Relationships between probabilistic Boolean networks and dynamic Bayesian networks as models of gene regulatory networks

A significant amount of attention has recently been focused on modeling of gene regulatory networks. Two frequently used large-scale modeling frameworks are Bayesian networks (BNs) and Boolean networks, the latter one being a special case of its recent stochastic extension, probabilistic Boolean networks (PBNs). PBN is a promising model class that generalizes the standard rule-based interactions of Boolean networks into the stochastic setting. Dynamic Bayesian networks (DBNs) is a general and versatile model class that is able to represent complex temporal stochastic processes and has also been proposed as a model for gene regulatory systems. In this paper, we concentrate on these two model classes and demonstrate that PBNs and a certain subclass of DBNs can represent the same joint probability distribution over their common variables. The major benefit of introducing the relationships between the models is that it opens up the possibility of applying the standard tools of DBNs to PBNs and vice versa. Hence, the standard learning tools of DBNs can be applied in the context of PBNs, and the inference methods give a natural way of handling the missing values in PBNs which are often present in gene expression measurements. Conversely, the tools for controlling the stationary behavior of the networks, tools for projecting networks onto sub-networks, and efficient learning schemes can be used for DBNs. In other words, the introduced relationships between the models extend the collection of analysis tools for both model classes.     

Identifying the miRNA Signature Association with Aging-Related Senescence in Glioblastoma

Glioblastoma (GBM) is the most common malignant brain tumor and its malignant phenotypic characteristics are classified as grade IV tumors. Molecular interactions, such as protein–protein, protein–ncRNA, and protein–peptide interactions are crucial to transfer the signaling communications in cellular signaling pathways. Evidences suggest that signaling pathways of stem cells are also activated, which helps the propagation of GBM. Hence, it is important to identify a common signaling pathway that could be visible from multiple GBM gene expression data. microRNA signaling is considered important in GBM signaling, which needs further validation. We performed a high-throughput analysis using micro array expression profiles from 574 samples to explore the role of non-coding RNAs in the disease progression and unique signaling communication in GBM. A series of computational methods involving miRNA expression, gene ontology (GO) based gene enrichment, pathway mapping, and annotation from metabolic pathways databases, and network analysis were used for the analysis. Our study revealed the physiological roles of many known and novel miRNAs in cancer signaling, especially concerning signaling in cancer progression and proliferation. Overall, the results revealed a strong connection with stress induced senescence, significant miRNA targets for cell cycle arrest, and many common signaling pathways to GBM in the network.     

Lightweight porous silica foams with extreme-low dielectric permittivity and loss for future 6G wireless communication technologies

In the next generation wireless communication systems operating at near terahertz frequencies, dielectric substrates with the lowest possible permittivity and loss factor are becoming essential. In this work, highly porous (98.9% ± 0.1%) and lightweight silica foams (0.025 ± 0.005 g/cm3), that have extremely low relative permittivity (εr = 1.018 ± 0.003 at 300 GHz) and corresponding loss factor (tan δ< 3 × 10?4 at 300 GHz) are synthetized by a template-assisted sol-gel method. After dip-coating the slabs of foams with a thin film of cellulose nanofibers, sufficiently smooth surfaces are obtained, on which it is convenient to deposit electrically conductive planar thin films of metals important for applications in electronics and telecommunication devices. Here, micropatterns of Ag thin films are sputtered on the substrates through a shadow mask to demonstrate double split-ring resonator metamaterial structures as radio frequency filters operating in the sub-THz band.     

Experimental confirmation of the transversal symmetry breaking in laser profiles

The Snell phase effects on the propagation of optical beams through dielectric blocks have been matter of recent theoretical studies. The effects of this phase on the laser profiles have been tested in our experiment. The data show an excellent agreement with the theoretical predictions confirming the axial spreading modification and the transversal symmetry breaking. The possibility to set, by rotating the dielectric blocks, different configurations allows to recover the transversal symmetry. Based on this experimental evidence, dielectric blocks can be used as alternative optical tools to control the beam profile.     

Design and validation of an air-liquid interface (ALI) exposure device based on thermophoresis

In vitro, direct aerosol nanoparticle exposure of cells cultured at the air-liquid interface (ALI) has shown great potential over the conventional submerged cell exposure methods due to exposure relevancy and more accurate dose determination. Here, we present a design of an ALI cell exposure device, the thermocollector, which applies thermophoresis to deposit aerosol particles onto the cells. Computational numerical simulations were used to estimate the deposition flux and how it depended on particle properties. The deposition flux was approximately 250 particles/m²s for particles smaller than 100?nm, corresponding to an aerosol concentration of 1 #/cm³. This was also confirmed with experimental studies. For larger particles, the deposition rate depended more on particle properties; however, for fractal combustion derived soot particles, the deposition rate is practically size independent at the size range studied here. Finally, epithelial cells were exposed with wood combustion aerosol, and the toxicologic responses were investigated. The cell viability decrease and DNA damage were detected after the exposure. These effects were not detected in cells after the exposure to clean air in this cell exposure system.

Copyright © 2019 American Association for Aerosol Research     

Mechanically durable superhydrophobic surfaces

Development of durable non-wetting surfaces is hindered by the fragility of the microscopic roughness features that are necessary for superhydrophobicity. Mechanical wear on superhydrophobic surfaces usually shows as increased sticking of water, leading to loss of non-wettability. Increased wear resistance has been demonstrated by exploiting hierarchical roughness where nanoscale roughness is protected to some degree by large scale features, and avoiding the use of hydrophilic bulk materials is shown to help prevent the formation of hydrophilic defects as a result of wear. Additionally, self-healing hydrophobic layers and roughness patterns have been suggested and demonstrated. Nevertheless, mechanical contact not only causes damage to roughness patterns but also surface contamination, which shortens the lifetime of superhydrophobic surfaces in spite of the self-cleaning effect. The use of photocatalytic effect and reduced electric resistance have been suggested to prevent the accumulation of surface contaminants. Resistance to organic contaminants is more challenging, however, oleophobic surface patterns which are non-wetting to organic liquids have been demonstrated. While the fragility of superhydrophobic surfaces currently limits their applicability, development of mechanically durable surfaces will enable a wide range of new applications in the future.