Cryptococcus is a major fungal pathogen that frequently causes systemic infection in patients with compromised immunity. Glucose, an important signal molecule and the preferred carbon source for Cryptococcus, plays a critical role in fungal development and virulence. Cryptococcus contains more than 50 genes sharing high sequence homology with hexose transporters in Saccharomyces cerevisiae. However, there is no report on their function in glucose sensing or transport. In this study, we investigated two hexose transporter-like proteins (Hxs1 and Hxs2) in Cryptococcus that share the highest sequence identity with the glucose sensors Snf3 and Rgt2 in S. cerevisiae. The expression of HXS1 is repressed by high glucose, while the HXS2 expression is not regulated by glucose. Functional studies showed that Hxs1 is required for fungal resistance to oxidative stress and fungal virulence. The hxs1Δ mutant exhibited a significant reduction in glucose uptake activity, indicating that Hxs1 is required for glucose uptake. Heterologous expression of Cryptococcus HXS1 rendered the S. cerevisiae mutant lacking all 20 hexose transporters a high glucose uptake activity, demonstrating that Hxs1 functions as a glucose transporter. Heterologous expression of HXS1 in the snf3Δ rgt2Δ double mutant did not complement its growth in YPD medium containing the respiration inhibitor antimycin A, suggesting that Hxs1 may not function as a glucose sensor. Taken together, our results demonstrate that Hxs1 is a high-affinity glucose transporter and required for fungal virulence.
This paper investigates the nonlinearities in commodity prices using smooth transition regression (STR) models. The STR model, which is technically a nonlinear model in the conditional mean, is extended to model nonlinearities in the conditional variance equation of the price series. What distinguishes this paper from the majority of the studies in the smooth transition literature is its use of external transition variables, in addition to the standard autoregressive lags of the dependent variable, in modelling the regime switching behavior of commodity prices. Two external transition variables were found successful in capturing the regime switching dynamics of commodity prices: ináation rate and the price of oil. When both variables were used in the STR in mean and the STR in variance models, they displayed the same dynamics in their limiting processes. This result suggests that both models can be seen as substitutes when modelling nonlinearity in the commodity price index. As for the two transition variables, ináation was capable of capturing the early dynamics (between 1900 and 1950) of the commodity index whereas oil 1 price captured the late ones (between 1980 and 2007). This result motivates the use of external threshold variables in regime switching models in general and, in particular, the use of ináation and oil price in the STR model when applied to an index of commodity prices.The paper also provides further insight on the issue of co-movment of commodity prices by classiÖying individual commodities into groups acoording to their border price (an issue that has been ignored in previous studies on commodity prices), and then trying to Önd the best common transition variable that can explain the dynamic behavior of each group.border price classiÖcation is crucial to identify the potential driving variables for individual commodities?The issue of commodity price formation has been studied extensively in the literature. Early theoretical models originate from Gustafsonís (1958) work on the theory of competitive storage and the work of Muth (1961), who introduced the rational expectations assumption in a model of commodity price formation. Both contributions formed the basic model of commodity price formation. Extensions (in di §erent directions) to this basic model can be seen from the work of Samuelson (1971), Danthine (1977), Williams andWright (1991), andDeaton andLaroque (1992). The previously mentioned attempts, elegant as they were, did not succeed in capturing entirely the dynamic behavior of commodity prices.The general conclusion is that commodity prices are nonlinear and this nonlinearity is attributed to the speculative behavior of agents for holding stocks or to unobserved demand and supply shocks. This paper follows a di §erent approach in modelling the dynamics of commodity prices. The approach is empirical in nature and is motivated by the fact that commodity prices tend to move together in groups that can be classiÖed according to the recorded border price of the commodity under considerati...
The objective of this paper is to explain the nonlinear behavior and the observed co-movement in commodity prices. We propose a novel approach of capturing nonlinearity in groups of commodity prices that tend to move together. The approach rests on using the International Commercial Terms (Incoterms), also known as border prices, to classify commodities in groups that tend to have similar dynamics. In each group, we …t an appropriate regime switching model with exogenous transition variable that can capture the nonlinearity of the price processes. We show that the proposed border price classi…cation is (1) the key to …nding the suitable transition variable that is capable of capturing the regime switching in each group, and (2) capable of explaining the observed co-movement in commodity prices.
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