Brief episodes of ischemia and reperfusion render the myocardium more resistant to necrosis from a subsequent, otherwise lethal ischemic insult. This phenomenon is called ischemic preconditioning(IP). Today, much is known about the signalling pathways involved in IP; however, the details of the final steps leading to cardioprotection, remain elusive. Adenosine (a catabolite of ATP) plays a major role in the signalling pathways of IP. Following IP there is an unexplained discrepancy between an increased adenosine production (evidenced by increased 5’-nucleotidase activity) and the successively lower adenosine levels observed in the interstitial space. We propose that this discrepancy in adenosine production vs. availability may be due to an increased metabolic utilisation of adenosine by the IP myocardium. According to our hypothesis, IP induces/activates a metabolic pathway involving deamination of adenosine to inosine. Inosine is further catalysed (in presence of Pi) to hypoxanthine and ribose-1-phosphate. Ribose-1-phosphate can be converted to ribose-5-phosphate in a phosphoribomutase reaction. Ribose-5-phosphate is an intermediate of the hexose monophosphate pathway also operative under anaerobic conditions. Hence the ribose moiety of adenosine can be utilised to generate pyruvate and ultimately ATP (via lactate formation) n.b. without any initial ATP investment. Such cost-effective adenosine utilisation may at least partly explain the cardioprotective effect of IP. Objectives & Methods: In the current studies we investigated the role of adenosine metabolism according to the suggested metabolic pathway by addition of adenosine and inhibition of its metabolism during IP as well as by comparing tissue and interstitial levels of key energy-metabolites following different protocols of IP. Furthermore, we studied the importance of the IP protocol with regard to the number of ischemia and reperfusion cycles for the cardioprotective effect of IP. In addition, the validity of the microdialysis technique for experimental in vivo studies of myocardial energy metabolism was evaluated. For these purposes the microdialysis technique, tissue biopsies, and planimetric infarct size estimation in an open chest porcine heart-model was used. Results: Addition of adenosine via microdialysis probes enhanced the interstitial release of inosine, hypoxanthine and lactate in the myocardium of IP-subjects during prolonged ischemia. This finding did not occur in non-preconditioned subjects. Similar addition of deoxyadenosine a non-metabolizable adenosine receptor-agonist, did not evoke the same metabolic response. Purine nucleoside phosphorylase (PNP) is responsible for the conversion of inosine to hypoxanthine being a key enzyme in the above mentioned metabolic pathway. Inclusion of 8' aminoguanosine (a competitive inhibitor of PNP) decreased interstitial hypoxanthine release (as a token of PNP inhibition) and increased the release of taurine (marker of cellular injury) in the ischemic IP myocardium. Addition of inosine (a natural substrate of PNP) reverted these changes. Four IP cycles protected the heart more than one IP cycle as evidenced by morphometric and energy-metabolic data.Proportionally more hypoxanthine was found in the myocardium of IP subjects during prolonged ischemia. The ratio of tissue levels of inosine/hypoxanthine (used as an indicator of PNP activity) was significantly smaller in the IP groups. In addition, myocardial interstitial levels of energy-related metabolites (lactate, adenosine, inosine, and hypoxanthine) obtained by the microdialysis technique correlated with tissue biopsy levels of corresponding metabolites. Conclusions: IP activated a metabolic pathway favouring metabolism of exogenous adenosine to inosine, hypoxanthine and eventually lactate. Inhibition of adenosine metabolism following IP (via inhibition of PNP-activity resulted in enhanced cellular injury. PNP-activity is proportionally higher in IP-myocardium. Metabolic utilisation of adenosine in IP-myocardium (as outlined above) may represent a costeffective way to produce ATP and at least partly explain the cardioprotective effect of IP. IP protects the myocardium in a graded fashion. Furthermore, we confirmed the validity of the microdialysis technique (in the current setting) for studying dynamic changes of myocardial energy metabolism.

