Regulation of polyisoprenylated methylated protein methyl esterase by polyunsaturated fatty acids and prostaglandins

Polyisoprenylation is a set of secondary modifications involving proteins whose aberrant activities are implicated in cancers and degenerative disorders. The last step of the pathway involves an ester‐forming polyisoprenylated protein methyl transferase‐ and hydrolytic polyisoprenylated methylated protein methyl esterase (PMPMEase)‐catalyzed reactions. Omega‐3 and omega‐6 PUFAs have been linked with antitumorigeneis and tumorigenesis, respectively. PUFAs are structurally similar to the polyisoprenyl groups and may interfere with polyisoprenylated protein metabolism. It was hypothesized that PUFAs may be more potent inhibitors of PMPMEase than their more polar oxidative metabolites, the prostaglandins. As such, the relative effects of PUFAs and prostaglandins on PMPMEase could explain the association between cyclooxygenase‐2 (COX‐2) expression in tumors, the chemopreventive effects of the non‐steroidal anti‐inflammatory (NSAIDs) COX‐2 inhibitors and PUFAs. PUFAs such as AA, EPA, and DHA inhibited PMPMEase activity with K_i values of 0.12–3.7 µM. The most potent prostaglandin was 63‐fold less potent than AA. The PUFAs were also more effective at inducing neuroblastoma cell death at physiologically equivalent concentrations. The lost PMPMEase activity in AA‐treated degenerating cells was restored by incubating the lysates with COX‐1 or COX‐2. PUFAs may thus be physiological regulators of cell growth and could owe these effects to PMPMEase inhibition. Practical applications: Some PUFAs have been widely reported to have anticancer benefits. However, the molecular mechanisms for these effects are not well understood. The findings in the current paper appear to suggest that inhibition of PMPMEase may underlie their effects. They also imply that the expression of COX‐2 in various tumors may serve to convert the PUFAs into significantly less inhibitory prostaglandins. From these findings, AA and the other PUFAs, rather than being substrates for the synthesis of tumorigenic agents may actually contribute in suppressing cell proliferation. This being congruent with the lower cancer risks associated with long term use of anti‐inflammatory agents, the practical implications will likely include the nutritional and/or therapeutic management of cancer with the goal of maintaining suitable levels of the fatty acids in tissues.     

Coupled acoustic-shell model for experimental study of cell stiffness under acoustophoresis

Under the influence of acoustic radiation force, particles can be trapped and deformed at the pressure node in a microfluidic channel. Based on this principle, the elastic modulus of biological cells can be estimated. In this study, a numerical framework, consisting of a boundary element model for acoustic field and an axisymmetric shell model, is developed to simulate the cell deformation under acoustic radiation force. The boundary element model is used to calculate the radiation traction exerted on the cell surface. The cell membrane deformation due to this traction is simulated by using the axisymmetric shell model. The Young’s moduli of algae and red blood cell membranes are then estimated by comparing the experimental observation with the simulated membrane deformation. It is found that the value of Young’s modulus of the red blood cell membrane is lower than that of algae cell membrane. Furthermore, for both cells, the estimated Young’s moduli are negligible compared to the bulk moduli of the cells reported in the previous studies.     

Der Wertbeitrag von Prozessflexibilität

Promising to cope with increasing demand variety and uncertainty, flexibility in general and process flexibility in particular are becoming ever more desired corporate capabilities. During the last years, the business process management and the production/operations management communities have proposed numerous approaches that investigate how to valuate and determine an appropriate level of process flexibility. Most of these approaches are very restrictive regarding their application domain, neglect characteristics of the involved processes and outputs other than demand and capacity, and do not conduct a thorough economic analysis of process flexibility. Against this backdrop, the authors propose an optimization model that determines an appropriate level of process flexibility in line with the principles of value-based business process management. The model includes demand uncertainty, variability, criticality, and similarity as process characteristics. The paper also reports on the insights gained from applying the optimization model to the coverage switching processes of an insurance broker pool company.     

