Photodynamic therapy (PDT) has long been known as an effective method for treating surface cancer tissues. Although this technique is widely used in modern medicine, some novel approaches for deep lying tumors have to be developed. Recently, deeper penetration of X-rays into tissues has been implemented, which is now known as X-ray photodynamic therapy (XPDT). The two methods differ in the photon energy used, thus requiring the use of different types of scintillating nanoparticles. These nanoparticles are known to convert the incident energy into the activation energy of a photosensitizer, which leads to the generation of reactive oxygen species. Since not all photosensitizers are found to be suitable for the currently used scintillating nanoparticles, it is necessary to find the most effective biocompatible combination of these two agents. The most successful combinations of nanoparticles for XPDT are presented. Nanomaterials such as metal–organic frameworks having properties of photosensitizers and scintillation nanoparticles are reported to have been used as XPDT agents. The role of metal–organic frameworks for applying XPDT as well as the mechanism underlying the generation of reactive oxygen species are discussed.

Abiotic stress factors are considered a serious threat to various growth parameters of crop plants. Stressors such as drought, salinity, and heavy metals (HMs) hamper the chlorophyll content in plants, resulting in low photosynthesis, hinder the integrity of cell membranes, reduce biomass, and overall growth and development of crops which ultimately results in the sharp decline of crop yield. Under such stressful conditions, various strategies are employed to overcome hazardous effects. Application of Zinc (Zn) or Selenium (Se) in different forms is an effective way to alleviate the abiotic stresses in plants. Zn and Se play a pivotal role in enhancing the chlorophyll level to improve photosynthesis, reducing oxidative stress by limiting reactive oxygen species (ROS) production, controlling HMs absorption by plant roots and their accumulation in the plant body, maintaining homeostasis, and alleviating all the detrimental effects caused by abiotic stress factors. The current review is focused on the usefulness of Zn and Se application, their uptake, sensitization, and different defence mechanisms to relieve adverse effects of abiotic stresses (such as drought, salinity, and HMs) on crops. In this connection, research gaps have also been highlighted.

The role of machine learning (a part of artificial intelligence—AI) in the diagnosis and treatment of various types of oncology is steadily increasing. It is expected that the use of AI in oncology will speed up both diagnostic and treatment planning processes. This review describes recent applications of machine learning in oncology, including medical image analysis, treatment planning, patient survival prognosis, and the synthesis of drugs at the point of care. The fast and reliable analysis of medical images is of great importance in the case of fast-flowing forms of cancer. The introduction of ML for the analysis of constantly growing volumes of big data makes it possible to improve the quality of prescribed treatment and patient care. Thus, ML is expected to become an essential technology for medical specialists. The ML model has already improved prognostic prediction for patients compared to traditional staging algorithms. The direct synthesis of the necessary medical substances (small molecule mixtures) at the point of care could also seriously benefit from the application of ML. We further review the main trends in the use of artificial intelligence-based technologies in modern oncology. This review demonstrates the future prospects of using ML tools to make progress in cancer research, as well as in other areas of medicine. Despite growing interest in the use of modern computer technologies in medical practice, a number of unresolved ethical and legal problems remain. In this review, we also discuss the most relevant issues among them.

Polycyclic aromatic hydrocarbons (PAHs) are chemically recalcitrant carcinogenic and mutagenic compounds with primarily anthropogenic origin. The investigation of the effects of emissions from energy enterprises on soil microbiomes is of a high priority for modern soil science. In this study, metagenomic profiling of technogenic contaminated soils was carried out based on bioinformatic analysis of shotgun metagenome data with PAH-degrading genes identification. The use of prokaryotic consortia has been often used as one of the bio-remediation approaches to degrade PAHs with different molecular weight. Since the process of PAH degradation predominantly includes non-culturable or yet-to-be cultured species, metagenomic approaches are highly recommended for studying the composition and metabolic abilities of microbial communities. In this study, whole metagenome shotgun sequencing of DNA from two soils with varying PAH levels was performed. In the control site, the total content of 12 priority PAHs was 262 µg kg⁻¹. The background soil levels in the polluted site for PAHs with 3 or more rings exceeded this, at 800 µg kg⁻¹. The abundance of genes and taxa associated with PAH degradation in these two sites were estimated. Despite differences in PAH concentrations up to 1200 µg kg⁻¹, individual and operon-organized PAH degradation genes were almost equally abundant and diverse in pristine and highly contaminated areas. The most numerous taxa in both spots were actinobacteria from Terrabacteria group. In addition to well-known PAH degraders such as Gordonia and Rhodococcus, genes corresponding to the PAH degradation were found in Azoarcus, Burkholderia and Variovorax. The data shows non-specificity and multifunctionality of metabolic pathways encoded in the genes of PAH-degrading microorganisms.

Biobanks are the platform for innovative biomedical research in the field of translational and personalized medicine. The important aspect for conducting large-scale research in the field of genomics, transcriptomics, proteomics is the availability of a sample information of the documented high-resolution samples. The biobanks solve the problem of forming groups of patients with different nosology within the population of interest and provide clinical and laboratory information on each sample. The aim of this article is to describe the Biobank processes of the National Medical Research Centre for Oncology within the framework of existing projects and build up collections. The review discusses the main stages of the systematized biobank process, describes the methods of sample preparation of different types of biological material, and also provides statistics of the build up collections. To this date, the predominant part of the depository consists of tissue samples of patients diagnosed with colorectal cancer 24% and stomach cancer 23% of the total number of tissue samples, while the number of tissue samples of pancreatic cancer is 10%, and esophageal cancer and breast cancer 22%. In addition to tissue samples, the biobank of the National Medical Research Centre for Oncology stores 24 cell lines of a human origin and the collection of 200 microbiota samples: 100 are from patients diagnosed with lung cancer and 100 from conditional healthy donors. Currently, the studies have been performed on biomaterial from the biobank build up collections to search for prognostic biomarkers and potential targets for targeted therapy by using high-throughput sequencing in patients diagnosed with pancreatic cancer and brain cancer. Thus, the collections play an important role for research in the field of personalized medicine, providing early diagnosis and effective treatment for each patient.