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This article investigates the composition and content of information resources used as sources of geospatial data to support the planning and design of reconstruction and restoration of cultural heritage sites in Ukraine as a result of armed aggression and full-scale war of the Russian Federation on the territory of Ukraine. Therefore, the requirements for geospatial data on cultural heritage sites have been formed following the NSDI. [ABSTRACT FROM AUTHOR]

Increased expression of NUSAP1 has been identified as a robust prognostic biomarker in prostate cancer and other malignancies. We have previously shown that NUSAP1 is positively regulated by E2F1 and promotes cancer invasion and metastasis. To further understand the biological function of NUSAP1, we used affinity purification and mass spectrometry proteomic analysis to identify NUSAP1 interactors. We identified 85 unique proteins in the NUSAP1 interactome, including ILF2, DHX9, and other RNA-binding proteins. Using proteomic approaches, we uncovered a function for NUSAP1 in maintaining R-loops and in DNA damage response through its interaction with ILF2. Co-immunoprecipitation and colocalization using confocal microscopy verified the interactions of NUSAP1 with ILF2 and DHX9, and RNA/DNA hybrids. We showed that the microtubule and charged helical domains of NUSAP1 were necessary for the protein-protein interactions. Depletion of ILF2 alone further increased camptothecin-induced R-loop accumulation and DNA damage, and NUSAP1 depletion abolished this effect. In human prostate adenocarcinoma, NUSAP1 and ILF2 mRNA expression levels are positively correlated, elevated, and associated with poor clinical outcomes. Our study identifies a novel role for NUSAP1 in regulating R-loop formation and accumulation in response to DNA damage through its interactions with ILF2 and hence provides a potential therapeutic target. [ABSTRACT FROM AUTHOR]

Patient-derived xenografts (PDX) are high-fidelity cancer models typically credentialled by genomics, transcriptomics and proteomics. Characterization of metabolic reprogramming, a hallmark of cancer, is less frequent. Dysregulated metabolism is a key feature of clear cell renal cell carcinoma (ccRCC) and authentic preclinical models are needed to evaluate novel imaging and therapeutic approaches targeting metabolism. We characterized 5 PDX from high-grade or metastatic ccRCC by multiparametric magnetic resonance imaging (MRI) and steady state metabolic profiling and flux analysis. Similar to MRI of clinical ccRCC, T2-weighted images of orthotopic tumors of most PDX were homogeneous. The increased hyperintense (cystic) areas observed in one PDX mimicked the cystic phenotype typical of some RCC. The negligible hypointense (necrotic) areas of PDX grown under the highly vascularized renal capsule are beneficial for preclinical studies. Mean apparent diffusion coefficient (ADC) values were equivalent to those of ccRCC in human patients. Hyperpolarized (HP) [1-13C]pyruvate MRI of PDX showed high glycolytic activity typical of high-grade primary and metastatic ccRCC with considerable intra- and inter-tumoral variability, as has been observed in clinical HP MRI of ccRCC. Comparison of steady state metabolite concentrations and metabolic flux in [U-13C]glucose-labeled tumors highlighted the distinctive phenotypes of two PDX with elevated levels of numerous metabolites and increased fractional enrichment of lactate and/or glutamate, capturing the metabolic heterogeneity of glycolysis and the TCA cycle in clinical ccRCC. Culturing PDX cells and reimplanting to generate xenografts (XEN), or passaging PDX in vivo, altered some imaging and metabolic characteristics while transcription remained like that of the original PDX. These findings show that PDX are realistic models of ccRCC for imaging and metabolic studies but that the plasticity of metabolism must be considered when manipulating PDX for preclinical studies. [ABSTRACT FROM AUTHOR]

Simple Summary: Cancer metastasis is a critical event in the progression of solid tumors and is invariably associated with adverse outcomes and mortality. Understanding novel mechanisms or molecules that promote cancer metastasis will facilitate the development of new strategies for cancer treatment. Recently, MARCKS has been studied extensively in several cancers and has been implicated in tumor progression and metastasis. This review summarizes recent advances in the understanding of MARCKS on cancer metastasis, stemness, and therapeutic resistance and provides prospects on targeting MARCKS therapeutically. Specifically, we review the molecular mechanisms and multiple signaling pathways by which MARCKS contributes to the progression and metastasis in solid tumors. The myristoylated alanine-rich C-kinase substrate (MARCKS) is a membrane-associated protein kinase C (PKC) substrate ubiquitously expressed in eukaryotic cells. MARCKS plays important roles in multiple cellular processes, including cell adhesion and motility, mucin secretion, exocytosis, and inflammatory response. Aberrant MARCKS signaling has been observed in the development and progression of multiple cancer types. In addition, MARCKS facilitates cancer metastasis through modulating cancer cell migration and invasion. Moreover, MARCKS contributes to treatment resistance, likely by promoting cancer stem cell renewal as well as immunosuppression. In this review, we describe MARCKS protein structure, cellular localization, and biological functions. We then discuss the role of MARCKS in cancer metastasis as well as its mechanisms of action in solid tumors. Finally, we review recent advances in targeting MARCKS as a new therapeutic strategy in cancer management. [ABSTRACT FROM AUTHOR]

Under the action of various dynamic loads, bridges will experience large deflections and stress. When the situation is difficult, it will affect the regular use of the bridge and even cause it to collapse suddenly. This article generated a sample of road surface irregularities based on the Chinese national standard. An ANSYS model was used to create the vehicle–bridge coupling model. In order to meet the actual engineering calculations, an essential but valuable analytical approach is presented here. The node coupling method established the time-varying vehicle axle coupling system. The moving tire force was applied to the axle coupling system. The ANSYS parametric design language was adopted to realize the process of the vehicle approach and exit of the bridge. Combined with the actual data of dynamic and static load experiments, the model's accuracy was verified. The influence of different vehicle driving speeds, road irregularities, vehicle driving position, and vehicle driving state are analyzed in this paper. The vehicle speed had no significant influence on the displacement time-history and the force of the middle wheel of the vehicle at a specific driving position. The pavement grade significantly influenced the bridge's displacement time-history and acceleration spectrum. [ABSTRACT FROM AUTHOR]