Epithelial Cell Transformation and Senescence as Indicators of Genome Aging: Current Advances and Unanswered Questions

The recent advances in deciphering the human genome allow us to understand and evaluate the mechanisms of human genome age-associated transformations, which are largely unclear. Genome sequencing techniques assure comprehensive mapping of human genetics; however, understanding of gene functional interactions, specifically of time/age-dependent modifications, remain challenging. The age of the genome is defined by the sum of individual (inherited) and acquired genomic traits, based on internal and external factors that impact ontogenesis from the moment of egg fertilization and embryonic development. The biological part of genomic age opens a new perspective for intervention. The discovery of single cell-based mechanisms for genetic change indicates the possibility of influencing aging and associated disease burden, as well as metabolism. Cell populations with transformed genetic background were shown to serve as the origin of common diseases during extended life expectancy (superaging). Consequently, age-related cell transformation leads to cancer and cell degeneration (senescence). This article aims to describe current advances in the genomic mechanisms of senescence and its role in the spatiotemporal spread of epithelial clones and cell evolution.     

Recombinant Long-Acting Thioredoxin Ameliorates AKI to CKD Transition via Modulating Renal Oxidative Stress and Inflammation

An effective strategy is highly desirable for preventing acute kidney injury (AKI) to chronic kidney disease (CKD) transition. Thioredoxin-1 (Trx), a redox-active protein that has anti-oxidative and anti-inflammatory properties, would be a candidate for this but its short half-life limits its clinical application. In this study, we examined the renoprotective effect of long-acting Trx that is comprised of human albumin and Trx (HSA-Trx) against AKI to CKD transition. AKI to CKD mice were created by renal ischemia-reperfusion (IR). From day 1 to day 14 after renal IR, the recovery of renal function was accelerated by HSA-Trx administration. On day 14, HSA-Trx reduced renal fibrosis compared with PBS treatment. At the early phase of fibrogenesis (day 7), HSA-Trx treatment suppressed renal oxidative stress, pro-inflammatory cytokine production and macrophage infiltration, thus ameliorating tubular injury and fibrosis. In addition, HSA-Trx treatment inhibited G2/M cell cycle arrest and apoptosis in renal tubular cells. While renal Trx protein levels were decreased after renal IR, the levels were recovered by HSA-Trx treatment. Together, HSA-Trx has potential for use in the treatment of AKI to CKD transition via its effects of modulating oxidative stress and inflammation.     

Measurement of the flood discharge of a small-sized river using an existing digital video recording system

In this study, a closed-circuit television (CCTV) system, installed for surveillance purposes, is utilized to measure the flow rate during a flood. The procedure to determine both the angle and scale-factor of the camera is described. Then, image analysis techniques, namely the direct visual measurement method, Large-Scale PIV (LSPIV) and Space-Time Image Velocimetry (STIV), are applied to the video images recorded by the CCTV camera. The results of these methods and the conventional float measurement are compared. In addition, the accuracy of the respective methods is discussed. A set of low-quality video images of a flood during a thunderstorm that occurred under the dark ambient conditions (midnight) is analyzed using three image-based methods. The transition of the flow rate during the event is successfully estimated.     

All solid-state battery with sulfur electrode and thio-LISICON electrolyte

A high-capacity type of all solid-state battery was developed using sulfur electrode and the thio-LISICON electrolyte. New nano-composite of sulfur and acetylene black (AB) with an average particle size of 1–10 nm was fabricated by gas-phase mixing and showed a reversible capacity of 900 mAh g⁻¹ at a current density of 0.013 mA cm⁻².     

Development of lateral displacement sensor for real‐time detection of structural damage

We have developed a novel sensor that enables us to measure the relative story displacement of a building structure in real time. This lateral displacement sensor (LDS) is composed of a light‐emitting diode (LED) array, which is fixed on the ceiling, and a position‐sensitive detector (PSD) unit, which is placed on the floor. We optimized the LDS to achieve high accuracy in lateral displacement measurement. The accuracy was evaluated to be 60 µm by conducting shaking table tests. Two LDSs were implemented in an actual building equipped with an active variable stiffness (AVS) system, and the building was vibrated with seismic waveforms by an exciter placed on the rooftop. The seismic displacement of the second floor relative to the first floor was measured using the LDS. Furthermore, the inclination angle of the second floor could be measured using the LDS during the seismic vibration. Using the AVS system, we realized the residual displacement of the second floor without inducing damage to the building, and succeeded in real‐time residual displacement measurement for the first time. These results indicate that the LDS is useful for the health diagnosis of a building structure. © 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Analysis of PD-generated SF/sub 6/ decomposition gases adsorbed on carbon nanotubes

