A Novel Modeling Approach to Stochastically Evaluate the Impact of Pore Network Geometry, Chemistry and Topology on Fluid Transport

Fine-grained sandstones, siltstones, and shales have become increasingly important to satisfy the ever-growing global energy demands. Of particular current interest are shale rocks, which are mudstones made up of organic and inorganic constituents of varying pore sizes. These materials exhibit high heterogeneity, low porosity, varying chemical composition and low pore connectivity. Due to the complexity and the importance of such materials, many experimental, theoretical and computational eforts have attempted to quantify the impact of rock features on fuids difusivity and ultimately on permeability. In this study, we introduce a stochastic kinetic Monte Carlo approach developed to simulate fuid transport. The features of this approach allow us to discuss the applicability of 2D vs 3D models for the calculation of transport properties. It is found that a successful model should consider realistic 3D pore networks consisting of pore bodies that communicate via pore throats, which however requires a prohibitive amount of computational resources. To overcome current limitations, we present a rigorous protocol to stochastically generate synthetic 3D pore networks in which pore features can be isolated and varied systematically and individually. These synthetic networks do not correspond to real sample scenarios but are crucial to achieve a systematic evaluation of the pore features on the transport properties. Using this protocol, we quantify the contribution of the pore network’s connectivity, porosity, mineralogy, and pore throat width distribution on the difusivity of supercritical methane. A sensitivity analysis is conducted to rank the signifcance of the various network features on methane difusivity. Connectivity is found to be the most important descriptor, followed by pore throat width distribution and porosity. Based on such insights, recommendations are provided on possible technological approaches to enhance fuid transport through shale rocks and equally complex pore networks. The purpose of this work is to identify the signifcance of various pore network characteristics using a stochastic KMC algorithm to simulate the transport of fuids. Our fndings could be relevant for applications that make use of porous media, ranging from catalysis to radioactive waste management, and from environmental remediation to shale gas production

The metalloproteinase ADAM10 requires its activity to sustain surface expression

The metalloproteinase ADAM10 critically contributes to development, inflammation, and cancer and can be controlled by endogenous or synthetic inhibitors. Here, we demonstrate for the first time that loss of proteolytic activity of ADAM10 by either inhibition or loss of function mutations induces removal of the protease from the cell surface and the whole cell. This process is temperature dependent, restricted to mature ADAM10, and associated with an increased internalization, lysosomal degradation, and release of mature ADAM10 in extracellular vesicles. Recovery from this depletion requires de novo synthesis. Functionally, this is reflected by loss and recovery of ADAM10 substrate shedding. Finally, ADAM10 inhibition in mice reduces systemic ADAM10 levels in different tissues. Thus, ADAM10 activity is critically required for its surface expression in vitro and in vivo. These findings are crucial for development of therapeutic ADAM10 inhibition strategies and may showcase a novel, physiologically relevant mechanism of protease removal due to activity loss

Removal of PCR Error Products and Unincorporated Primers by Metal-Chelate Affinity Chromatography

Immobilized Metal Affinity Chromatography (IMAC) has been used for decades to purify proteins on the basis of amino acid content, especially surface-exposed histidines and “histidine tags” genetically added to recombinant proteins. We and others have extended the use of IMAC to purification of nucleic acids via interactions with the nucleotide bases, especially purines, of single-stranded RNA and DNA. We also have demonstrated the purification of plasmid DNA from contaminating genomic DNA by IMAC capture of selectively-denatured genomic DNA. Here we describe an efficient method of purifying PCR products by specifically removing error products, excess primers, and unincorporated dNTPs from PCR product mixtures using flow-through metal-chelate affinity adsorption. By flowing a PCR product mixture through a Cu2+-iminodiacetic acid (IDA) agarose spin column, 94–99% of the dNTPs and nearly all the primers can be removed. Many of the error products commonly formed by Taq polymerase also are removed. Sequencing of the IMAC-processed PCR product gave base-calling accuracy comparable to that obtained with a commercial PCR product purification method. The results show that IMAC matrices (specifically Cu2+-IDA agarose) can be used for the purification of PCR products. Due to the generality of the base-specific mechanism of adsorption, IMAC matrices may also be used in the purification of oligonucleotides, cDNA, mRNA and micro RNAs