This thesis deals with the problems of scaling aerodynamic data from wind tunnel to free flight  conditions. The main challenges when this scaling should be performed is how the model support, wall interference and the potentially lower Reynolds number in the windtunnel should be corrected. Computational Fluid Dynamics (CFD) simulations have been performed on a modern transonic transport aircraft in order to reveal Reynolds number effects and how these should be scaled accurately. A methodology for scaling drag and identifying scaling effects in general is presented.  This investigation also examines how the European Transonic Wind tunnel twin sting model support influences the flow over the aircraft. When the Reynolds number is differing between the wind tunnel and free flight conditions, a change in boundary layer transition position can occur. In order to estimate first order boundary layer transition effects a correlation based transition prediction method, previously presented by Menter and Langtry, is implemented in the CFD solver Edge. The transition model is further developed and a novel set of equations for the production terms is found through a CFD/optimizer coupling. The transition data, used to calibrate the CFD transition model,  have been extracted from a low Mach number wind tunnel campaign. At these low Mach numbers many compressible CFD solvers suffer of poor convergence rates and a deficiency in robustness and accuracy might appear. The low Mach number effects are investigated, and an effort to prevent these is done by implementing different preconditioning techniques in the compressible CFD solver Edge. The preconditioners are mainly based on the general Turkel preconditioner, but a novel formulation is also presented in order to make the numerical technique less problem dependent. / QC 20100903

Objective: Ischemic spinal cord injury is a serious complication of aortic surgery. The mechanism underlying ischemic preconditioning (IPC) protection against spinal cord ischemia/reperfusion (I/R) injury is unclear. We investigated the role of spinal cord autoregulation in tolerance to spinal cord I/R injury induced by IPC. Although the extracellular signal-regulated kinases 1 and 2 (ERK1/2) are generally regarded as related to cell survival and proliferation, increasing evidence suggests that the role of the ERK1/2 pathway in I/R injury is contributory to inflammation. We investigated the effect of blocking ERK1/2 pathway to inhibit inflammation reaction in tolerance to spinal cord I/R injury. Methods: In the part 1 study, Sprague-Dawley rats were randomly assigned to 4 groups. IPC (P) group animals received IPC by temporary thoracic aortic occlusion (AO) with a 2-F Fogarty arterial embolectomy catheter for 3 min. I/R injury (I/R) group animals were treated with blood withdrawal and temporary AO for 12 min, and shed blood reinfusion at the end of the procedures. (P+I/R) group animals received IPC, followed by 5 min reperfusion, and then I/R procedures for 12 min. Sham (S) group animals received anesthesia and underwent surgical preparation only. Neurological functions were evaluated, and lumbar segments were harvested for histopathological examination. To evaluate the role of autoregulation in IPC, spinal cord blood flow and tissue oxygenation were continuously monitored throughout the procedure duration. In the part 2 study, spinal cord ischemia rats was induced by occluding the thoracic descending aorta with a balloon catheter introduced through a femoral artery, accompanied by concomitant exsanguinations. Rats in the control group were given dimethyl sulfoxide (vehicle) before undergoing spinal cord ischemia/reperfusion injury. In the U0126-treated group, rats were pretreated with an inhibitor of ERK1/2, U0126, to inhibit ERK1/2 phosphorylation. The sham rats underwent aortic catheterization without occlusion. Parameters, including neurologic status, neuronal survival, inflammatory cell infiltration, and interleukin-1£] production in the spinal cords, were compared between groups. Results: The Tarlov scores in the (I/R) group were significantly lower than those in the (S), (P), and (P+I/R) groups on days 1, 3, 5, and 7. The numbers of surviving motor neurons in the (S), (P), and (P+I/R) groups were significantly higher than those in the (I/R) group. The (P) group exhibited higher spinal cord blood flow and tissue oxygenation after reperfusion than the (S) group. The (P+I/R) group exhibited higher spinal cord blood flow and tissue oxygenation within the first 60 min after reperfusion than the (I/R) groups. In the part 2 study, early ERK1/2 phosphorylation was observed after injury in the control group, followed by abundant microglial accumulation in the infarct area and increased interleukin-1£] expression. In the U0126 group, U0126 treatment completely blocked ERK1/2 phosphorylation. Microglial activation and spinal cord interleukin-1£] levels were significantly reduced. Neuronal survival and functional performance were improved. Conclusions: IPC ameliorates spinal cord I/R injury in rats, probably mediated by triggering spinal cord autoregulation and improving local spinal cord blood flow and tissue oxygenation. The ERK1/2 pathway may play a noxious role in spinal cord ischemia/reperfusion injury by participating in inflammatory reactions and cytokine production. According to our findings, these concepts may be the new therapeutic targets in patients requiring aortic surgery.

