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Background/purpose: Osteogenesis imperfecta (OI) is a disease characterized by low bone mass and bony fragility. This study investigated the serum proteomic profiles and their correlation with bone density for OI cases.Methods: Twenty OI patients and 20 control participants were included. Comparative serum proteomic profiles were analyzed by two-dimensional electrophoresis and tandem mass spectrometry. Serum protein levels were measured by enzyme-linked immunosorbent assay. Cutoff values and areas under the curve were estimated by the receiver operating characteristic curve. Bone mineral density data was obtained from all OI patients.Results: Candidate proteins identified by electrophoresis were complement component C3 (C3), vitamin D-binding protein (DBP), and haptoglobin (HP). Enzyme-linked immunosorbent assay validation showed that OI patients had decreased C3 and DBP and increased HP. The results were not affected by age or bisphosphonate use. Serum C3 levels significantly correlated with bone mineral density of the lumbar spine and hip. C3 had the greatest areas under the curve to distinguish OI from healthy controls.Conclusion: Serum C3, DBP, and HP are emerging serologic signatures for OI. Concentrations of serum C3 correlated with the T score of OI patients. C3 had the greatest areas under the curve of the three proteins to distinguish OI from healthy controls. [ABSTRACT FROM AUTHOR]

Objectives: Shock waves have been shown to induce recruitment of intravenously injected endothelial progenitor cells to ischemic hind limbs in rats. We hypothesized that shock wave treatment as sole therapy would induce angiogenesis in this ischemia model and would lead to mobilization of endogenous endothelial (progenitor) cells. Methods: A total of 18 rats, aged 5 weeks old, were subdivided into 3 groups: sham (n = 6), ischemic muscle with shock wave treatment (shock wave treatment group, n = 6), and without shock wave treatment (control, n = 6). Hind limb ischemia was induced by ligation of the femoral artery. Three weeks later, shock wave treatment (300 impulses at 0.1 mJ/mm2) was applied to the adductor muscle; the controls were left untreated. Muscle samples were analyzed using real-time polymerase chain reaction for angiogenic factors and chemoattractants for endothelial progenitor cell mobilization. Fluorescence activated cell sorting analysis of the peripheral blood was performed for CD31/CD34-positive cells. Perfusion was measured using laser Doppler imaging. Functional improvement was evaluated by walking analysis. Results: Angiogenic factors/endothelial progenitor cell chemoattractants, stromal cell-derived factor-1 and vascular endothelial growth factor, were increased in the treatment group, as shown by real-time polymerase chain reaction, indicating the mobilization of endothelial progenitor cells. Fluorescence activated cell sorting analysis of the peripheral blood revealed high numbers of CD31/CD34-positive cells in the treatment group. Greater numbers of capillaries were found in the treated muscles. Blood perfusion increased markedly in the treatment group and led to functional restoration, as shown by the results from the walking analysis. Conclusions: Shock wave therapy therefore could develop into a feasible alternative to stem cell therapy in regenerative medicine, in particular for ischemic heart and limb disease. [Copyright &y& Elsevier]

Abstract: In this study, we considered a multi-stage integrated extractive fermentation with cell recycling for ethanol production using the genetically engineered Sacchromyces yeast 1400 (pLNH33), which can utilize glucose and xylose as carbon sources to produce ethanol. Each stage consists of a stirred-tank bioreactor, a cell settler and an extractor. A generalized mathematical model was formulated to express the multi-stage integrated process. The aim of the optimization problem was to obtain the maximum overall productivity and conversions subject to the interval inequality constraints for the residual glucose and xylose concentrations and the total sugar supply. A fuzzy goal attainment method was applied to the multiobjective problem in order to achieve the maximum satisfaction for all design requirements. From the computational results, the integrated extractive fermentation with cell recycling (involving the extraction of ethanol from the extractor in situ to alleviate product inhibition) led to an optimal overall productivity that was 8.0% higher than that obtained by the method of continuous fermentation with cell recycling, and about 13-fold higher than that obtained by the method of continuous fermentation without cell recycling. [Copyright &y& Elsevier]

