Multiple-point statistical simulation for hydrogeological models: 3D training image development and conditioning strategies

Most studies about the application of geostatistical simulations based on multiple-point statistics (MPS) to hydrogeological modelling focus on relatively fine-scale models and concentrate on the estimation of facies-level, structural uncertainty. Much less attention is paid to the use of input data and optimal construction of training images. For instance, even though the training image should capture a set of spatial geological characteristics to guide the simulations, the majority of the research still relies on 2D or quasi-3D training images. In the present study, we demonstrate a novel strategy for 3D MPS modelling characterized by: (i) realistic 3D training images, and (ii) an effective workflow for incorporating a diverse group of geological and geophysical data sets. The study covers an area of 2810 km2 in the southern part of Denmark. MPS simulations are performed on a subset of the geological succession (the lower to middle Miocene sediments) which is characterized by relatively uniform structures and dominated by sand and clay. The simulated domain is large and each of the geostatistical realizations contains approximately 45 million voxels with size 100 m × 100 m × 5 m. Data used for the modelling include water well logs, high-resolution seismic data, and a previously published 3D geological model. We apply a series of different strategies for the simulations based on data quality, and develop a novel method to effectively create observed sand/clay spatial trends. The training image is constructed as a small 3D voxel model covering an area of 90 km2. We use an iterative training image development strategy and find that even slight modifications in the training image create significant changes in simulations. Thus, the study underlines that it is important to consider both the geological environment, and the type and quality of input information in order to achieve optimal results from MPS modelling. In this study we present a possible workflow to build the training image and effectively handle different types of input information to perform large-scale geostatistical modellin

Pericellular activation of hepatocyte growth factor by the transmembrane serine proteases matriptase and hepsin, but not by the membrane-associated protease uPA

HGF (hepatocyte growth factor) is a pleiotropic cytokine homologous to the serine protease zymogen plasminogen that requires canonical proteolytic cleavage to gain functional activity. The activating proteases are key components of its regulation, but controversy surrounds their identity. Using quantitative analysis we found no evidence for activation by uPA (urokinase plasminogen activator), despite reports that this is a principal activator of pro-HGF. This was unaffected by a wide range of experimental conditions, including the use of various molecular forms of both HGF and uPA, and the presence of uPAR (uPA receptor) or heparin. In contrast the catalytic domains of the TTSPs (type-II transmembrane serine proteases) matriptase and hepsin were highly efficient activators (50% activation at 0.1 and 3.4 nM respectively), at least four orders of magnitude more efficient than uPA. PS-SCL (positional-scanning synthetic combinatorial peptide libraries) were used to identify consensus sequences for the TTSPs, which in the case of hepsin corresponded to the pro-HGF activation sequence, demonstrating a high specificity for this reaction. Both TTSPs were also found to be efficient activators at the cell surface. Activation of pro-HGF by PC3 prostate carcinoma cells was abolished by both protease inhibition and matriptase-targeting siRNA (small interfering RNA), and scattering of MDCK (Madin–Darby canine kidney) cells in the presence of pro-HGF was abolished by inhibition of matriptase. Hepsin-transfected HEK (human embryonic kidney)-293 cells also activated pro-HGF. These observations demonstrate that, in contrast with the uPA/uPAR system, the TTSPs matriptase and hepsin are direct pericellular activators of pro-HGF, and that together these proteins may form a pathway contributing to their involvement in pathological situations, including cancer

Skeletal muscle O-GlcNAc transferase is important for muscle energy homeostasis and whole-body insulin sensitivity

Objective: Given that cellular O-GlcNAcylation levels are thought to be real-time measures of cellular nutrient status and dysregulated O-GlcNAc signaling is associated with insulin resistance, we evaluated the role of O-GlcNAc transferase (OGT), the enzyme that mediates O-GlcNAcylation, in skeletal muscle. Methods: We assessed O-GlcNAcylation levels in skeletal muscle from obese, type 2 diabetic people, and we characterized muscle-specific OGT knockout (mKO) mice in metabolic cages and measured energy expenditure and substrate utilization pattern using indirect calorimetry. Whole body insulin sensitivity was assessed using the hyperinsulinemic euglycemic clamp technique and tissue-specific glucose uptake was subsequently evaluated. Tissues were used for histology, qPCR, Western blot, co-immunoprecipitation, and chromatin immunoprecipitation analyses. Results: We found elevated levels of O-GlcNAc-modified proteins in obese, type 2 diabetic people compared with well-matched obese and lean controls. Muscle-specific OGT knockout mice were lean, and whole body energy expenditure and insulin sensitivity were increased in these mice, consistent with enhanced glucose uptake and elevated glycolytic enzyme activities in skeletal muscle. Moreover, enhanced glucose uptake was also observed in white adipose tissue that was browner than that of WT mice. Interestingly, mKO mice had elevated mRNA levels of Il15 in skeletal muscle and increased circulating IL-15 levels. We found that OGT in muscle mediates transcriptional repression of Il15 by O-GlcNAcylating Enhancer of Zeste Homolog 2 (EZH2). Conclusions: Elevated muscle O-GlcNAc levels paralleled insulin resistance and type 2 diabetes in humans. Moreover, OGT-mediated signaling is necessary for proper skeletal muscle metabolism and whole-body energy homeostasis, and our data highlight O-GlcNAcylation as a potential target for ameliorating metabolic disorders. Keywords: O-GlcNAc signaling, Type 2 diabetes, N-acetyl-d-glucosamine, Tissue cross talk, Epigenetic regulation of Il15 transcription, Insulin sensitivit

Soluble urokinase receptor released from human carcinoma cells: a plasma parameter for xenograft tumour studies

The urokinase plasminogen activator receptor (uPAR) plays a critical role in urokinase-mediated plasminogen activation and thereby in the process leading to invasion and metastasis. Soluble urokinase receptor (suPAR) is released from tumours, and in cancer patients the blood level of soluble receptor is increased. Using an enzyme-linked, immunosorbent assay (ELISA)-specific for the human urokinase receptor, release of soluble receptor was measured in cultures of human breast carcinoma cells, in tumour extracts and in plasma from mice with xenografted human tumours. Soluble human urokinase receptor (shuPAR) was released into culture supernatant during the growth of the human breast cancer cell line MDA-MB-231 BAG, and the level of shuPAR in conditioned medium determined by ELISA was a linear function of both viable cell number and time of incubation. Western blotting showed that the form of shuPAR measured by ELISA in conditioned medium consisted virtually exclusively of the three-domain full-length protein, while uPAR in cell lysates consisted of full-length uPAR as well as the domains (2+3) cleavage product. shuPAR was also released into the plasma of nude mice during growth of MDA-MB-231 BAG, MDA-MB-435 BAG and HCT 116 cells as subcutaneously xenografted tumours. Western blotting demonstrated that the shuPAR released from the xenografted human tumours into plasma consisted of the three-domain full-length protein, despite the finding of some cleaved uPAR in detergent extracts of tumour tissue. The levels of shuPAR determined by ELISA in the plasma of host mice during the growth of xenografted cell lines were highly correlated with tumour volume. © 1999 Cancer Research Campaig