Ukrainian School оf Terminology

The main stages of establishment and origins of Ukrainian terminology school are analyzed beginning from the history of Ukrainian scientific terminology in correlation with the history of development of terminological activity in Ukraine, through formation of practical and theoretical foundations of Ukrainian terminology, development of theoretical and practical principles of Ukrainian terminology on the basis of russification of specialized terminologies and development of contemporary Ukrainian terminology following the formation of an independent Ukrainian state

Nutrient sensor O-GlcNAc transferase controls cancer lipid metabolism via SREBP-1 regulation

Elevated O-GlcNAcylation is associated with disease states such as diabetes and cancer. O-GlcNAc transferase (OGT) is elevated in multiple cancers and inhibition of this enzyme genetically or pharmacologically inhibits oncogenesis. Here we show that O-GlcNAcylation modulates lipid metabolism in cancer cells. OGT regulates expression of the master lipid regulator the transcription factor sterol regulatory element binding protein 1 (SREBP-1) and its transcriptional targets both in cancer and lipogenic tissue. OGT regulates SREBP-1 protein expression via AMP-activated protein kinase (AMPK). SREBP-1 is critical for OGT-mediated regulation of cell survival and of lipid synthesis, as overexpression of SREBP-1 rescues lipogenic defects associated with OGT suppression, and tumor growth in vitro and in vivo. These results unravel a previously unidentified link between O-GlcNAcylation, lipid metabolism and the regulation of SREBP-1 in cancer and suggests a crucial role for O-GlcNAc signaling in transducing nutritional state to regulate lipid metabolism

Emergence of fractal geometries in the evolution of a metabolic enzyme

Fractals are patterns that are self-similar across multiple length-scales. Macroscopic fractals are common in nature; however, so far, molecular assembly into fractals is restricted to synthetic systems. Here we report the discovery of a natural protein, citrate synthase from the cyanobacterium Synechococcus elongatus, which self-assembles into Sierpiński triangles. Using cryo-electron microscopy, we reveal how the fractal assembles from a hexameric building block. Although different stimuli modulate the formation of fractal complexes and these complexes can regulate the enzymatic activity of citrate synthase in vitro, the fractal may not serve a physiological function in vivo. We use ancestral sequence reconstruction to retrace how the citrate synthase fractal evolved from non-fractal precursors, and the results suggest it may have emerged as a harmless evolutionary accident. Our findings expand the space of possible protein complexes and demonstrate that intricate and regulatable assemblies can evolve in a single substitution

Structural pathways for ultrafast melting of optically excited thin polycrystalline Palladium films

Due to its extremely short timescale, the non-equilibrium melting of metals is exceptionally difficult to probe experimentally. The knowledge of melting mechanisms is thus based mainly on the results of theoretical predictions. This work reports on the investigation of ultrafast melting of thin polycrystalline Pd films studied by optical laser pump - X-ray free-electron laser probe experiments and molecular-dynamics simulations. By acquiring X-ray diffraction snapshots with sub-picosecond resolution, we capture the sample's atomic structure during its transition from the crystalline to the liquid state. Bridging the timescales of experiments and simulations allows us to formulate a realistic microscopic picture of melting. We demonstrate that the existing models of strongly non-equilibrium melting, developed for systems with relatively weak electron-phonon coupling, remain valid even for ultrafast heating rates achieved in femtosecond laser-excited Pd. Furthermore, we highlight the role of pre-existing and transiently generated crystal defects in the transition to the liquid state.Comment: main manuscript 33 pages, 9 figures; supplemental material 19 pages, 13 figures - all in one fil

Hematopoietic stem cell mobilization with the reversible CXCR4 receptor inhibitor plerixafor (AMD3100)—Polish compassionate use experience

Recent developments in the field of targeted therapy have led to the discovery of a new drug, plerixafor, that is a specific inhibitor of the CXCR4 receptor. Plerixafor acts in concert with granulocyte colony-stimulating factor (G-CSF) to increase the number of stem cells circulating in the peripheral blood (PB). Therefore, it has been applied in the field of hematopoietic stem cell mobilization. We analyzed retrospectively data regarding stem cell mobilization with plerixafor in a cohort of 61 patients suffering from multiple myeloma (N = 23), non-Hodgkin’s lymphoma (N = 20), or Hodgkin’s lymphoma (N = 18). At least one previous mobilization attempt had failed in 83.6% of these patients, whereas 16.4% were predicted to be poor mobilizers. The median number of CD34+ cells in the PB after the first administration of plerixafor was 22/μL (range of 0–121). In total, 85.2% of the patients proceeded to cell collection, and a median of two (range of 0–4) aphereses were performed. A minimum of 2.0 × 106 CD34+ cells per kilogram of the patient’s body weight (cells/kg b.w.) was collected from 65.6% of patients, and the median number of cells collected was 2.67 × 106 CD34+ cells/kg b.w. (0–8.0). Of the patients, 55.7% had already undergone autologous stem cell transplantation, and the median time to neutrophil and platelet reconstitution was 12 and 14 days, respectively. Cases of late graft failure were not observed. We identified the diagnosis of non-Hodgkin’s lymphoma and previous radiotherapy as independent factors that contributed to failure of mobilization. The current report demonstrates the satisfactory efficacy of plerixafor plus G-CSF for stem cell mobilization in heavily pre-treated poor or predicted poor mobilizers

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)

Comprehensive molecular characterization of gastric adenocarcinoma

Gastric cancer is a leading cause of cancer deaths, but analysis of its molecular and clinical characteristics has been complicated by histological and aetiological heterogeneity. Here we describe a comprehensive molecular evaluation of 295 primary gastric adenocarcinomas as part of The Cancer Genome Atlas (TCGA) project. We propose a molecular classification dividing gastric cancer into four subtypes: tumours positive for Epstein–Barr virus, which display recurrent PIK3CA mutations, extreme DNA hypermethylation, and amplification of JAK2, CD274 (also known as PD-L1) and PDCD1LG2 (also knownasPD-L2); microsatellite unstable tumours, which show elevated mutation rates, including mutations of genes encoding targetable oncogenic signalling proteins; genomically stable tumours, which are enriched for the diffuse histological variant and mutations of RHOA or fusions involving RHO-family GTPase-activating proteins; and tumours with chromosomal instability, which show marked aneuploidy and focal amplification of receptor tyrosine kinases. Identification of these subtypes provides a roadmap for patient stratification and trials of targeted therapies