Mechanical environment alters tissue formation patterns during fracture repair

Fracture repair has previously been shown to be sensitive to mechanical environment, yet the specific relationship between strain character, magnitude and frequency, as well as other mechanical parameters, and tissue formation is not well understood. This study aimed to correlate strain distribution within the healing fracture gap with patterns of tissue formation using a rat model of a healing osteotomy subject to mechanical stimulation in bending. Finite element models based on realistic tissue distributions were used to estimate both the magnitude and spatial distribution of strains within the fracture gap. The spatial distribution of regenerating tissue was determined by microcomputed tomography and histology, and was confirmed using reverse transcription-polymerase chain reaction (RT-PCR). Results suggest that tensile strains suppress chondrogenesis during the mechanical stimulation period. After stimulation ends, however, tensile strains increased chondrogenesis followed by rapid bone formation. In contrast, in compressive environments, bone is formed primarily via intramembranous ossification. Taken together, these results suggest that intermittent tensile strains during fracture repair stimulate endochondral ossification and promote eventual bone healing compared to intermittent compressive strains and unstimulated fractures. Further understanding of these relationships may allow proposal of optimal therapeutic strategies for improvement of the fracture repair process. © 2004 Orthopaedic Research Society. Published y Elsevier Ltd. All rights reserved.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/34921/1/1100220523_ftp.pd

Sequence of the Bacillus subtilis genome region in the vicinity of the lev operon reveals two new extracytoplasmic function RNA polymerase sigma factors SigV and SigZ

Two regions with sizes 18900 and 25400 bp, which join previously known contigs containing levRDEFG, aadK and bit genes near 235 degrees of the Bacillus subtilis chromosome, were sequenced. Among others, two genes, which encode proteins homologous to RNA polymerase sigma-factors, were identified within this region. The gene products designated SigV and SigZ, show the highest homology with sigma-factors encoded by the gene carQ of Myxococcus xanthus and sigX (formerly orfX20) of B. subtilis, correspondingly. All sigma-factors which show statistically significant homology to SigV and SigZ, belong to the ECF (extracytoplasmic functions) subfamily. SigV and SigZ do not have N-terminal sequence which prevents such proteins from binding to DNA without RNA polymerase core enzyme

Estimating permeability in shales and other heterogeneous porous media: Deterministic vs. stochastic investigations

With increasing global energy demands, unconventional formations, such as shale rocks, are becoming an important source of natural gas. Extensive efforts focus on understanding the complex behavior of fluids (including their transport in the sub-surface) to maximize natural gas yields. Shale rocks are mudstones made up of organic and inorganic constituents of varying pore sizes (1-500 nm). With cutting-edge imaging technologies, detailed structural and chemical description of shale rocks can be obtained at different length scales. Using this knowledge to assess macroscopic properties, such as fluid permeability, remains challenging. Direct experimental measurements of permeability supply answers, but at elevated costs of time and resources. To complement these, computer simulations are widely available; however, they employ significant approximations, and a reliable methodology to estimate permeability in heterogeneous pore networks remains elusive. For this study, permeability predictions obtained by implementing two deterministic methods and one stochastic approach, using a kinetic Monte Carlo algorithm, are compared. This analysis focuses on the effects resulting from pore size distribution, the impact of micro- and macropores, and the effects of anisotropy (induced or naturally occurring) on the predicted matrix permeability. While considering multiple case studies, recommendations are provided on the optimal conditions under which each method can be used. Finally, a stochastic analysis is performed to estimate the permeability of an Eagle Ford shale sample using the kinetic Monte Carlo algorithm. Successful comparisons against experimental data demonstrate the appeal of the stochastic approach proposed