Aging response of the young’s modulus and mechanical properties of Ti-29Nb-13Ta-4.6Zr for biomedical applications

Alloys for implant devices require improved strength but a reduced Young’s modulus, in order to become mechanically more compatible with adjacent bone tissues. In this study, a new metastable β-type titanium alloy, Ti-29Nb-13Ta-4.6Zr (wt pct), was subjected to aging treatment to produce different microstructures, and the resulting mechanical properties, including the Young’s modulus, were measured. The Young’s modulus of this alloy is found to be sensitive to microstructures generated by various heat treatments. For microstructures varying from (α + β) to (α + β + ω) and (β + ω), the Young’s modulus increases with an accompanying increase in tensile strength and hardness, but decreases in ductility. The (β + ω) microstructure has a low strength, high modulus, and poor ductility and cannot be used for biomedical applications. For an (α + β) microstructure, the volume fraction of the phases is shown to be the main factor that determines the mechanical properties.     

X-ray absorptiometry

Bone mass measurements are essential in the diagnosis of osteoporosis, the monitoring of its progression, and the evaluation of therapeutical responses. Among various methods of bone mass measurements, single- and dual-X-ray absorptiometry, SXA and DXA, have shown excellent fundamental performance. In this paper, the principles of SXA and DXA; i.e., factors of fundamental performance, such as precision, data-acquisition, and radiation dose, the practice of DXA, recent advances in DXA, such as the lateral spine scan, the measurement of body composition, application to BMD measurement of the bones of small animals and at sites of metal implants, morphometry of the spine, and geometrical measurement in the proxial femur, and clinical applications to osteoporosis were particularly reviewed.     

Radiation tolerance for the SMASH-series front-end chips for a silicon micro-strip detector

The radiation tolerance for prototype front-end chips designed for a silicon micro-strip detector was examined with a ⁶⁰Co irradiation source to establish an allowable range of the radiation dose. The irradiated front-end chips were SMA²SH-64A, a 64-channel preamplifier array; SMA²SH-1, a single-channel preamplifier circuit with a comparator; and Control-C, a digital-control chip for the preamplifiers.     

Screening of Inhibitors Targeting Heat Shock Protein 47 Involved in the Development of Idiopathic Pulmonary Fibrosis

Heat shock protein 47 (HSP47), a collagen-specific molecular chaperone, is causally related to fibrotic diseases, including idiopathic pulmonary fibrosis. The identification of Compounds that interfere with the HSP47-collagen interaction is essential for the development of relevant therapeutics. Herein, we prepared human HSP47 as a soluble fusion protein expressed in E. coli and established an assay system for HSP47 inhibitor screening. We screened a natural and synthetic Compound library established at Nagasaki University. Among 1023 Compounds, 13 exhibited inhibitory activity against human HSP47, of which three inhibited its function in a dose-dependent manner. Epigallocatechin-3-O-gallate, one of these three Compounds, is a typical polyphenol Compound derived from tea leaves. Structurally related Compounds were synthesized and examined for their activity, revealing a hydroxyl group at A-ring position 5 as important for its activity. The present findings provide valuable insight for the development of natural product-derived therapeutics for fibrotic diseases, including idiopathic pulmonary fibrosis.     

Thermal Expansion of Solid Solutions in the ZrTiO4—In2O3—M2O5 (M = Sb, Ta) System

Axial and dilatometric thermal expansions and phase transformations were studied for solid solutions having the α-PbO₂ structure in the ZrTiO₄—In₂O₃—M₂O₅ (M = Sb, Ta) system with nominal formulas of Zr _x Ti _y In _z Sb _z O₄ and Zr _x Ti _y In _z Ta _z O₄ where x + y + 2 z = 2. With increased substitution of z , the cell volume increased, the difference in the b parameters at room temperature between those quenched from 1400° and 1000°C decreased, and the thermal expansion decreased. The axial thermal expansion of ZrTi _y In _z · Ta _z O₄ with z = 0.3 was almost identical with that of HfTiO₄, and those with z = 0.4 and z = 0.45 were smaller than that of HfTiO₄. Unit-cell volumes of these compound were compared with those of single oxides to make it clear that the unit-cell volume of ZrTiO₄ was small anomalously and to distinguish the normal and abnormal substitution systems. These results were explained by the working hypothesis proposed for these compounds.     

