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All types of cancer cells are addicted to methionine, which is known as the Hoffman effect. Restricting methionine inhibits the growth and proliferation of all tested types of cancer cells, leaving normal cells unaffected. Targeting methionine addiction with methioninase (METase), either alone or in combination with common cancer chemotherapy drugs, has been shown as an effective and safe therapy in various types of cancer cells and animal cancer models. About six years ago, recombinant METase (rMETase) was found to be able to be taken orally as a supplement, resulting in anecdotal positive results in patients with advanced cancer. Currently, there are 8 published clinical studies on METase, including two from the 1990s and six more recent ones. This review focuses on the results of clinical studies on METase-mediated methionine restriction, in particular, on the dosage of oral rMETase taken alone as a supplement or in combination with common chemotherapeutic agents in patients with advanced cancer.

Plant cell cultures of various yew species are a profitable source of taxoids (taxane diterpenoids) with antitumor activity. So far, despite intensive studies, the principles of the formation of different groups of taxoids in cultured in vitro plant cells have not been fully revealed. In this study, the qualitative composition of taxoids of different structural groups was assessed in callus and suspension cell cultures of three yew species (Taxus baccata, T. canadensis, and T. wallichiana) and two T. × media hybrids. For the first time, 14-hydroxylated taxoids were isolated from the biomass of the suspension culture of T. baccata cells, and their structures were identified by high-resolution mass spectrometry and NMR spectroscopy as 7β-hydroxy-taxuyunnanin C, sinenxane C, taxuyunnanine C, 2α,5α,9α,10β,14β-pentaacetoxy-4(20), 11-taxadiene, and yunnanxane. UPLC–ESI-MS screening of taxoids was performed in more than 20 callus and suspension cell lines originating from different explants and grown in over 20 formulations of nutrient media. Regardless of the species, cell line origin, and conditions, most of the investigated cell cultures retained the ability to form taxane diterpenoids. Nonpolar 14-hydroxylated taxoids (in the form of polyesters) were predominant under in vitro culture conditions in all cell lines. These results, together with the literature data, suggest that dedifferentiated cell cultures of various yew species retain the ability to synthesize taxoids, but predominantly of the 14-OH taxoid group compared to the 13-OH taxoids found in plants.

Imbalanced graph node classification is a highly relevant and challenging problem in many real-world applications. The inherent data scarcity, a central characteristic of this task, substantially limits the performance of neural classification models driven solely by data. Given the limited instances of relevant nodes and complex graph structures, current methods fail to capture the distinct characteristics of node attributes and graph patterns within the underrepresented classes. In this article, we propose REFUEL—a novel approach for highly imbalanced node classification problems in graphs. Whereas symbolic and neural methods have complementary strengths and weaknesses when applied to such problems, REFUEL combines the power of symbolic and neural learning in a novel neural rule-extraction architecture. REFUEL captures the class semantics in the automatically extracted rule vectors. Then, REFUEL augments the graph nodes with the extracted rules vectors and adopts a Graph Attention Network-based neural node embedding, enhancing the downstream neural node representation. Our evaluation confirms the effectiveness of the proposed REFUEL approach for three real-world datasets with different minority class sizes. REFUEL achieves at least a 4% point improvement in precision on the minority classes of 1.5–2% compared to the baselines.

This article presents a dataset containing messages from the Digital Teaching Assistant (DTA) system, which records the results from the automatic verification of students’ solutions to unique programming exercises of 11 various types. These results are automatically generated by the system, which automates a massive Python programming course at MIREA—Russian Technological University (RTU MIREA). The DTA system is trained to distinguish between approaches to solve programming exercises, as well as to identify correct and incorrect solutions, using intelligent algorithms responsible for analyzing the source code in the DTA system using vector representations of programs based on Markov chains, calculating pairwise Jensen–Shannon distances for programs and using a hierarchical clustering algorithm to detect high-level approaches used by students in solving unique programming exercises. In the process of learning, each student must correctly solve 11 unique exercises in order to receive admission to the intermediate certification in the form of a test. In addition, a motivated student may try to find additional approaches to solve exercises they have already solved. At the same time, not all students are able or willing to solve the 11 unique exercises proposed to them; some will resort to outside help in solving all or part of the exercises. Since all information about the interactions of the students with the DTA system is recorded, it is possible to identify different types of students. First of all, the students can be classified into 2 classes: those who failed to solve 11 exercises and those who received admission to the intermediate certification in the form of a test, having solved the 11 unique exercises correctly. However, it is possible to identify classes of typical, motivated and suspicious students among the latter group based on the proposed dataset. The proposed dataset can be used to develop regression models that will predict outbursts of student activity when interacting with the DTA system, to solve clustering problems, to identify groups of students with a similar behavior model in the learning process and to develop intelligent data classifiers that predict the students’ behavior model and draw appropriate conclusions, not only at the end of the learning process but also during the course of it in order to motivate all students, even those who are classified as suspicious, to visualize the results of the learning process using various tools.