A relatively new preconditioning technique called support graph preconditioning has many merits over the traditional incomplete factorization based methods. A major limitation of this technique is that it is applicable to symmetric diagonally dominant matrices only. This work presents a technique that can be used to transform the symmetric positive definite matrices arising from elliptic finite element problems into symmetric diagonally dominant M-matrices. The basic idea is to approximate the element gradient matrix by taking the gradients along chosen edges, whose unit vectors form a new coordinate system. For Lagrangian elements, the rows of the element gradient matrix in this new coordinate system are scaled edge vectors, thus a diagonally dominant symmetric semidefinite M-matrix can be generated to approximate the element stiffness matrix. Depending on the element type, one or more such coordinate systems are required to obtain a global nonsingular M-matrix. Since such approximation takes place at the element level, the degradation in the quality of the preconditioner is only a small constant factor independent of the size of the problem. This technique of element coordinate transformations applies to a variety of first order Lagrangian elements. Combination of this technique and other techniques enables us to construct an M-matrix preconditioner for a wide range of second order elliptic problems even with higher order elements. Another contribution of this work is the proposal of a new variant of Vaidya’s support graph preconditioning technique called modified domain partitioned support graph preconditioners. Numerical experiments are conducted for various second order elliptic finite element problems, along with performance comparison to the incomplete factorization based preconditioners. Results show that these support graph preconditioners are superior when solving ill-conditioned problems. In addition, the domain partition feature provides inherent parallelism, and initial experiments show a good potential of parallelization and scalability of these preconditioners.

Elliptic partial differential equations that are used to model physical phenomena give rise to large sparse linear systems. Such systems can be symmetric positive definite and can be solved by the preconditioned conjugate gradients method. In this thesis, we develop support graph preconditioners for symmetric positive definite matrices that arise from the finite element discretization of elliptic partial differential equations. An object oriented code is developed for the construction, integration and application of these preconditioners. Experimental results show that the advantages of support graph preconditioners are retained in the proposed extension to the finite element matrices.

Fast and accurate solvers for capacitance extraction are needed by the VLSI industry in order to achieve good design quality in feasible time. With the development of technology, this demand is increasing dramatically. Three-dimensional capacitance extraction algorithms are desired due to their high accuracy. However, the present 3D algorithms are slow and thus their application is limited. In this dissertation, we present several novel techniques to significantly speed up capacitance extraction algorithms based on boundary element methods (BEM) and to compute the capacitance extraction in the presence of floating dummy conductors. We propose the PHiCap algorithm, which is based on a hierarchical refinement algorithm and the wavelet transform. Unlike traditional algorithms which result in dense linear systems, PHiCap converts the coefficient matrix in capacitance extraction problems to a sparse linear system. PHiCap solves the sparse linear system iteratively, with much faster convergence, using an efficient preconditioning technique. We also propose a variant of PHiCap in which the capacitances are solved for directly from a very small linear system. This small system is derived from the original large linear system by reordering the wavelet basis functions and computing an approximate LU factorization. We named the algorithm RedCap. To our knowledge, RedCap is the first capacitance extraction algorithm based on BEM that uses a direct method to solve a reduced linear system. In the presence of floating dummy conductors, the equivalent capacitances among regular conductors are required. For floating dummy conductors, the potential is unknown and the total charge is zero. We embed these requirements into the extraction linear system. Thus, the equivalent capacitance matrix is solved directly. The number of system solves needed is equal to the number of regular conductors. Based on a sensitivity analysis, we propose the selective coefficient enhancement method for increasing the accuracy of selected coupling or self-capacitances with only a small increase in the overall computation time. This method is desirable for applications, such as crosstalk and signal integrity analysis, where the coupling capacitances between some conductors needs high accuracy. We also propose the variable order multipole method which enhances the overall accuracy without raising the overall multipole expansion order. Finally, we apply the multigrid method to capacitance extraction to solve the linear system faster. We present experimental results to show that the techniques are significantly more efficient in comparison to existing techniques.