Network Design with Edge-Connectivity and Degree Constraints

We consider the following network design problem; Given a vertex set V with a metric cost c on V, an integer k≥1, and a degree specification b, find a minimum cost k-edge-connected multigraph on V under the constraint that the degree of each vertex v∈V is equal to b(v). This problem generalizes metric TSP. In this paper, we show that the problem admits a ρ-approximation algorithm if b(v)≥2, v∈V, where ρ=2.5 if k is even, and ρ=2.5+1.5/k if k is odd. We also prove that the digraph version of this problem admits a 2.5-approximation algorithm and discuss some generalization of metric TSP.     

Development of an epileptic seizure prediction algorithm using R–R intervals with self-attentive autoencoder

Epilepsy is a neurological disorder that may affect the autonomic nervous system (ANS) from 15 to 20 min before seizure onset, and disturbances of ANS affect R–R intervals (RRI) on an electrocardiogram (ECG). This study aims to develop a machine learning algorithm for predicting focal epileptic seizures by monitoring R–R interval (RRI) data in real time. The developed algorithm adopts a self-attentive autoencoder (SA-AE), which is a neural network for time-series data. The results of applying the developed seizure prediction algorithm to clinical data demonstrated that it functioned well in most patients; however, false positives (FPs) occurred in specific participants. In a future work, we will investigate the causes of FPs and optimize the developing seizure prediction algorithm to further improve performance using newly added clinical data.

     

The effect of small dose of topiroxostat on serum uric acid in patients receiving hemodialysis

Introduction : Topiroxostat, a recently developed xanthine oxidase inhibitor, is expected to have fewer adverse effects than allopurinol because it has different mechanism of action from alloprinol. However, its dosage, usage and safety have not been established in patients with impaired renal function or those undergoing dialysis at the development since no studies was conducted in these patients. Methods : Cross over clinical trial using 3 months of allopurinol and topiroxostat on 27 maintain Japanese HD patients were carried out. The effects on oxidative stress status of both drugs were also evaluated by measuring oxidation reduction potential. Findings : Twenty‐five of twenty‐seven patients completed study. The mean serum uric acid levels in the topiroxostat‐treated arm was significantly lower than it in the allopurinol‐treated arm time‐dependently (P < 0.0001). Corrected oxidative stress ratio defined as biological antioxidant potential/diacron reactive oxygen metabolites was significantly increased in topiroxostat‐arm (*P = 0.0035), but not in allopurinol‐arm (P = 0.1429). No significant difference was seen in diacron reactive oxygen metabolites, biological antioxidant potential, static oxidation‐reduction potential, and capacity oxidation‐reduction potential between pre and post treatment of both drugs. Discussion : It is suggested that a low dose of topiroxostat decreased serum uric acid sufficiently to maintain it below 7.0 mg/dL in patients receiving hemodialysis.     

Automated discovery of local search heuristics for satisfiability testing

The development of successful metaheuristic algorithms such as local search for a difficult problem such as satisfiability testing (SAT) is a challenging task. We investigate an evolutionary approach to automating the discovery of new local search heuristics for SAT. We show that several well-known SAT local search algorithms such as Walksat and Novelty are composite heuristics that are derived from novel combinations of a set of building blocks. Based on this observation, we developed CLASS, a genetic programming system that uses a simple composition operator to automatically discover SAT local search heuristics. New heuristics discovered by CLASS are shown to be competitive with the best Walksat variants, including Novelty+. Evolutionary algorithms have previously been applied to directly evolve a solution for a particular SAT instance. We show that the heuristics discovered by CLASS are also competitive with these previous, direct evolutionary approaches for SAT. We also analyze the local search behavior of the learned heuristics using the depth, mobility, and coverage metrics proposed by Schuurmans and Southey.