Dietary exposure to acrylamide in a group of Japanese adults based on 24-hour duplicate diet samples

Acrylamide is a probable human carcinogen and known human neurotoxin that can be generated in food through heating. Using a mathematical modelling approach, our previous study estimated long-term average dietary exposure to acrylamide in the Japanese people; however, the validity of these estimates remained unknown. Here, we aimed to obtain a more accurate estimate of acrylamide exposure that would reflect the usual practice of heat processing and consumption of foods in the population. We collected duplicate diet samples and dietary records during 24 h from a group of Japanese adults. A total of 110 duplicate diet samples were analysed for acrylamide by LC-MS/MS. Data from individual dietary records were used to examine the association between dietary acrylamide exposure and consumption of selected food groups (e.g., coffee, tea, confectioneries, and vegetables prepared at high temperature [deep-frying, stir-frying, sautéing, and baking]). Of the 110 homogenised diet samples, 108 contained detectable levels of acrylamide. Dietary exposure to acrylamide ranged from 8 to 1582 ng/kg body weight (bw)/day, with the mean value of 215 ng/kg-bw/day and median value of 143 ng/kg-bw/day. This mean value was higher than the value we previously estimated for Japanese adults using a mathematical approach. Multiple linear regression analysis showed log dietary acrylamide exposure was significantly associated with consumption of coffee and vegetables prepared at high temperature during 24-hr of sampling (adj. R² = 0.250, p < 0.001). We revealed significant difference in dietary acrylamide exposure between participants who had coffee and vegetables prepared at high temperature (median, 169 ng/kg-bw/day; range, 35–1224 ng/kg-bw/day, n = 42) and those who had none of them (median, 75 ng/kg-bw/day; range, 8–311 ng/kg-bw/day, n = 15) (Steel-Dwass test, p < 0.05).     

Use of a YAP1 overexpression cassette conferring specific resistance to cerulenin and cycloheximide as an efficient selectable marker in the yeast Saccharomyces cerevisiae.

Drug-resistance markers for yeast transformation are useful because they can be applied to strains without auxotrophic mutations. However, they are susceptible to technical difficulties, namely lower transformation efficiency and the appearance of drug-resistant mutants without the marker. To avoid these problems, we have constructed a phosphoglycerate kinase (PGK) promoter-driven YAP1 expression cassette, called PGKp-YAP1. Yeast cells containing PGKp-YAP1 were resistant to cycloheximide, a protein synthesis inhibitor, and also to cerulenin, a fatty acid synthesis inhibitor, but not to other drugs tested. The transformation efficiency of PGKp-YAP1 using cerulenin selection was comparable to that using a URA3 auxotrophic marker when low concentrations of cerulenin were used. Non-transformed drug-resistant colonies did appear on the low-concentration cerulenin plates. However, these non-transformed colonies could easily be identified, based on their cycloheximide sensitivity and/or their resistance to aureobasidin A to which the transformants were sensitive. Therefore, the dual drug resistance of PGKp-YAP1 could be used as an effective selection for PGKp-YAP1 recipient cells. The PGKp-YAP1 marker was used to disrupt the LYS2 gene and to transform an industrial yeast strain, indicating that this marker can be used for efficient and reliable gene manipulations in any Saccharomyces cerevisiae strain.     

Dissolution of Ti wires in sulphuric acid and hydrochloric acid solutions

Ti wire electrodes were immersed in acidic solutions containing H₂SO₄ and HCl of various concentrations at 353 K to evaluate corrosion rate by measurement of electric resistance change (resistometry). Addition of hydrochloric acid to sulphuric acid solution promoted depassivation of Ti. After depassivation, the immersion potential dropped to the hydrogen evolution potential and a hydride layer was formed on the surface. The hydride layer dissolved continuously in the acidic solution. SEM observation showed that Ti wires dissolved almost uniformly in the early stage and that the dissolution then trace became irregular due to nonuniform growth of the hydride layer. Dissolution rate of a Ti wire was estimated almost accurately by resistometry.     

XIII. Yeast sequencing reports. Cloning and sequencing of the NES24 gene of Saccharomyces cerevisiae

We have cloned NES24 using a temperature-sensitive nes24-1 mutant as a host and sequenced a 3162 bp XhoI-EcoRI DNA fragment containing the NES24 gene. Computer analysis revealed that this segment contains a 1806 bp open reading frame which is needed for complementation of the nes24-1 mutation. We found SUP8 in the region upstream of the NES24 gene, placing the NES24 gene on chromosome XIII. A protein homology search indicated that NES24 encodes a new protein. The disruption of the NES24 gene resulted in temperature-sensitive growth. The sequence has been deposited in DDBJ/EmBL/GenBank data bases under Accession Number D15052.     

Synthesis of poly(α-thiophenediyl)benzylidene with high molecular weight and its thermal stability

Summary The synthesis of poly(-thiophenediyl)benzylidene (PTB) with high molecular weight is described. Number-average degrees of polymerization reached about 74. The characterizations of the polymer was investigated by ¹H-NMR, ¹³C-NMR, IR, and UV-VIS spectra. The polymer with well-defined structure and high molecular weight was obtained by polymerization at low temperature and in polar solvent. This polymer was thermally stable and a thermal decomposition took place at 391°C under nitrogen and at 370°C under air. The glass transformation temperature was 117°C and this PTB was nonfusible.     

Interfacial Reactions between Sapphire and Silver—Copper—Titanium Thin Film Filler Metal

Wetting and brazing studies of sputtering-deposited, submicrometer thin film filler metal in an Ag—Cu—Ti/Al₂O₃ system were performed. The interfacial reaction layer between the filler metal and Al₂O₃ was investigated. It is possible to make a brazing joint even with a reaction layer of less than 100 nm thickness. Different types of interfacial reaction layers were observed when the Ti content in the filler metal was varied. The Cu—Ti—O system compounds were observed in the samples with high wetting capabilities, but not in the sample with low wetting characteristics. It was found that these compounds are substances that promote effective brazing.     

Segmented conjugated polymer based on poly(α-thiophenediyl)benzylidine

Summary Segmented polymers with random sequences of conjugated and non-conjugated blocks are produced by partial dehydrogenation of poly(-thiophenediyl)benzylidene. The fraction of conjugated block was controlled by the elimination time. The polymers gave photoluminescence. Absorption coefficients of the polymers increased with the rate of dehydrogenation, and the highest fluorescence intensity were achieved around 9 % conjugation conversion. The polymers were characterized by ¹H- and ¹³C-n.m.r. and infrared spectra, and were soluble in common organic solvents, which suggests a good processability.     

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.     

Attribute-based quality classification of academic papers

Investigating the relevant literature is very important for research activities. However, it is difficult to select the most appropriate and important academic papers from the enormous number of papers published annually. Researchers search paper databases by combining keywords, and then select papers to read using some evaluation measure—often, citation count. However, the citation count of recently published papers tends to be very small because citation count measures accumulated importance. This paper focuses on the possibility of classifying high-quality papers superficially using attributes such as publication year, publisher, and words in the abstract. To examine this idea, we construct classifiers by applying machine-learning algorithms and evaluate these classifiers using cross-validation. The results show that our approach effectively finds high-quality papers.