Recently, it has been shown that silver nanoparticles (AgNPs) provide a unique approach to the treatment of tumors, especially those of neuroepithelial origin. Thus, the aim of this study was to evaluate the impact of AgNPs on proliferation and activation of the intrinsic apoptotic pathway of glioblastoma multiforme (GBM) cells cultured in an in ovo model. Human GBM cells, line U-87, were placed on chicken embryo chorioallantoic membrane. After 8 days, the tumors were divided into three groups: control (non-treated), treated with colloidal AgNPs (40 μg/ml), and placebo (tumors supplemented with vehicle only). At the end of the experiment, all tumors were isolated.Assessment of cell proliferation and cell apoptosis was estimated by histological, immunohistochemical, and Western blot analyses. The results show that AgNPs can influence GBM growth. AgNPs inhibit proliferation of GBM cells and seem to have proapoptotic properties. Although there were statistically significant differences between control and AgNP groups in the AI and the levels of active caspase 9 and active caspase 3, the level of these proteins in GBM cells treated with AgNPs seems to be on the border between the spontaneous apoptosis and the induced. Our results indicate that the antiproliferative properties of silver nanoparticles overwhelm proapoptotic ones. Further research focused on the cytotoxic effect of AgNPs on tumor and normal cells should be conducted.

Pricing of options plays an important role in the financial industry. Investors knowing how to price derivative contracts quickly and accurately can beat the market. On the other hand market participants constructing their investment strategies with the use of options based on techniques that do not assure the highest computational speed and efficiency are doomed to failure. The aim of the article is to extend the existing methodology of pricing correlation options based on the Fourier transform. The article starts with a presentation of Carr and Madan's concept (Carr & Madan, 1999). Then other methods of pricing options with the use of the Fourier transform are summarized. Finally, a new approach to pricing derivative contracts is derived and then applied to the correlation options.

Many countries are pursuing energy security (ES) in their economies while implementing sustainable development goals (SDGs). Relevant policies may include: (1) access to efficient alternative and preferably renewable energy sources (RESs); and (2) reductions in conventionally obtained energy consumption. As the demand for energy is growing and alternative energy resources are expensive, new ways of financing projects to improve ES are of special interest, e.g., issuing green bonds. In such cases, the obtained funds are allocated to projects that can both improve ES and help to achieve SDGs. The aim of the study was to explore the dependences (in the sense of Granger causality) between the green bond (GB) market, different aspects of sustainable development, as measured by global indicators taken from a family of environmental NASDAQ OMX indices, and ES represented by crude oil prices. The methodology is based on the vector autoregression model. The findings reveal evidence of a short-term dependence between the GB market, ES and the multidimensional nature of sustainable development.

In this paper four methods of calculating characteristic functions and their application to selected stochastic volatility models are considered. The methods applied are based on the assumption that the prices of European calls are evaluated numerically by means of the Gauss-Kronrod quadrature. Such approach is used to investigate computational efficiency of pricing European calls. Particular attention in this matter is paid to the speed of generating theoretical prices of the analyzed contracts.