A Dynamic Model of Interactions of Ca^(2+), Calmodulin, and Catalytic Subunits of Ca^(2+)/Calmodulin-Dependent Protein Kinase II

During the acquisition of memories, influx of Ca^(2+) into the postsynaptic spine through the pores of activated N-methyl-D-aspartate-type glutamate receptors triggers processes that change the strength of excitatory synapses. The pattern of Ca^(2+) influx during the first few seconds of activity is interpreted within the Ca^(2+)-dependent signaling network such that synaptic strength is eventually either potentiated or depressed. Many of the critical signaling enzymes that control synaptic plasticity, including Ca^(2+)/calmodulin-dependent protein kinase II (CaMKII), are regulated by calmodulin, a small protein that can bind up to 4 Ca^(2+) ions. As a first step toward clarifying how the Ca^(2+)-signaling network decides between potentiation or depression, we have created a kinetic model of the interactions of Ca^(2+), calmodulin, and CaMKII that represents our best understanding of the dynamics of these interactions under conditions that resemble those in a postsynaptic spine. We constrained parameters of the model from data in the literature, or from our own measurements, and then predicted time courses of activation and autophosphorylation of CaMKII under a variety of conditions. Simulations showed that species of calmodulin with fewer than four bound Ca^(2+) play a significant role in activation of CaMKII in the physiological regime, supporting the notion that processing ofCa^(2+) signals in a spine involves competition among target enzymes for binding to unsaturated species of CaM in an environment in which the concentration of Ca^(2+) is fluctuating rapidly. Indeed, we showed that dependence of activation on the frequency of Ca^(2+) transients arises from the kinetics of interaction of fluctuating Ca^(2+) with calmodulin/CaMKII complexes. We used parameter sensitivity analysis to identify which parameters will be most beneficial to measure more carefully to improve the accuracy of predictions. This model provides a quantitative base from which to build more complex dynamic models of postsynaptic signal transduction during learning

Continuous immobilized yeast reactor system for complete beer fermentation using spent grains and corncobs as carrier materials

Despite extensive research carried out in the last few decades, continuous beer fermentation has not yet managed to outperform the traditional batch technology. An industrial breakthrough in favour of continuous brewing using immobilized yeast could be expected only on achievement of the following process characteristics: simple design, low investment costs, flexible operation, effective process control and good product quality. The application of cheap carrier materials of by-product origin could significantly lower the investment costs of continuous fermentation systems. This work deals with a complete continuous beer fermentation system consisting of a main fermentation reactor (gas-lift) and a maturation reactor (packedbed) containing yeast immobilized on spent grains and corncobs, respectively. The suitability of cheap carrier materials for long-term continuous brewing was proved. It was found that by fine tuning of process parameters (residence time, aeration) it was possible to adjust the flavour profile of the final product. Consumers considered the continuously fermented beer to be of a regular quality. Analytical and sensorial profiles of both continuously and batch fermented beers were compared.(Fundação de Amparo a Pesquisa do Estado de São Paulo, Brazil (FAPESPFundação para a Ciência e a Tecnologia (FC

Hypothyroidism Enhances Tumor Invasiveness and Metastasis Development

11 pages, 9 figures.[Background]: Whereas there is increasing evidence that loss of expression and/or function of the thyroid hormone receptors (TRs) could result in a selective advantage for tumor development, the relationship between thyroid hormone levels and human cancer is a controversial issue. It has been reported that hypothyroidism might be a possible risk factor for liver and breast cancer in humans, but a lower incidence of breast carcinoma has been also reported in hypothyroid patients [Methodology/Principal Findings]: In this work we have analyzed the influence of hypothyroidism on tumor progression and metastasis development using xenografts of parental and TRβ1–expressing human hepatocarcinoma (SK-hep1) and breast cancer cells (MDA-MB-468). In agreement with our previous observations tumor invasiveness and metastasis formation was strongly repressed when TRβ–expressing cells were injected into euthyroid nude mice. Whereas tumor growth was retarded when cells were inoculated into hypothyroid hosts, tumors had a more mesenchymal phenotype, were more invasive and metastatic growth was enhanced. Increased aggressiveness and tumor growth retardation was also observed with parental cells that do not express TRs. [Conclusions/Significance]: These results show that changes in the stromal cells secondary to host hypothyroidism can modulate tumor progression and metastatic growth independently of the presence of TRs on the tumor cells. On the other hand, the finding that hypothyroidism can affect differentially tumor growth and invasiveness can contribute to the explanation of the confounding reports on the influence of thyroidal status in human cancer.This work was supported by grants BFU2007-62402 from MEC; RD06/0020/0036 from FIS and from the EU Project CRESCENDO (FP6-018652.Peer reviewe

