Several studies have revealed that cyclin-dependent kinases (CDK) can mediate phosphorylation of steroid receptors at multiple sites, including serine 81 of the androgen receptor (AR). Phosphorylation of S81 is required for AR nuclear translocation, an association with chromatin and also regulates endogenous AR-regulated transcription in response to hormones. Up to date, S81-phosphorylation has been studied using different CDK inhibitors. Nevertheless, most inhibitors are non-selective or have unknown selectivity. We investigated the selectivity of commercially available CDK inhibitors and identified compounds that will be suitable for further studies to identify the CDKs responsible for S81-AR phosphorylation. We confirmed the positive impact of CDK1 and CDK9 on phosphorylation of S81-AR and its transcriptional activity. Although CDK1-mediated phosphorylation was previously shown to occur during mitosis, our experiments did not confirm this finding. By using chemical and genetic inhibition techniques, we identified that CDK2 contributes to S81-AR phosphorylation and transactivation while CDK4 was not shown to be involved in this process.

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ABSTRACT. In short rate models, bond prices and term structures of interest rates are determined by the parameters of the model and the current level of the instantaneous interest rate (so called short rate). The instantaneous interest rate can be approximated by the market overnight, which, however, can be influenced by speculations on the market. The aim of this paper is to propose a calibration method, where we consider the short rate to be a variable unobservable on the market and estimate it together with the model parameters for the case of the Vasicek model.

In this paper we study the convergence model of interest rates by Corzo and Schwartz. It models the situation when a country is going to enter a monetary union, for example the eurozone. We are interested in estimating the underlying short rate, which is a theoretical variable, not observed on the market. We use the procedure already employed for the Vasicek model to the eurozone data and for the case of a zero correlation we show that a similar procedure can be used also for the estimation of the domestic parameters and the short rate values. The assumption of the zero correlation allows us to simplify the optimization problem, but using simulations we show that our algorithm is robust to the specification of the correlation. It estimates the short rate with a high precision also in the original case of a nonzero correlation, as well as in the case of a dynamic correlation, when the correlation is modelled as a function of time. Finally, we use the algorithm to real market data and estimate the short rate before adoption of the euro currency in Slovakia, Estonia, Latvia and Lithuania.

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