Melanin content in melanoma metastases affects the outcome of radiotherapy

The COVID-19 pandemic has impacted religion and faith in different ways. Numerous restrictions have been implemented worldwide. Believers are in conflict with authorities’ warnings that gatherings must be limited to combat the spread of the virus. Religion has always played a role of the balm for the soul, and the regular religious participation is associated with better emotional health outcomes. In our study, we examined whether the exposure to COVID-19 enhances the faith. The instrument used was a survey verifying the power of spirituality in the face of the coronavirus pandemic.

The paper presents a comprehensive overview of the use of artificial intelligence (AI) systems in drug design. Neural networks, which are one of the systems employed in AI, are used to identify chemical structures that can have medical relevance. Successful training of neural networks must be preceded by the acquisition of relevant information about chemical compounds, functional groups, and their possible biological activity. In general, a neural network requires a large set of training data, which must contain information about the chemical structure–biological activity relationship. The data can come from experimental measurements, but can also be generated using appropriate quantum models. In many of the studies presented below, authors showed a significant potential of neural networks to produce generalizations based on even relatively narrow training data. Despite the fact that neural network systems have been known for more than 40 years, it is only recently that they have seen rapid development due to the wider availability of computing power. In recent years, there has been a growing interest in deep learning techniques, bringing network modeling to a new level of abstraction. Deep learning allows combining what seems to be causally distant phenomena and effects, and to associate facts in a way resembling the human mind.This article is categorized under: Computer and Information Science > Chemoinformatics

The development of anticancer therapies that involve natural drugs has undergone exponential growth in recent years. Among the natural compounds that produce beneficial effects on human health, polyphenols have shown potential therapeutic applications in cancer due to their protective functions in plants, their use as food additives, and their excellent antioxidant properties. The possibility of combining conventional drugs—which are usually more aggressive than natural compounds—with polyphenols offers very valuable advantages such as the building of more efficient anticancer therapies with less side effects on human health. This review shows a wide range of trials in which polyphenolic compounds play a crucial role as anticancer medicines alone or in combination with other drugs at different stages of cancer: cancer initiation, promotion, and growth or progression. Moreover, the future directions in applications of various polyphenols in cancer therapy are emphasized.

The current rapid advancement of numerous nanotechnology tools is being employed in treatment of many terminal diseases such as cancer. Nanocapsules (NCs) containing an anti-cancer drug offer a very promising alternative to conventional treatments, mostly due to their targeted delivery and precise action, and thereby they can be used in distinct applications: as biosensors or in medical imaging, allowing for cancer detection as well as agents/carriers in targeted drug delivery. The possibility of using different systems—inorganic nanoparticles, dendrimers, proteins, polymeric micelles, liposomes, carbon nanotubes (CNTs), quantum dots (QDs), biopolymeric nanoparticles and their combinations—offers multiple benefits to early cancer detection as well as controlled drug delivery to specific locations. This review focused on the key and recent progress in the encapsulation of anticancer drugs that include methods of preparation, drug loading and drug release mechanism on the presented nanosystems. Furthermore, the future directions in applications of various nanoparticles are highlighted.