Objective The protein deacetylase SirT1 positively regulates cartilage-specific gene expression, while the proinflammatory cytokine tumor necrosis factor α (TNFα) negatively regulates these same genes. This study was undertaken to test the hypothesis that SirT1 is adversely affected by TNFα, resulting in altered gene expression. Methods Cartilage-specific gene expression, SirT1 activity, and results of chromatin immunoprecipitation analysis at the α2(I) collagen enhancer site were determined in RNA, protein extracts, and nuclei of human osteoarthritic chondrocytes left untreated or treated with TNFα. Protein extracts from human chondrocytes transfected with epitope-tagged SirT1 that had been left untreated or had been treated with TNFα were analyzed by immunoblotting with SirT1 and epitope-specific antibodies. The 75-kd SirT1-reactive protein present in TNFα-treated extracts was identified by mass spectroscopy, and its amino-terminal cleavage site was identified via Edman sequencing. SirT1 activity was assayed following an in vitro cathepsin B cleavage reaction. Cathepsin B small interfering RNA (siRNA) was transfected into chondrocytes left untreated or treated with TNFα. Results TNFα-treated chondrocytes had impaired SirT1 enzymatic activity and displayed 2 forms of the enzyme: a full-length 110-kd protein and a smaller 75-kd fragment. The 75-kd SirT1 fragment was found to lack the carboxy-terminus. Cathepsin B was identified as the TNFα-responsive protease that cleaves SirT1 at residue 533. Reducing cathepsin B levels via siRNA following TNFα exposure blocked the generation of the 75-kd SirT1 fragment. Conclusion These data indicate that TNFα, a cytokine that mediates joint inflammation in arthritis, induces cathepsin B–mediated cleavage of SirT1, resulting in reduced SirT1 activity. This reduced SirT1 activity correlates with the reduced cartilage-specific gene expression evident in these TNFα-treated cells.
We develop a simple mathematical model for forced flow of culture medium through a porous scaffold in a tissue engineering bioreactor. Porous-walled hollow fibres penetrate the scaffold and act as additional sources of culture medium. The model, based on Darcy's law, is used to examine the nutrient and shear stress distributions throughout the scaffold. We consider several configurations of fibres and inlet and outlet pipes. Compared with a numerical solution of the full Navier-Stokes equations within the complex scaffold geometry, the modelling approach is cheap, and does not require knowledge of the detailed microstructure of the particular scaffold being used. The potential of this approach is demonstrated through quantification of the effect the additional flow from the fibres has on the nutrient and shear-stress distribution.
We investigate the growth of a mixing zone in the displacement of oil by a solvent. Such a zone usually takes the form of long thin fingers of solvent which protrude into the oil. However, despite the existence of reasonably good empirical models for the evolution of mixing zones, there is limited theoretical understanding of the observed growth. Of particular interest is the rate at which the leading edge of the mixing zone grows. In this paper we establish the structure of the mixing zone, and reveal a critical mechanism that plays a role in the growth of the leading edge of the mixing zone. It turns out that there is a close link between the growth rate of the mixing zone and a shape selection problem for Saffman–Taylor fingers.
Rock-pore-space geometry and network topology have a great impact on dynamic reservoir characteristics, in particular on capillary pressure and relative permeability curves. Hydraulic tortuosity is a key independent measurement relating the pore-space geometry and topology to the rock's effective porosity and absolute permeability. Therefore, hydraulic tortuosity can be an important concept for dynamic reservoir characterization and reservoir simulation. Our objectives are to recommend a new dynamic rock-typing process and to assess the corresponding improvement on reservoir simulation processes. We introduce an innovative dynamic reservoir-rock-typing (DRRT) index, using absolute permeability, porosity and hydraulic tortuosity data, derived from mercury-injection capillary pressure (MICP) experiments. For correlation purposes, we also derived electric tortuosity data from formation-resistivity experiments. We used the experimental data from the Worldwide Rock Catalog (WWRC) provided by a joint-industry project (Core Lab, 2014), for both carbonate and clastic rocks. Based on the new proposed DRRT index and on corresponding dynamic reservoir properties, we prepared a comprehensive sensitivity study on the impact of hydraulic tortuosity heterogeneity on oil recovery results. This sensitivity study was done by incorporating the concept of hydraulic tortuosity in a synthetic carbonate- reservoir simulation model. The analysis of the MICP and formation-resistivity data showed both greater average tortuosity and greater tortuosity variability for carbonates, when compared with clastic rocks. It also showed good correlation between hydraulic and electric tortuosity values. The sensitivity study results showed a significant impact of hydraulic tortuosity heterogeneity on oil in place and reserves estimates for improved oil recovery (IOR) / enhanced oil recovery (EOR) processes in typical complex carbonate reservoirs, such as the ones found in the Brazilian Pre-Salt. It also showed the importance of applying proper corrections while deriving dynamic reservoir properties from capillary pressure and relative permeability experiments. The new DRRT index shows a much stronger correlation with pore-space geometry when compared with traditional reservoir-quality (RQI) and flow-zone (FZI) indexes. Therefore, it has clear potential to enhance the dynamic rock-typing process for reservoir simulation of IOR / EOR in complex carbonate rocks. We also discuss the importance of an integrated laboratory test and well log program to enable the proper characterization, population, and upscaling of dynamic rock properties. In complex carbonate reservoirs under IOR / EOR, overlooking the rock-pore-space geometry and network topology may result in significant errors in reservoir characterization and simulation processes. In this context, proper DRRT in carbonates, including tortuosity, is therefore crucial for reservoir simulation; enabling correspondence between core, well log and reservoir-scale dynamic properties. The presented correlation between hydraulic and electric tortuosity significantly increases the potential of dielectric measurements for dynamic reservoir characterization of complex carbonates on both core and well log scales.
We present and compare three different grid-based inversion methods for estimation of formation parameters and spatial geological feature identification based on pressure transient test (PTT) data from multiple-well locations. The first and second methods employ efficient adjoint schemes to determine the gradient of the objective functions resulting in the most likely set of reservoir parameters and an ensemble of updated realizations of the parameters, respectively. The second method is based on the Langevin equation. The third method uses ensemble Kalman filtering (EnKF) for data assimilation, in which the outcome is an ensemble of updated parameter realizations. These three methods use a grid-independent prior model (in view of the limited prior knowledge of the system expected to be available), described by as few parameters as possible, and consider a non-uniform grid with the highest resolution near the wells. With these methods, the existence of and location of many sub- seismic features such as strong spatial permeability variations, faults, fractures and pinch outs may be determined using exploration and production data. Such features may not be known a priori, particularly in the exploration of heterogeneous carbonate reservoirs. We examine each method considering the degree of prior information required, the computational overhead and the applicability to the reservoir characterization workflow. Our results indicate that the first method provides a good history match to the observed PTT data and is suited for the early exploration phase of the reservoir. However, the parameters must be convolved with the smaller scale data to produce multiple realizations away from the implausibly smooth most-likely solution. The observed PTT data lies within the ensemble of predicted pressures in the EnKF and Langevin-based methods which are both applicable to probabilistic workflows where uncertainty is treated rigorously. However, EnKF seems to be computationally more efficient than the Langevin approach.
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