TWIST1 Is Expressed in Colorectal Carcinomas and Predicts Patient Survival

TWIST1 is a transcription factor that belongs to the family of basic helix-loop-helix proteins involved in epithelial-to-mesenchymal transition and invasion processes. The TWIST1 protein possesses oncogenic, drug-resistant, angiogenic and invasive properties, and has been related with several human tumors and other pathologies. Colorectal cancer is one of the tumors in which TWIST1 is over-expressed, but its involvement in the clinical outcome of the disease is still unclear. We tested, by RT-PCR, the expression levels of TWIST1 in normal and tumor paired-sample tissues from a series of 151 colorectal cancer patients, in order to investigate its prognostic value as a tumor marker. TWIST1 expression was restricted to tumor tissues (86.1%) and correlated with lymph node metastasis (LNM). Adjusted analysis showed that the expression levels of TWIST1 correlated with overall survival (OS) and disease-free survival (DFS). Importantly, TWIST1 expression levels predicted OS specifically at stages I and II. Moreover, patients with stage II tumors and high TWIST1 levels showed even shorter survival than patients with stage III tumors. These results suggest that TWIST1 expression levels could be a tumor indicator in stage II patients and help select patients at greater risk of poor prognosis who might benefit from adjuvant chemotherapy

Refining value-at-risk estimates using a Bayesian Markov-switching GJR-GARCH copula-EVT model

In this paper, we propose a model for forecasting Value-at-Risk (VaR) using a Bayesian Markov-switching GJR-GARCH(1,1) model with skewed Student’s-t innovation, copula functions and extreme value theory. A Bayesian Markov-switching GJR-GARCH(1,1) model that identifies non-constant volatility over time and allows the GARCH parameters to vary over time following a Markov process, is combined with copula functions and EVT to formulate the Bayesian Markov-switching GJR-GARCH(1,1) copula-EVT VaR model, which is then used to forecast the level of risk on financial asset returns. We further propose a new method for threshold selection in EVT analysis, which we term the hybrid method. Empirical and back-testing results show that the proposed VaR models capture VaR reasonably well in periods of calm and in periods of crisis

Design of agile supply chains including analysing the trade-off between number of partners and reliability

The reliability of supply partners is particularly vital in agile supply chains as it is vulnerable to the inability of a supply partner to meet its high responsiveness and flexibility requirements resulting in the disruption of the whole network. Disruption can have expensive and extensive results for the entire agile supply chain. To mitigate the risk of disruption and improve the reliability of the whole agile supply chain, decision-makers need to pay more attention to supply chain design and construction, whilst simultaneously taking into account the sourcing strategy decisions. This paper proposes a series of models for the design of agile supply chains using dynamic programming modelling. These provide decision-makers with a systematic way of analysing one of the key decisions of sourcing strategy, namely the trade-off between the number of supply partners and reliability. The efficacy of the models is demonstrated through their application to a Chinese bus and coach manufacturer by way of an empirical illustration. The results show that this approach is effective for this application and it can be applied in other related decision-making scenarios. The methods offered in this paper provide managers with a practical tool to design their agile supply chains while considering the trade-offs between the number of partners and the reliability of the entire agile supply chain