Abstract: Problems of parameter estimation of nonlinear bioreaction systems are in general formulated as function optimization problems and are known to be frequently ill-conditioned and multimodal. While the optimization problems are defined on a large parameter search space, only few evolutionary algorithms are able to find a global solution to the large parameter search problem. In this study, a geometric mean mutation was embedded to hybrid differential evolution to replace a gene of the selected individual outside the assigned region. The replaced individuals were then applied to a differential mutation strategy to yield a perturbed individual. The benefit of using a large parameter search space to an inverse problem is to reduce the kinetic model complexity to yield a more compact formulation. Two inverse problems and twelve static benchmark problems with the large parameter search space are employed to illustrate the effectiveness of the proposed method. [Copyright &y& Elsevier]

In this study, crisp and fuzzy multiple-goal optimization approaches are respectively introduced to design an optimal biocompatible solvent to a two-stage extractive fermentation with cell recycling for ethanol production. When designing a biocompatible solvent for the extractive fermentation process, many issues, such as extractive efficiency, conversion, amount of solvent utilized and so on, have to be considered. An interactive multiple-goal design procedure is introduced to determine a trade-off result in order to satisfy such contradicted goals. Both approaches could be iterated to solve the interactive multiple-goal design problem in order to yield a trade-off result. However, the crisp optimization design is a tedious task that requires the designer to provide various pairs of the upper bounds for the design problem to obtain the corresponding solution. The fuzzy optimization approach is able to be trade-off several goals simultaneously and to yield the overall satisfactory grade for the product/process design problem. [Copyright &y& Elsevier]

In this study, crisp and flexible optimization approaches are, respectively, introduced to design an optimal biocompatible solvent for an extractive fermentation process. The optimal design problem is formulated as a mixed-integer nonlinear programming model in which performance requirements of the compounds are reflected in the objective and the constraints. In general, the requirements for the objective and constraints are not rigid; consequently, the flexible or fuzzy optimization approach is applied to soften the rigid requirement for maximization of the extraction efficiency and to consider the mass flow rate and biocompatibility of solvent as the softened inequality constraints to the solvent design problem. Having elicited the membership function for the objective function and the constraint, the optimal solvent design problem can be formulated as a flexible goal attainment problem. Mixed-integer hybrid differential evolution is applied to solve the problem in order to find a satisfactory design. [Copyright &y& Elsevier]

In this study, we consider a two-stage fermenter with cell recycling including an extractor to produce lactic acid. When the extractor was omitted, the proposed process was simplified to two special processes. Under the same operating conditions, we compared the overall lactic acid productivity and glucose conversion for the three processes. The proposed fermentation process was more efficient than the other processes. To simultaneously obtain the maximum productivity and conversion, the problem is formulated as a fuzzy multiobjective optimization problem. The fuzzy decision is introduced to convert the multiobjective fuzzy optimization problem into the fuzzy goal attainment problem. Hybrid differential evolution is applied to solve the fuzzy goal attainment problem to obtain a global Pareto solution. [Copyright &y& Elsevier]

In this study, we have introduced a fuzzy decision-making approach to design a multi-objective optimal design problem of a multiproduct batch chemical plant. In the crisp decision-making approach, the designer is first to solve the multi-objective optimization problem, and then to check whether each optimal objective function value satisfies the rigid preference goal. In real world application, the preference goal for each objective function is an interval bound not a rigid value so that the problem becomes a fuzzy goal optimization problem. A monotonic increasing or decreasing membership function is used to define the degree of satisfaction for each objective function so that the fuzzy goal optimization problem is then represented as an augmented minimax problem formulated as mixed-integer nonlinear programming (MINLP) models. To obtain a unique solution, we have introduced the mixed-integer hybrid differential evolution (MIHDE) to solve the MINLP problems. The MIHDE can straightforwardly solve the problem without any mathematical model transformation. Two examples were used to illustrate the applicability of the proposed interactive algorithm. [Copyright &y& Elsevier]

In this paper, mixed-integer hybrid differential evolution (MIHDE) is developed to deal with the mixed-integer optimization problems. This hybrid algorithm contains the migration operation to avoid candidate individuals clustering together. We introduce the population diversity measure to inspect when the migration operation should be performed so that the user can use a smaller population size to obtain a global solution. A mixed coding representation and a rounding operation are introduced in MIHDE so that the hybrid algorithm is not only used to solve the mixed-integer nonlinear optimization problems, but also used to solve the real and integer nonlinear optimization problems. Some numerical examples are tested to illustrate the performance of the proposed algorithm. Numerical examples show that the proposed algorithm converges to better solutions than the conventional genetic algorithms. [Copyright &y& Elsevier]