Dietary Intake of 17α-Ethinylestradiol Promotes HCC Progression in Humanized Male Mice Expressing Sex Hormone-Binding Globulin

Hepatocellular carcinoma (HCC) is a male-oriented malignancy; its progression is affected by sex hormones. 17α-ethinylestradiol (EE2) is a synthetic estrogen widely used as an oral contraceptive; however, it is unknown whether EE2 regulates sex hormone action in HCC. We investigated whether EE2 influences HCC risk in male androgenic environments, using mice expressing human sex hormone-binding globulin (SHBG). Two-week-old male mice were injected with diethyl-nitrosamine (DEN, 25 mg/kg) and fed an EE2 diet for 10 weeks from 30 weeks of age. Development and characteristics of liver cancer were evaluated in 40-week-old mice via molecular and histological analyses. Although EE2 did not increase HCC progression in wild-type mice, SHBG mice exhibited remarkably higher HCC risk when fed EE2. The livers of EE2-treated SHBG mice exhibited substantially increased pro-inflammatory necrosis with high plasma levels of ALT and HMGB1, and intrahepatic injury and fibers. Additionally, increased androgen response and androgen-mediated proliferation in the livers of EE2-treated SHBG mice and EE2-exposed hepatocytes under SHBG conditions were observed. As a competitor of SHBG-androgen binding, EE2 could bind with SHBG and increase the bioavailability of androgen. Our results revealed that EE2 is a novel risk factor in androgen-dominant men, predisposing them to HCC risk.     

Effect of prepolymer structure on the electro-optic performance of polymer dispersed liquid crystals

The effect of prepolymer structure on the electro-optic properties of polymer dispersed liquid crystals (PDLCs) prepared from UV-cured polyurethane acrylates (PUAs) has been studied. Among four types of films with different soft-segment structure, polypropylene glycol (PPG)- and polytetramethyl ether glycol (PTMG)-based PUAs gave lower threshold (V₁₀) and operating (V₉₀) voltages, whereas polycaprolactone diol (PCL)-based PUAs gave higher V₁₀ and V₉₀ voltages. The use of mixed polyol polypropylene glycol/ poly(tetramethylene adipate)diol) (PPG/PTAd) gave an electro-optic response intermediate between the two. Regarding the effect of hard segment type, that from a linear aliphatic diisocyanate (hexamethylene diisocyanate, HDI) gave the lowest V₁₀ and V₉₀ voltages as well as transparent–translucent transition temperature compared with those from cycloaliphatic diisocyanates. This was interpreted in terms of a more flexible nature and hence a lower glass transition temperature of HDI-based PUA. © 1998 SCI.     

Protein Ligation-Assisted Reconstitution of Split HRP Fragments for Facile Production of HRP Fusion Proteins in E. coli

Horseradish peroxidase (HRP) is a pivotal biocatalyst for biosensor development and fine chemical synthesis. HRP proteins are mostly extracted and purified from the roots of horseradish because the solubility and productivity of recombinant HRP in bacteria are significantly low. In this study, we investigate the reconstitution system of split HRP fragments to improve its soluble expression levels in E. coli allowing the cost-effective production of bioactive HRPs. To promote the effective association between two HRP fragments (HRPn and HRPc), we exploit SpyTag-SpyCatcher chemistry, a versatile protein coupling method with high affinity and selectivity. Each HRP fragment was genetically fused with SpyTag and SpyCatcher, respectively, exhibiting soluble expression in the E. coli cytoplasm. The engineered split HRPs were effectively and irreversibly reconstituted into a biologically active and stable assembly that can catalyze intrinsic enzymatic reactions. Compared to the chaperone co-expression system, our approach shows that the production yield of soluble HRP is comparable, but the purity of the final product is relatively high. Therefore, our results can be applied to the high-yield production of recombinant HRP variants and other difficult-to-express proteins in bacteria without complex downstream processes.     

Control strategies of energy storage limiting intermittent output of solar power generation: Planning and evaluation for participation in electricity market

Renewable energy generation cannot be consistently predicted or controlled. Therefore, it is currently not widely used in the electricity market, which requires dependable production. In this study, reliability- and variance-based controls of energy storage strategies are proposed to utilize renewable energy as a steady contributor to the electricity market. For reliability-based control, photovoltaic (PV) generation is assumed to be registered in the power generation plan. PV generation yields a reliable output using energy storage units to compensate for PV prediction errors. We also propose a runtime state-of-charge management method for sustainable operations. With variance-based controls, changes in rapid power generation are limited through ramp rate control. This study introduces new reliability and variance indices as indicators for evaluating these strategies. The reliability index quantifies the degree to which the actual generation realizes the plan, and the variance index quantifies the degree of power change. The two strategies are verified based on simulations and experiments. The reliability index improved by 3.1 times on average over 21 days at a real power plant.     

Correction to: Food-derived coagulase-negative Staphylococcus as starter cultures for fermented foods

Food Science and Biotechnology - The article “Food-derived coagulase-negative Staphylococcus as starter cultures for fermented foods”, written by Sojeong Heo, Jong-Hoon Lee, and Do-Won...     

A novel MobileNet with selective depth multiplier to compromise complexity and accuracy

In the last few years, convolutional neural networks (CNNs) have demonstrated good performance while solving various computer vision problems. However, since CNNs exhibit high computational complexity, signal processing is performed on the server side. To reduce the computational complexity of CNNs for edge computing, a lightweight algorithm, such as a MobileNet, is proposed. Although MobileNet is lighter than other CNN models, it commonly achieves lower classification accuracy. Hence, to find a balance between complexity and accuracy, additional hyperparameters for adjusting the size of the model have recently been proposed. However, significantly increasing the number of parameters makes models dense and unsuitable for devices with limited computational resources. In this study, we propose a novel MobileNet architecture, in which the number of parameters is adaptively increased according to the importance of feature maps. We show that our proposed network achieves better classification accuracy with fewer parameters than the conventional MobileNet.     

A rhodamine B-based colorimetric chemosensor for sensitive and selective detection of Cu2+: Test strip analysis and density functional theory

We designed a rhodamine B-based colorimetric chemosensor BHSO ((Z)-3′,6′-bis(diethylamino)-2-(2-(((8-hydroxy-2,3,6,7-tetrahydro-1H,5H-pyrido[3,2,1-ij]quinolin-9-yl)methylene)amino)ethyl)spiro[isoindoline-1,9′-xanthen]-3-one) for detecting Cu²⁺. In the presence of Cu²⁺, BHSO caused a colour variation from colourless to bright orange. The limit of detection for Cu²⁺ towards BHSO was 0.73 μM. The binding of BHSO to Cu²⁺ was analysed as a 1:1 ratio through a Job plot and electrospray ionisation mass spectrometry. BHSO can detect readily Cu²⁺ with a test strip by colorimetric variation. The detecting process of Cu²⁺ by BHSO was represented by ultraviolet-visible titration, electrospray ionisation mass spectrometry, proton nuclear magnetic resonance titration, Job plot and density functional theory calculations.