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Background DNA methylation (DNAm) is a critical regulator of both development and cellular identity and shows unique patterns in neurons. To better characterize maturational changes in DNAm patterns in these cells, we profile the DNAm landscape at single-base resolution across the first two decades of human neocortical development in NeuN+ neurons using whole-genome bisulfite sequencing and compare them to non-neurons (primarily glia) and prenatal homogenate cortex. Results We show that DNAm changes more dramatically during the first 5 years of postnatal life than during the entire remaining period. We further refine global patterns of increasingly divergent neuronal CpG and CpH methylation (mCpG and mCpH) into six developmental trajectories and find that in contrast to genome-wide patterns, neighboring mCpG and mCpH levels within these regions are highly correlated. We integrate paired RNA-seq data and identify putative regulation of hundreds of transcripts and their splicing events exclusively by mCpH levels, independently from mCpG levels, across this period. We finally explore the relationship between DNAm patterns and development of brain-related phenotypes and find enriched heritability for many phenotypes within identified DNAm features. Conclusions By profiling DNAm changes in NeuN-sorted neurons over the span of human cortical development, we identify novel, dynamic regions of DNAm that would be masked in homogenate DNAm data; expand on the relationship between CpG methylation, CpH methylation, and gene expression; and find enrichment particularly for neuropsychiatric diseases in genomic regions with cell type-specific, developmentally dynamic DNAm patterns.

Recently, the capture of carbon dioxide, the primary greenhouse gas, has attracted particular interest from researchers worldwide. In the present work, several theoretical methods have been used to study adsorption of CO2 molecules on Li+-decorated coronene (Li+@coronene). It has been established that Li+ can be strongly anchored on coronene, and then a physical adsorption of CO2 will occur in the vicinity of this cation. Moreover, such a decoration has substantially improved interaction energy (Eint) between CO2 molecules and the adsorbent. One to twelve CO2 molecules per one Li+ have been considered, and their Eint values are in the range from −5.55 to −16.87 kcal/mol. Symmetry-adapted perturbation theory (SAPT0) calculations have shown that, depending on the quantity of adsorbed CO2 molecules, different energy components act as the main reason for attraction. AIMD simulations allow estimating gravimetric densities (GD, wt.%) at various temperatures, and the maximal GDs have been calculated to be 9.3, 6.0, and 4.9% at T = 77, 300, and 400 K, respectively. Besides this, AIMD calculations validate stability of Li+@coronene complexes during simulation time at the maximum CO2 loading. Bader’s atoms-in-molecules (QTAIM) and independent gradient model (IGM) techniques have been implemented to unveil the features of interactions between CO2 and Li+@coronene. These methods have proved that there exists a non-covalent bonding between the cation center and CO2. We suppose that findings, derived in this theoretical work, may also benefit the design of novel nanosystems for gas storage and delivery.

Kazakhstan’s asbestos industry produces over 3 million tons of waste annually. The primary component of asbestos ore waste (AOW) is magnesium rich minerals. In this study, the extraction of magnesium from AOW with nitric acid (HNO3) was for the first time systematically studied. A series of experiments were conducted to optimize acid concentration (300–600 g/L), leaching temperature (55–95 °C), leaching time (60–180 min), solid-to-liquid ratio (1:3–1:7), and particle size, with the overall goal of maximizing magnesium extraction and cost efficiency. Our results provide dependence of magnesium extraction in the order of acid concentration  >  temperature  >  time  >  solid-to-liquid ratio, while particle size was found to be negligible. The cost-efficiency optimization demonstrated the positive impact of the relatively low acid concentrations (< 450 g/L) and temperatures between 65 and 85 °C, while the Protodyakonov model validated a linear dependence of the extraction rate on temperature and acid concentration. Our model demonstrates that extraction efficiencies of up to 90% can be achieved while reducing reagent use and lowering the overall cost of magnesium production. Leaching of magnesium by HNO3 also opens a pathway to a closed-cycle process, due to the formation of magnesium nitrate. The thermal decomposition of Mg(NO3)2 provides valuable products such as MgO and NO2 reused in HNO3 regeneration for subsequent cycles. The proposed model predicts magnesium extraction from asbestos ore depending on leaching parameters with reasonable accuracy.

