2 × 10 6 cells per mouse. DIO or CHOW mice injected with saline were used as controls. Body weights, blood glucose levels, glucose, and insulin tolerance test results were obtained before and 2 and 6 weeks after cell infusion. Triglyceride (TG), high-density lipoprotein (HDL), and insulin levels in serum were measured. Expressions of genes related to insulin resistance, including peroxisome proliferator-activated receptor γ (PPARγ) and insulin receptor (InsR), and inflammation (IL-6, F4/80, and nucleotide-binding oligomerization domain containing 2, or NOD2), were measured in livers at mRNA level by real-time-polymerase chain reaction analysis. Beta-cell mass in pancrheases from CHOW, DIO, and DIO + ASC mice was quantified. GFP + ASCs were injected, and the presence of GFP + cells in livers and pancreases was determined. Results DIO mice that had received ASCs showed reduced body weights, reduced blood glucose levels, and increased glucose tolerance. ASC treatment was found to reduce TG levels and increase serum HDL levels. In livers, less fat cell deposition was observed, as were increased expression of InsR and PPARγ and reduction in expressions of IL-6 and F4/80. Treated mice showed well-preserved pancreatic β-cell mass with reduced expression of F4/80 and TNF-α compared with DIO controls. GFP + cells were found in liver and pancreas tissues at 1 and 2 weeks after cell injection. Conclusions ASC therapy is effective in lowering blood glucose levels and increasing glucose tolerance in DIO mice. The protective effects of ASCs arise at least in part from suppression of inflammation in the liver. In addition, ASCs are associated with better-preserved pancreatic β-cell mass

SPIDer: Saccharomyces protein-protein interaction database

BACKGROUND: Since proteins perform their functions by interacting with one another and with other biomolecules, reconstructing a map of the protein-protein interactions of a cell, experimentally or computationally, is an important first step toward understanding cellular function and machinery of a proteome. Solely derived from the Gene Ontology (GO), we have defined an effective method of reconstructing a yeast protein interaction network by measuring relative specificity similarity (RSS) between two GO terms. DESCRIPTION: Based on the RSS method, here, we introduce a predicted Saccharomyces protein-protein interaction database called SPIDer. It houses a gold standard positive dataset (GSP) with high confidence level that covered 79.2% of the high-quality interaction dataset. Our predicted protein-protein interaction network reconstructed from the GSPs consists of 92 257 interactions among 3600 proteins, and forms 23 connected components. It also provides general links to connect predicted protein-protein interactions with three other databases, DIP, BIND and MIPS. An Internet-based interface provides users with fast and convenient access to protein-protein interactions based on various search features (searching by protein information, GO term information or sequence similarity). In addition, the RSS value of two GO terms in the same ontology, and the inter-member interactions in a list of proteins of interest or in a protein complex could be retrieved. Furthermore, the database presents a user-friendly graphical interface which is created dynamically for visualizing an interaction sub-network. The database is accessible at . CONCLUSION: SPIDer is a public database server for protein-protein interactions based on the yeast genome. It provides a variety of search options and graphical visualization of an interaction network. In particular, it will be very useful for the study of inter-member interactions among a list of proteins, especially the protein complex. In addition, based on the predicted interaction dataset, researchers could analyze the whole interaction network and associate the network topology with gene/protein properties based on a global or local topology view

A New Model for Predicting Dynamic Surge Pressure in Gas and Drilling Mud Two-Phase Flow during Tripping Operations

Investigation of surge pressure is of great significance to the circulation loss problem caused by unsteady operations in management pressure drilling (MPD) operations. With full consideration of the important factors such as wave velocity, gas influx rate, pressure, temperature, and well depth, a new surge pressure model has been proposed based on the mass conservation equations and the momentum conservation equations during MPD operations. The finite-difference method, the Newton-Raphson iterative method, and the fourth-order explicit Runge-Kutta method (R-K4) are adopted to solve the model. Calculation results indicate that the surge pressure has different values with respect to different drill pipe tripping speeds and well parameters. In general, the surge pressure tends to increase with the increases of drill pipe operating speed and with the decrease of gas influx rate and wellbore diameter. When the gas influx occurs, the surge pressure is weakened obviously. The surge pressure can cause a significant lag time if the gas influx occurs at bottomhole, and it is mainly affected by pressure wave velocity. The maximum surge pressure may occur before drill pipe reaches bottomhole, and the surge pressure is mainly affected by drill pipe operating speed and gas influx rate

Genome-wide comparative analysis of digital gene expression tag profiles during maize ear development

Background: Development of the maize (Zea mays L.) female inflorescence (ear) has an important impact on corn yield. However, the molecular mechanisms underlying maize ear development are poorly understood. Results: We profiled and analyzed gene expression of the maize ear at four developmental stages: elongation phase (I), spikelet differentiation phase (II), floret primordium differentiation phase (III), and floret organ differentiation phase (IV). Based on genome-wide profile analysis, we detected differential mRNA of maize genes. Among the ~6,800 differentially expressed genes (DEGs), 3,325 genes were differentially expressed in stage II, 3,765 genes in III, and 1,698 genes in IV, compared to its previous adjacent stages, respectively. Furthermore, some of DEGs were predicted to be potential candidates in maize ear development, such as AGAMOUS (GRMZM2G052890) and ATFP3 (GRMZM2G155281). Meanwhile, some genes were well-known annotated to the mutants during maize inflorescence development such as compact plant2 (ct2), zea AGAMOUS homolog1 (zag1), bearded ear (bde), and silky1 (si1). Some DEGs were predicted targets of microRNAs such as microRNA156. K-means clustering revealed that the DEGs showed 18 major expression patterns. Thirteen transcriptional factors from 10 families were differentially expressed across three comparisons of adjacent stages (II vs. I, III vs. II, IV vs. III). Antisense transcripts were widespread during all four stages, and might play important roles in maize ear development. Finally, we randomly selected 32 DEGs to validate their expression patterns using quantitative reverse-transcription polymerase chain reaction (qRT-PCR). The results were consistent with those from Solexa sequencing. Conclusions: DEGs technique had shown an advantage in detecting candidates, and some transcription factors during maize ear development. RT-PCR data were consistent with our sequencing data and supplied additional information on ear developmental processes. These results provide a molecular foundation for future research on maize ear development