Pathogenic variants (PVs) in multiple genes are known to increase the risk of early-onset renal cancer (eoRC). However, many eoRC patients lack PVs in RC-specific genes; thus, their genetic risk remains undefined. Here, we determine if PVs in DNA damage response and repair (DDRR) genes are enriched in eoRC patients undergoing cancer risk assessment. Retrospective review of de-identified results from 844 eoRC patients, undergoing testing with a multi-gene panel, for a variety of indications, by Ambry Genetics. PVs in cancer-risk genes were identified in 12.8% of patients—with 3.7% in RC-specific, and 8.55% in DDRR genes. DDRR gene PVs were most commonly identified in CHEK2 , BRCA1, BRCA2, and ATM . Among the 2.1% of patients with a BRCA1 or BRCA2 PV, < 50% reported a personal history of hereditary breast or ovarian-associated cancer. No association between age of RC diagnosis and prevalence of PVs in RC-specific or DDRR genes was observed. Additionally, 57.9% patients reported at least one additional cancer; breast cancer being the most common (40.1% of females, 2.5% of males). Multi-gene testing including DDRR genes may provide a more comprehensive risk assessment in eoRC patients. Further validation is needed to characterize the association with eoRC.

Background Early-onset renal cell carcinoma (eoRCC) is typically associated with pathogenic germline variants (PGVs) in RCC familial syndrome genes . However, most eoRCC patients lack PGVs in familial RCC genes and their genetic risk remains undefined. Methods Here, we analyzed biospecimens from 22 eoRCC patients that were seen at our institution for genetic counseling and tested negative for PGVs in RCC familial syndrome genes. Results Analysis of whole-exome sequencing (WES) data found enrichment of candidate pathogenic germline variants in DNA repair and replication genes, including multiple DNA polymerases. Induction of DNA damage in peripheral blood monocytes (PBMCs) significantly elevated numbers of γ H2AX foci, a marker of double-stranded breaks, in PBMCs from eoRCC patients versus PBMCs from matched cancer-free controls. Knockdown of candidate variant genes in Caki RCC cells increased γ H2AX foci. Immortalized patient-derived B cell lines bearing the candidate variants in DNA polymerase genes ( POLD1, POLH, POLE, POLK ) had DNA replication defects compared to control cells. Renal tumors carrying these DNA polymerase variants were microsatellite stable but had a high mutational burden. Direct biochemical analysis of the variant Pol δ and Pol η polymerases revealed defective enzymatic activities. Conclusions Together, these results suggest that constitutional defects in DNA repair underlie a subset of eoRCC cases. Screening patient lymphocytes to identify these defects may provide insight into mechanisms of carcinogenesis in a subset of genetically undefined eoRCCs. Evaluation of DNA repair defects may also provide insight into the cancer initiation mechanisms for subsets of eoRCCs and lay the foundation for targeting DNA repair vulnerabilities in eoRCC.

Three types of extraction were used to obtain biologically active substances from the heartwood of M. amurensis: supercritical CO2 extraction, maceration with EtOH, and maceration with MeOH. The supercritical extraction method proved to be the most effective type of extraction, giving the highest yield of biologically active substances. Several experimental conditions were investigated in the pressure range of 50–400 bar, with 2% of ethanol as co-solvent in the liquid phase at a temperature in the range of 31–70 °C. The most effective extraction conditions are: pressure of 100 bar and a temperature of 55 °C for M. amurensis heartwood. The heartwood of M. amurensis contains various polyphenolic compounds and compounds of other chemical groups with valuable biological activity. Tandem mass spectrometry (HPLC-ESI—ion trap) was applied to detect target analytes. High-accuracy mass spectrometric data were recorded on an ion trap equipped with an ESI source in the modes of negative and positive ions. The four-stage ion separation mode was implemented. Sixty-six different biologically active components have been identified in M. amurensis extracts. Twenty-two polyphenols were identified for the first time in the genus Maackia.