Significant innovations in the regulatory framework of the construction industry of the Russian Federation force construction organizations to change their attitude to digital technology in general and automation in particular. The existing objective differences of construction companies, carrying out their activities at different stages of the life cycle of construction products, put them in different initial conditions on the way to solving the problem. In the present study, the authors analyze the level of elaboration of a number of issues that arise at different stages of the construction project life cycle (CPLC). As a result of the analysis, the authors conclude that there is a lack of attention to digitalization at the stage “construction”. In particular, it is noted that little attention is paid to the automation of the management activities of companies at this stage of CPLC lifecycle. The authors analyze possible approaches to the automation of management tasks of a construction organization that directly erects buildings and structures. As a result, key features of approaches to the formation of task complexes for automation for two different groups of departments of the management apparatus of a construction organization are formulated. Based on the results of the study, the authors conclude that in order to ensure the effective functioning of construction companies and organizations the use of digitalization technologies at all stages is mandatory.

Abstract Context Pancreatic neuroendocrine tumors (PNETs) exhibit a wide range of behavior from localized disease to aggressive metastasis. A comprehensive transcriptomic profile capable of differentiating between these phenotypes remains elusive. Objective Use machine learning to develop predictive models of PNET metastatic potential dependent upon transcriptomic signature. Methods RNA-sequencing data were analyzed from 95 surgically resected primary PNETs in an international cohort. Two cohorts were generated with equally balanced metastatic PNET composition. Machine learning was used to create predictive models distinguishing between localized and metastatic tumors. Models were validated on an independent cohort of 29 formalin-fixed, paraffin-embedded samples using NanoString nCounter®, a clinically available mRNA quantification platform. Results Gene expression analysis identified concordant differentially expressed genes between the 2 cohorts. Gene set enrichment analysis identified additional genes that contributed to enriched biologic pathways in metastatic PNETs. Expression values for these genes were combined with an additional 7 genes known to contribute to PNET oncogenesis and prognosis, including ARX and PDX1. Eight specific genes (AURKA, CDCA8, CPB2, MYT1L, NDC80, PAPPA2, SFMBT1, ZPLD1) were identified as sufficient to classify the metastatic status with high sensitivity (87.5-93.8%) and specificity (78.1-96.9%). These models remained predictive of the metastatic phenotype using NanoString nCounter® on the independent validation cohort, achieving a median area under the receiving operating characteristic curve of 0.886. Conclusion We identified and validated an 8-gene panel predictive of the metastatic phenotype in PNETs, which can be detected using the clinically available NanoString nCounter® system. This panel should be studied prospectively to determine its utility in guiding operative vs nonoperative management.

The paper presents Large Eddy Simulation (LES) data for the ventilation airflow in an isothermal room corresponding to the Nielsen et al. (1978) test. Based on a simplified formulation with the periodicity boundary conditions in the transverse direction, detailed grid sensitivity study was performed. Using LES data on velocity components and mean speed extracted from a periodic domain-size-independent solution, the paper assesses velocity-to-speed conversion procedures available in the literature for the Reynolds-Averaged Navier-Stokes ventilation airflow data processing.

