The Emerging Regulatory Role of Circular RNAs in Periodontal Tissues and Cells

Periodontitis is a chronic complex inflammatory disease associated with a destructive host immune response to microbial dysbiosis, leading to irreversible loss of tooth-supporting tissues. Regeneration of functional periodontal soft (periodontal ligament and gingiva) and hard tissue components (cementum and alveolar bone) to replace lost tissues is the ultimate goal of periodontal treatment, but clinically predictable treatments are lacking. Similarly, the identification of biomarkers that can be used to accurately diagnose periodontitis activity is lacking. A relatively novel category of molecules found in oral tissue, circular RNAs (circRNAs) are single-stranded endogenous, long, non-coding RNA molecules, with covalently circular-closed structures without a 5’ cap and a 3’ tail via non-classic backsplicing. Emerging research indicates that circRNAs are tissue and disease-specific expressed and have crucial regulatory functions in various diseases. CircRNAs can function as microRNA or RNA binding sites or can regulate mRNA. In this review, we explore the biogenesis and function of circRNAs in the context of the emerging role of circRNAs in periodontitis pathogenesis and the differentiation of periodontal cells. CircMAP3K11, circCDK8, circCDR1as, circ_0062491, and circ_0095812 are associated with pathological periodontitis tissues. Furthermore, circRNAs are expressed in periodontal cells in a cell-specific manner. They can function as microRNA sponges and can form circRNA–miRNA–mRNA networks during osteogenic differentiation for periodontal-tissue (or dental pulp)-derived progenitor cells.     

Nano fibrillated cellulose-based foam by Pickering emulsion: Preparation,characterizations, and application as dye adsorbent

An ecofriendly and biodegradable porous structure was prepared from drying aqueous foams based on nano fibrillated cellulose (NFC), extracted from softwood pulp by subcritical water/CO₂ treatment (SC-NFC). The primary aim of this work was to use the modified SC-NFC as stabilizer for a water-based Pickering emulsion which upon drying, yielded porous cellulosic materials, a good dye adsorbent. In order to exploit the carboxymethylated SC-NFC (CMSC-NFC, with a degree of substitution of 0.35 and a charge density of 649 μeqv/g) as a stabilizer for water-based Pickering emulsion in subsequent step, an optimized quantity of octyl amine (30 mg/g of SC-NFC) was added to make them partially hydrophobic. A series of dry foam structures were prepared by varying the concentrations of treated CMSC-NFCs and 4 wt% was found to be the optimum concentration to yield foam with high porosity (99%) and low density (0.038 g/cc) along with high compression strength (0.24 MPa), superior to the conventionally extracted NFC. The foams were applied to capture as high as 98% of methylene blue dyes, making them a potential green candidate for treating industrial effluent. In addition, the dye adsorption kinetics and isotherms were found to be well suited with second order kinetics and Langmuir isotherm models.     

Alumina-Periclase-Carbon Refractories Produced by OOO Ogneupor

Refractories and Industrial Ceramics - Technology for producing alumina-periclase-carbon refractories of the brands APUK-D and APU-D is developed and implemented. Use of complex antioxidant and...     

Gluten-free cakes with walnut flour: a technological,sensory, and microstructural approach

Walnut flour (WF), a by-product of walnut oil production, is characterised by high polyunsaturated fatty acids, proteins, and fibre contents and presents suitability for bakery products. However, when using non-traditional ingredients, it is essential to evaluate the effect on the quality properties of the final product. So, this work aimed to assess the impact of WF on the technological, physicochemical, and sensory properties of gluten-free (GF) cakes. WF was added at a flour blend (cassava (CS) and maize (MS) starches and rice flour) at 0, 10%, 15%, and 20%. The results showed that WF modified starch gelatinisation, increased amylose–lipid complex (ALC) content, and made crumbs easier to chew. Besides, the total dietary fibre (TDF) and protein content significantly increased. Cakes with 15% WF presented the highest specific volume (SV) and no differences in overall acceptability with respect to control. Hence, WF is a suitable ingredient for gluten-free bakery products.     

Investigation of thermal residual stresses during laser ablation of tantalum carbide coated graphite substrates using micro-Raman spectroscopy and COMSOL multiphysics

Laser ablation of high-temperature ceramic coatings results in thermal residual stresses due to which the coatings fail by cracking and debonding. Hence, the measurement of such residual stresses during laser ablation process holds utmost importance from the view of performance of coatings in extreme conditions. The present research aims at investigating the effect of laser parameters such as laser pulse energy, scanning speed and line spacing on thermal residual stresses induced in tantalum carbide-coated graphite substrates. Residual stresses were measured using micro-Raman spectroscopy and correlated with Raman peak shifts. Transient thermal analysis was performed using COMSOL Multiphysics to model the single ablated track and residual stresses were reported at low, moderate and high pulse energy regimes. The results showed that the initial laser conditions caused higher tensile residual stresses. Moderate pulse energy regime comprised higher compressive residual stresses due to off centre overlapping of the laser pulses. Higher pulse energy (250 μJ), higher scanning speed (1000 mm/s) and moderate line spacing (20 μm) caused accumulation of tensile residual stresses during the final stage of laser ablation. The deviation of experimental residual stresses from COMSOL numerical model was attributed to unaccounted additional stresses induced during thermal spraying process and deformation potentials in the numerical model.     

Down-link OFDRMA communications

Wireless Networks - Orthogonal frequency-division multiplexing with random multiple access (OFDRMA) is discussed for down-link communications, whereby a single base-station transmits information...     

QoS-Aware Optical Fog-Assisted Cyber-Physical System in the 5G Ready Heterogeneous Network

Wireless Personal Communications - In recent years, the emergence of Internet of things and cyber-physical system provide a proactive and efficacious solution to enable remote monitoring, machine...     

Efficient watermarking technique for protection and authentication of document images

Multimedia Tools and Applications - In this paper, a hashing based watermarking technique for the protection and authentication of document image is proposed. Message Digest 5 (MD5) hashing is...     

Extremum Strategies of Approach of Controlled Objects in Dynamic Game Problems with Terminal Payoff Function

Cybernetics and Systems Analysis - The authors propose a method for solving the problem of approach of controlled objects in dynamic game problems with a terminal payoff function. The method is...     

Validation of scientific topic models using graph analysis and corpus metadata

Probabilistic topic modeling algorithms like Latent Dirichlet Allocation (LDA) have become powerful tools for the analysis of large collections of documents (such as papers, projects, or funding applications) in science, technology an innovation (STI) policy design and monitoring. However, selecting an appropriate and stable topic model for a specific application (by adjusting the hyperparameters of the algorithm) is not a trivial problem. Common validation metrics like coherence or perplexity, which are focused on the quality of topics, are not a good fit in applications where the quality of the document similarity relations inferred from the topic model is especially relevant. Relying on graph analysis techniques, the aim of our work is to state a new methodology for the selection of hyperparameters which is specifically oriented to optimize the similarity metrics emanating from the topic model. In order to do this, we propose two graph metrics: the first measures the variability of the similarity graphs that result from different runs of the algorithm for a fixed value of the hyperparameters, while the second metric measures the alignment between the graph derived from the LDA model and another obtained using metadata available for the corresponding corpus. Through experiments on various corpora related to STI, it is shown that the proposed metrics provide relevant indicators to select the number of topics and build persistent topic models that are consistent with the metadata. Their use, which can be extended to other topic models beyond LDA, could facilitate the systematic adoption of this kind of techniques in STI policy analysis and design.