In VLSI circuits, signal delays play an important role in design, timing verification and signal integrity checks. These delays are attributed to the presence of parasitic resistance, capacitance and inductance. With increasing clock speed and reducing feature sizes, these delays will be dominated by parasitic inductance. In the next generation VLSI circuits, with more than millions of components and interconnect segments, fast and accurate inductance estimation becomes a crucial step. A generalized approach for inductance extraction requires the solution of a large, dense, complex linear system that models mutual inductive effects among circuit elements. Iterative methods are used to solve the system without explicit computation of the system matrix itself. Fast hierarchical techniques are used to compute approximate matrix-vector products with the dense system matrix in a matrix-free way. Due to unavailability of system matrix, constructing a preconditioner to accelerate the convergence of the iterative method becomes a challenging task. This work presents a class of parallel algorithms for fast and accurate inductance extraction of VLSI circuits. We use the solenoidal basis approach that converts the linear system into a reduced system. The reduced system of equations is solved by a preconditioned iterative solver that uses fast hierarchical methods to compute products with the dense coefficient matrix. A Green’s function based preconditioner is proposed that achieves near-optimal convergence rates in several cases. By formulating the preconditioner as a dense matrix similar to the coefficient matrix, we are able to use fast hierarchical methods for the preconditioning step as well. Experiments on a number of benchmark problems highlight the efficient preconditioning scheme and its advantages over FastHenry. To further reduce the solution time of the software, we have developed a parallel implementation. The parallel software package is capable of analyzing interconnects con- figurations involving several conductors within reasonable time. A two-tier parallelization scheme enables mixed mode parallelization, which uses both OpenMP and MPI directives. The parallel performance of the software is demonstrated through experiments on the IBM p690 and AMD Linux clusters. These experiments highlight the portability and efficiency of the software on multiprocessors with shared, distributed, and distributed-shared memory architectures.

Sarcolemmal chloride channels and associated cell volume regulatory pathways have been shown to be important in local ischemic preconditioning (IPC) induced protection against myocardial ischemia/reperfusion injury. Similarities between intracellular pathways in remote (rIPC) and classic IPC suggest that these mechanisms may also play an important role in rIPC. rIPC protected cultured rabbit ventricular cardiomyocytes against necrosis caused by 75 minutes simulated ischemia followed by 60 minutes simulated reperfusion. The protective effect was abolished by chloride channel blockade using 50 μM indanyloxyacetic acid 94 (IAA-94). rIPC also reduced peak cardiomyocyte swelling during exposure to 200 mOsm hypo-osmotic buffer. The reduction in peak swelling was also abolished by IAA-94. These results suggest that the protective effect of rIPC is achieved, at least in part, by enhancing cell volume regulation and that this effect is dependent on the availability of chloride channels in a similar fashion to local IPC.

Sarcolemmal chloride channels and associated cell volume regulatory pathways have been shown to be important in local ischemic preconditioning (IPC) induced protection against myocardial ischemia/reperfusion injury. Similarities between intracellular pathways in remote (rIPC) and classic IPC suggest that these mechanisms may also play an important role in rIPC. rIPC protected cultured rabbit ventricular cardiomyocytes against necrosis caused by 75 minutes simulated ischemia followed by 60 minutes simulated reperfusion. The protective effect was abolished by chloride channel blockade using 50 μM indanyloxyacetic acid 94 (IAA-94). rIPC also reduced peak cardiomyocyte swelling during exposure to 200 mOsm hypo-osmotic buffer. The reduction in peak swelling was also abolished by IAA-94. These results suggest that the protective effect of rIPC is achieved, at least in part, by enhancing cell volume regulation and that this effect is dependent on the availability of chloride channels in a similar fashion to local IPC.

An investigation of preconditioning techniques is presented for a Newton--Krylov algorithm that is used for the computation of steady, compressible, high Reynolds number flows about airfoils. A second-order centred-difference method is used to discretize the compressible Navier--Stokes (NS) equations that govern the fluid flow. The one-equation Spalart--Allmaras turbulence model is used. The discretized equations are solved using Newton's method and the generalized minimal residual (GMRES) Krylov subspace method is used to approximately solve the linear system. These preconditioning techniques are first applied to the solution of the discretized steady convection-diffusion equation. Various orderings, iterative block incomplete LU (BILU) preconditioning and multigrid preconditioning are explored. The baseline preconditioner is a BILU factorization of a lower-order discretization of the system matrix in the Newton linearization. An ordering based on the minimum discarded fill (MDF) ordering is developed and compared to the widely popular reverse Cuthill--McKee ordering. An evolutionary algorithm is used to investigate and enhance this ordering. For the convection-diffusion equation, the MDF-based ordering performs well and RCM is superior for the NS equations. Experiments for inviscid, laminar and turbulent cases are presented to show the effectiveness of iterative BILU preconditioning in terms of reducing the number of GMRES iterations, and hence the memory requirements of the Newton--Krylov algorithm. Multigrid preconditioning also reduces the number of GMRES iterations. The framework for the iterative BILU and BILU-smoothed multigrid preconditioning algorithms is presented in detail.