Chemical byproducts analysis has been recognized as a powerful diagnosis method for SF₆ gas-insulated switchgear (GIS). The authors have previously demonstrated that a carbon nanotube (CNT) gas sensor could detect partial discharge (PD) generated in SF₆ gas. However, PD-generated decomposition gas species, which were responsible for the CNT gas sensor response, have not been identified yet. In this paper, two kinds of experiments were conducted in order to identify the responsible decomposition gas species. At first, the decomposition gas molecules adsorbed on CNTs were analyzed by Fourier transformation infrared (FTIR) spectroscopy. FTIR absorbance was observed around 735 cm^-1 after CNTs were exposed to PD generated in SF₆. In the second experiment, the CNT gas sensor responses to typical SF₆ decomposition products (HF and SF₄) were examined. The CNT gas sensor responded to these gases in the same way as to PD generated in SF₆. SF₄ response was larger than HF response. Based on these results, SF ₄ and SOF₂ emerged as candidates for the responsible decomposition gases. Electrochemical interactions between adsorbed gas molecules and CNT were discussed based on theoretical predictions of molecular orbital calculations. The calculation results suggested that both of SOF₂ and SF₄ could increase the CNT gas sensor conductance     

First plasma experiment on spherical tokamak device UTST

The UTST (University of Tokyo Spherical Tokamak) device was constructed for the purpose of exploring the formation of ultrahigh‐beta ST (spherical tokamak) plasma using the double null plasma merging method. When two plasmas merge together to form a single plasma, magnetic field lines reconnect, and magnetic field energy is converted to plasma kinetic energy, increasing the plasma beta. Merging start‐up has been demonstrated in the TS‐3/4, START, and MAST devices using coils inside the vacuum vessel, and the TS‐3 plasma obtained a 50% beta. In order to demonstrate start‐up in a more reactor‐relevant situation, UTST has all poloidal field (PF) coils outside the vacuum vessel. The first plasma experiment on the UTST was begun in December 2007. In the results, the plasma obtained 10 kA by using only the outer PF coils and a single ST was generated in the lower area (z = –0.3 to –1.0 m) close to a washer gun. This result suggests that another washer gun on the top of the UTST can allow the generation of ST in the upper area and merging start‐up by using outer PF coils. © 2012 Wiley Periodicals, Inc. Electr Eng Jpn, 179(2): 20–26, 2012; Published online in Wiley Online Library ( wileyonlinelibrary.com ). DOI 10.1002/eej.21216     

A system for synchronizing the nods of a CG character and a human using thermal image processing and a moving-average model

The purpose of this study was to develop a system for communication between a human and a computer generated (CG) character to make him or her more peaceful and cheerful. Nonverbal communication using such things as facial expression, a nod, or a hand gesture is very important for reciprocal communication between humans. In this study, an image registered by infrared rays which describes the thermal distribution of the face and neck has been used to develop a system for communication between a human and a CG character. The CG character can synchronize its nod with a person’s nod by predicting his or her nod angle. The measured feature parameter is input to a fuzzy algorithm system to obtain the nod angle of a person in front of an infrared camera, and then a moving-average model is used to predict the nod angle of the person. The average error of the nod angle obtained by the system has been estimated as about 5°. The CG character nods its head, not only when the human nods his or her head, but also when the human shakes his or her head to the left or right.     

Additional kernel observer: privilege escalation attack prevention mechanism focusing on system call privilege changes

International Journal of Information Security - Cyberattacks, especially attacks that exploit operating system vulnerabilities, have been increasing in recent years. In particular, if administrator...     

Estimation of time-dependent input from neuronal membrane potential

The set of firing rates of the presynaptic excitatory and inhibitory neurons constitutes the input signal to the postsynaptic neuron. Estimation of the time-varying input rates from intracellularly recorded membrane potential is investigated here. For that purpose, the membrane potential dynamics must be specified. We consider the Ornstein-Uhlenbeck stochastic process, one of the most common single-neuron models, with time-dependent mean and variance. Assuming the slow variation of these two moments, it is possible to formulate the estimation problem by using a state-space model. We develop an algorithm that estimates the paths of the mean and variance of the input current by using the empirical Bayes approach. Then the input firing rates are directly available from the moments. The proposed method is applied to three simulated data examples: constant signal, sinusoidally modulated signal, and constant signal with a jump. For the constant signal, the estimation performance of the method is comparable to that of the traditionally applied maximum likelihood method. Further, the proposed method accurately estimates both continuous and discontinuous time-variable signals. In the case of the signal with a jump, which does not satisfy the assumption of slow variability, the robustness of the method is verified. It can be concluded that the method provides reliable estimates of the total input firing rates, which are not experimentally measurable.