Comparison of Repeated Doses of C-kit-Positive Cardiac Cells versus a Single Equivalent Combined Dose in a Murine Model of Chronic Ischemic Cardiomyopathy

Using a murine model of chronic ischemic cardiomyopathy caused by an old myocardial infarction (MI), we have previously found that three doses of 1 × 10⁶ c-kit positive cardiac cells (CPCs) are more effective than a single dose of 1 × 10⁶ cells. The goal of this study was to determine whether the beneficial effects of three doses of CPCs (1 × 10⁶ cells each) can be fully replicated by a single combined dose of 3 × 10⁶ CPCs. Mice underwent a 60-min coronary occlusion; after 90 days of reperfusion, they received three echo-guided intraventricular infusions at 5-week intervals: (1) vehicle × 3; (2) one combined dose of CPCs (3 × 10⁶) and vehicle × 2; or (3) three doses of CPCs (1 × 10⁶ each). In the combined-dose group, left ventricular ejection fraction (LVEF) improved after the 1st CPC infusion, but not after the 2nd and 3rd (vehicle) infusions. In contrast, in the multiple-dose group, LVEF increased after each CPC infusion; at the final echo, LVEF averaged 35.2 ± 0.6% (p < 0.001 vs. the vehicle group, 27.3 ± 0.2%). At the end of the study, the total cumulative change in EF from pretreatment values was numerically greater in the multiple-dose group (6.6 ± 0.6%) than in the combined-dose group (4.8 ± 0.8%), although the difference was not statistically significant (p = 0.08). Hemodynamic studies showed that several parameters of LV function in the multiple-dose group were numerically greater than in the combined-dose group (p = 0.08 for the difference in LVEF). Compared with vehicle, cardiomyocyte cross-sectional area was reduced only in the multiple-dose group (−32.7%, 182.6 ± 15.1 µm² vs. 271.5 ± 27.2 µm², p < 0.05, in the risk region and −28.5%, 148.5 ± 12.1 µm² vs. 207.6 ± 20.5 µm², p < 0.05, in the noninfarcted region). LV weight/body weight ratio and LV weight/tibia length ratios were significantly reduced in both cell treated groups vs. the vehicle group, indicating the attenuation of LV hypertrophy; however, the lung weight/body weight ratio was significantly reduced only in the multiple-dose group, suggesting decreased pulmonary congestion. Taken together, these results indicate that in mice with chronic ischemic cardiomyopathy, the beneficial effects of three doses of CPCs on LV function and hypertrophy cannot be fully replicated with a single dose, notwithstanding the fact that the total number of cells delivered with one or three doses is the same. Thus, it is the multiplicity of doses, and not the total number of cells, that accounts for the superiority of the repeated-dose paradigm. This study supports the idea that the efficacy of cell therapy in heart failure can be augmented by repeated administrations.     

Release of stored thermochemical energy from dehydrated salts

Thermochemical materials, particularly salt hydrates, have significant potential for use in thermal energy storage applications. When a salt hydrate is heated to a threshold temperature, a chemical reaction is initiated to dissociate it into its anhydrous form and water vapor. The anhydrous salt stores the sensible energy that was supplied for dehydration, which can be later extracted by allowing cooler water or water vapor to flow through the salt, transforming the stored energy into sensible heat. We model the heat release that occurs during a thermochemical hydration reaction using relations for mass and energy conservation, and for chemical kinetics and stoichiometry. A set of physically significant dimensionless parameters reduces the number of design variables. Through a robust sensitivity analysis, we identify those parameters from this group that more significantly influence the performance of the heat release process, namely a modified Damköhler number, the thermochemical heat capacity, and the heat flux and flowrate. There is a strong nonlinear relationship between these parameters and the process efficiency. The optimization of the efficiency with respect to the parameters provides guidance for designing engineering solutions in terms of material selection and system properties.     

Switching through singularities

Asymptotic tracking is studied for systems which are not regular, that is, the relative degree is not well defined. For these systems, the input–output linearizing control law has singularities. We propose a tracking control law which switches between an approximate tracking law (Hauser et al., IEEE Trans. Automat. Control 37 (3) (1992) 392–398) close to the singularities, and an exact tracking law away from the singularities, and we study the applicability of this law based on the behavior of the system’s zero dynamics at the switching boundary. As in Hauser et al. (IEEE Trans. Automat. Control 37 (3) (1992) 392–398), the ball and beam example is used to motivate the study.     

Grandmothers' responsibility in raising two-year olds facilitates their grandchildren's adaptive behavior: A preliminary intrafamilial investigation of mothers' and maternal grandmothers' effects.

To investigate the extent to which the presence of their maternal grandmother might facilitate independent and adaptive responding, 2-year-old children were observed in a novel environment. Although the two-year-olds' extent of exploration and amount of time spent in a playroom were significantly greater when their mother was present than when an unfamiliar person was present, the grandmother's functional characteristics were on an intermediate level between those of the mother and those of the unfamiliar person. However, the more responsibilities that grandmothers reported customarily assuming for their grandchildren, the more similarly the children in the playroom reacted to their mothers and grandmothers. Extended involvement by a sensitive grandmother may enhance her grandchild's relationship with her. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Characterization of a Flip-Flop Metastability Measurement Method

We characterize a proposed metastability measurement system in which asynchronous data input and sampling clock frequencies trigger metastability. We develop an equation describing the time interval between data and clock inputs for practical frequencies and show that it takes on discrete values in the absence of jitter and that the presence of jitter perturbs these values. Finally, we present experimental results supporting our characterization     

An Optimal successive overrelaxtion technique for solving second order finite difference equations for triangular meshes

A finite difference method for analyzing two-dimensional steady-state potential flow in a zoned anisotropic material is described. A triangular mesh is used is as to avoid difficulties often occurring in the more familiar rectangular mesh where fractional mesh spaces exist at irregular boundaries. The system of finite difference equations based on the triangular mesh is assembled in a form such that the coefficient matrix is 3-cylic and consistently ordered.^{1, 2} This enables the optimum accelerating factor for successive overrelaxation to be closely estimated. Since the rate of convergence to the solution, and consequently the efficiency of the method, increases rapidly as the accelerating factor tends towards its optimum value, close determination of the optimum is important. The method is particularly suitable for problems having large numbers of nodes. Examples of the method on specific problems are given. The solution accuracy is assessed and has been found acceptable.     

Quantum annealing for combinatorial clustering

Clustering is a powerful machine learning technique that groups “similar” data points based on their characteristics. Many clustering algorithms work by approximating the minimization of an objective function, namely the sum of within-the-cluster distances between points. The straightforward approach involves examining all the possible assignments of points to each of the clusters. This approach guarantees the solution will be a global minimum; however, the number of possible assignments scales quickly with the number of data points and becomes computationally intractable even for very small datasets. In order to circumvent this issue, cost function minima are found using popular local search-based heuristic approaches such as k-means and hierarchical clustering. Due to their greedy nature, such techniques do not guarantee that a global minimum will be found and can lead to sub-optimal clustering assignments. Other classes of global search-based techniques, such as simulated annealing, tabu search, and genetic algorithms, may offer better quality results but can be too time-consuming to implement. In this work, we describe how quantum annealing can be used to carry out clustering. We map the clustering objective to a quadratic binary optimization problem and discuss two clustering algorithms which are then implemented on commercially available quantum annealing hardware, as well as on a purely classical solver “qbsolv.” The first algorithm assigns N data points to K clusters, and the second one can be used to perform binary clustering in a hierarchical manner. We present our results in the form of benchmarks against well-known k-means clustering and discuss the advantages and disadvantages of the proposed techniques.