Evaluation of the mechanical behavior of W7-X central support connections by means of semi-automated FE analysis

The stellarator Wendelstein 7-X is under construction at the Max-Planck-Institut für Plasmaphysik in Greifswald. Its superconducting coil system is fixed by a massive structure. During machine operation the coils exert high forces and moments against each other and the central support structure (CSS). Therefore, the detailed analysis of the coil to CSS connections, the so-called central support elements (CSE), is a critical item. The major details of the design have been frozen; nevertheless, there is still need for detailed analysis of the CSEs due to assembly issues, and later on for exploring operational limits of the machine. These analyses have to be performed quickly, reliably, and shall provide results in a standardized form to enable timely responses to the assembly team. Special numerical tools – finite element (FE) parametric models of CSEs – have been developed for the purpose of such analyses. In the models, the geometry, material properties, contact conditions, loads as well as results presentation are defined in a parametric way. The use of the developed models for the definition of the final weld parameters, bolt preloads, assessment of acceptable tolerances, and optimal positions of the CSE-wedges before welding is also discussed.     

New concepts for lithium minerals processing

A new concept for the enrichment of lithium minerals is offering higher purity and higher yield by applying new processing technologies addressing the specific properties of the pegmatitic host rock. Additional value is created from high quality by-products which will improve the sustainability of mining activity and the overall cost base. Within the new concept, flotation may even be avoided where wet separation techniques are not applicable.Two innovative processing technologies have been integrated in the new concept: electrodynamic fragmentation and optical sorting. Detailed results of lab-technical tests show that the new process design can achieve highly selective liberation and separation processes. Optical and mineralogical analyses of the test products indicate a high benefit for commercial applications.     

Modelling time-varying higher moments with maximum entropy density

Since the introduction of the Autoregressive Conditional Heteroscedasticity (ARCH) model of Engle [R. Engle, Autoregressive conditional heteroscedasticity with estimates of the variance of United Kingdom inflation, Econometrica 50 (1982) 987–1007], the literature of modelling the conditional second moment has become increasingly popular in the last two decades. Many extensions and alternate models of the original ARCH have been proposed in the literature aiming to capture the dynamics of volatility more accurately. Interestingly, the Quasi Maximum Likelihood Estimator (QMLE) with normal density is typically used to estimate the parameters in these models. As such, the higher moments of the underlying distribution are assumed to be the same as those of the normal distribution. However, various studies reveal that the higher moments, such as skewness and kurtosis of the distribution of financial returns are not likely to be the same as the normal distribution, and in some cases, they are not even constant over time. These have significant implications in risk management, especially in the calculation of Value-at-Risk (VaR) which focuses on the negative quantile of the return distribution. Failed to accurately capture the shape of the negative quantile would produce inaccurate measure of risk, and subsequently lead to misleading decision in risk management. This paper proposes a solution to model the distribution of financial returns more accurately by introducing a general framework to model the distribution of financial returns using maximum entropy density (MED). The main advantage of MED is that it provides a general framework to estimate the distribution function directly based on a given set of data, and it provides a convenient framework to model higher order moments up to any arbitrary finite order k. However this flexibility comes with a high cost in computational time as k increases, therefore this paper proposes an alternative model that would reduce computation time substantially. Moreover, the sensitivity of the parameters in the MED with respect to the dynamic changes of moments is derived analytically. This result is important as it relates the dynamic structure of the moments to the parameters in the MED. The usefulness of this approach will be demonstrated using 5 min intra-daily returns of the Euro/USD exchange rate.     

Multicriterion genetic optimization for due date assigned distribution network problems

This paper focuses on the demand due date factor in multiechelon distribution network problems and its impact on the production scheduling in manufacturing plants. A reliable demand due date is critical in winning of customer orders. However, this may usually require high collaboration among entities in the network. Mismatching of one single schedule may seriously influence the reliability. In this connection, holistically optimizing the schedule of each entity among the network is essential. In addition, on time delivery may induce high operating cost. A trade-off between earliness, on time, and tardiness should also be considered. Hence, a multicriterion genetic optimization methodology is developed to holistically optimize them. It determines the optimized schedule to collaborate each entity to fulfill the demands. For enabling multicriterion decision-making, the proposed algorithm combines analytic hierarchy process with genetic algorithms (GAs). The problem is divided into two parts—(i) demand allocation and transportation problem, and (ii) production scheduling problem. The optimization approach is applied to iteratively optimize part (i), and then part (ii). Three experiments have been carried out, and the computation results show that the effect of due date is critical, and the ability of the proposed algorithms in taking trade-off between earliness and tardiness.