Differentiating pluripotent cells from fibroblast progenitors is a potentially transformative tool in personalized medicine. We previously identified relatively greater success culturing dura-derived fibroblasts than scalp-derived fibroblasts from postmortem tissue. We hypothesized that these differences in culture success were related to epigenetic differences between the cultured fibroblasts by sampling location, and therefore generated genome-wide DNA methylation and transcriptome data on 11 intrinsically matched pairs of dural and scalp fibroblasts from donors across the lifespan (infant to 85 years). While these cultured fibroblasts were several generations removed from the primary tissue and morphologically indistinguishable, we found widespread epigenetic differences by sampling location at the single CpG (N = 101,989), region (N = 697), \"block\" (N = 243), and global spatial scales suggesting a strong epigenetic memory of original fibroblast location. Furthermore, many of these epigenetic differences manifested in the transcriptome, particularly at the region-level. We further identified 7,265 CpGs and 11 regions showing significant epigenetic memory related to the age of the donor, as well as an overall increased epigenetic variability, preferentially in scalp-derived fibroblasts-83% of loci were more variable in scalp, hypothesized to result from cumulative exposure to environmental stimuli in the primary tissue. By integrating publicly available DNA methylation datasets on individual cell populations in blood and brain, we identified significantly increased inter-individual variability in our scalp- and other skin-derived fibroblasts on a similar scale as epigenetic differences between different lineages of blood cells. Lastly, these epigenetic differences did not appear to be driven by somatic mutation--while we identified 64 probable de-novo variants across the 11 subjects, there was no association between mutation burden and age of the donor (p = 0.71). These results depict a strong component of epigenetic memory in cell culture from primary tissue, even after several generations of daughter cells, related to cell state and donor age.

Vanadium nitride (VN) ceramic layers were deposited on 304L stainless steel specimens by direct current (DC) magnetron sputtering in an Ar/N2 gas mixture at substrate temperatures of 250 °C, 300 °C, and 350 °C. The obtained films were evaluated by X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), and atomic force microscopy (AFM). The results showed the existence of VN and V2N phases in the as-deposited coatings. It was found that the surface roughness parameter (Ra = 10 nm) decreased with increasing substrate temperatures up to 350 °C. The highest hardness (10.6 GPa) was achieved in the layer produced at 300 °C. The low values of plastic and elastic deformation, as well as a low friction coefficient (0.38), led to an enhancement in the coatings’ tribological properties. The film’s thickness increased with increasing temperature due to the presence of nucleation centers in the films. The highest thickness (557 nm) was achieved in the layer deposited at 350 °C. The electrochemical tests exhibited reliable protection against corrosion in strongly aggressive electrolytes. It has been proven that the temperature significantly affects the ceramic coatings’ structural, morphological, tribological, and corrosion properties.

In conditions of economic crisis, businesses of construction industry lack the resources to eliminate real risks of non-conformities due differences between construction products and consumers' expectations. In this situation when classic models based on the CAPA become ineffective, the management of non-conformities requires some new acceptable, efficient, and low-cost approaches. The paper describes the original ranking algorithm for measures aimed at reducing the risks in business environment with financing constraints.

Titanium alloys are widely used for biomedical implants, but their performance is limited by wear, corrosion, and susceptibility to bacterial colonisation. To overcome these drawbacks, multilayer Ti–Cu oxide coatings were deposited on Ti6Al4V substrates using direct current magnetron sputtering. Two multilayer architectures (6 × 2 and 12 × 2 TiO2/CuO bilayers) were fabricated and evaluated for their structural, mechanical, electrochemical, and biological properties. SEM/EDS and XRD confirmed well-adhered crystalline coatings consisting of rutile/anatase TiO2 and monoclinic CuO with uniform elemental distribution. The coatings increased surface roughness, improved adhesion, and enhanced hardness by up to ~180% compared to uncoated Ti6Al4V alloy. Compared to the bare substrate, electrochemical testing in simulated body fluid showed higher corrosion resistance of both coated samples, but particularly for the 12 × 2 multilayers. Both architectures provided sustained Cu2+ release over seven days without a burst effect. In vitro biological testing showed that both multilayer coatings achieved over 96% inhibition of Gram-positive bacteria such as Staphylococcus aureus and Bacillus subtilis, while exhibiting moderate antibacterial effects against Gram-negative strains (Escherichia coli, Pseudomonas aeruginosa). Despite the presence of copper, MG-63 osteoblast-like cells demonstrated sustained viability and successful extracellular matrix mineralisation, indicating excellent cytocompatibility of the coatings with bone-forming cells. These results demonstrate that multilayer Ti–Cu oxide coatings can effectively balance antibacterial performance, corrosion resistance, mechanical strength, and support bone cell integration, making them a promising strategy for the surface modification of titanium-based biomedical implants.