Drosophila melanogaster polytene chromosomes display specific banding pattern; the underlying genetic organization of this pattern has remained elusive for many years. In the present paper, we analyze 32 cytology-mapped polytene chromosome interbands. We estimated molecular locations of these interbands, described their molecular and genetic organization and demonstrate that polytene chromosome interbands contain the 5' ends of housekeeping genes. As a rule, interbands display preferential \"head-to-head\" orientation of genes. They are enriched for \"broad\" class promoters characteristic of housekeeping genes and associate with open chromatin proteins and Origin Recognition Complex (ORC) components. In two regions, 10A and 100B, coding sequences of genes whose 5'-ends reside in interbands map to constantly loosely compacted, early-replicating, so-called \"grey\" bands. Comparison of expression patterns of genes mapping to late-replicating dense bands vs genes whose promoter regions map to interbands shows that the former are generally tissue-specific, whereas the latter are represented by ubiquitously active genes. Analysis of RNA-seq data (modENCODE-FlyBase) indicates that transcripts from interband-mapping genes are present in most tissues and cell lines studied, across most developmental stages and upon various treatment conditions. We developed a special algorithm to computationally process protein localization data generated by the modENCODE project and show that Drosophila genome has about 5700 sites that demonstrate all the features shared by the interbands cytologically mapped to date.

Large-scale planned special events in cities including concerts, football games and fairs can significantly impact urban mobility. The lack of reliable models for understanding and predicting mobility needs during urban events causes issues for mobility service users, providers as well as urban planners. In this article, we tackle the problem of building reliable supervised models for predicting the spatial and temporal impact of planned special events with respect to road traffic. We adopt a supervised machine learning approach to predict event impact from historical data and analyse effectiveness of a variety of features, covering, for instance, features of the events as well as mobility- and infrastructure-related features. Our evaluation results on real-world event data containing events from several venues in the Hannover region in Germany demonstrate that the proposed combinations of event-, mobility- and infrastructure-related features show the best performance and are able to accurately predict spatial and temporal impact on road traffic in the event context in this region. In particular, a comparison with both event-based and event-agnostic baselines shows superior capacity of our models to predict impact of planned special events on urban traffic.

The effects of methyl jasmonate (MeJ) on growth and taxoid formation in the cell culture of Taxus wallichiana were investigated to elucidate the specifics of phytohormone action in dedifferentiated plant cells in vitro. The characteristics of the same suspension cell culture were compared in 2017 (the «young» culture) and in 2022 (the «old» culture)—1.5 or 6 years after culture induction, respectively. MeJ (100 µM) is added to the cell suspension at the end of the exponential growth phase. Cell culture demonstrated good growth (dry weight accumulation 10–18 g/L, specific growth rate µ = 0.15–0.35 day−1) regardless of its «age», cultivation system, and MeJ addition. UPLC-ESI-MS analysis revealed the presence of C14-hydroxylated taxoids (yunnanxane, taxuyunnanine C, sinenxane C, and sinenxane B) in the cell biomass. The content of C14-OH taxoids increased from 0.2–1.6 mg/gDW in «young» culture to 0.6–10.1 mg/gDW in «old» culture. Yunnanxane was the main compound in «young» culture, while sinenxane C predominated in «old» culture. Without elicitation, small amounts of C13-OH taxoids (<0.05 mg/gDW) were found only in «young» cultures. MeJ addition to «young» culture had no effect on the content of C14-OH taxoids but caused a 10-fold increase in C13-OH taxoid production (up to 0.12–0.19 mg/gDW, comparable to the bark of yew trees). By contrast, MeJ added to «old» culture was not beneficial for the production of C13-OH taxoids but notably increased the content of C14-OH taxoids (1.5–2.0 times in flasks and 5–8 times in bioreactors). These findings suggest that hormonal signaling in dedifferentiated yew cells grown in vitro is different from that in plants and can be affected by the culture’s age. This might be a result of the high level of culture heterogeneity and constant auto-selection for intensive proliferation, which leads to the predominant formation of C14-OH taxoids versus C13-OH taxoids and a modified cell response to exogenous MeJ treatment.