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.     

In Operando Optical Tracking of Oxygen Vacancy Migration and Phase Change in few Nanometers Ferroelectric HZO Memories

Ferroelectric materials offer a low-energy, high-speed alternative to conventional logic and memory circuitry. Hafnia-based films have achieved single-digit nm ferroelectricity, enabling further device miniaturization. However, they can exhibit nonideal behavior, specifically wake-up and fatigue effects, leading to unpredictable performance variation over consecutive electronic switching cycles, preventing large-scale commercialization. The origins are still under debate. Using plasmon-enhanced spectroscopy, a non-destructive technique sensitive to <1% oxygen vacancy variation, phase changes, and single switching cycle resolution, the first real-time in operando nanoscale direct tracking of oxygen vacancy migration in 5 nm hafnium zirconium oxide during a pre-wake-up stage is provided. It is shown that the pre-wake-up leads to a structural phase change from monoclinic to orthorhombic phase, which further determines the device wake-up. Further migration of oxygen ions in the phase changed material is then observed, producing device fatigue. These results provide a comprehensive explanation for the wake-up and fatigue with Raman, photoluminescence and darkfield spectroscopy, combined with density functional theory and finite-difference time-domain simulations.     

Morphology-controlled therapeutic activity of cerium oxide nanoparticles for mild traumatic brain injury

The design and optimization of nanostructures with unique morphologies and properties are at the forefront of biomedical nanotechnology. Cerium oxides are widely used to investigate the effect of morphology on performance. However, elucidating the morphology–activity relationship of cerium oxide nanocrystals in biomedical applications remains challenging. Herein, the therapeutic effects of cerium oxide nanoparticles with different morphologies: cerium oxide nanorods with two different aspect ratios (CeO_x NRs_A and CeO_x NRs_B), cerium oxide nanopolyhedra (CeO_x NPs), and cerium oxide nanocubes (CeO_x NCs) are investigated in in vivo and in vitro mild traumatic brain injury (TBI) models. Cerium oxide nanoparticles inhibit oxidative stress and inflammation after mild TBI, alleviating cognitive impairment; furthermore, the therapeutic effect is significantly affected by their morphology. Owing to the higher Ce³⁺/Ce⁴⁺ ratio, exposure of more active crystal surfaces, and greater number of exposed oxygen vacancies, CeO_x NRs show better activity than CeO_x NPs and CeO_x NCs for mild TBI. Among the two investigated types of cerium oxide nanorods, CeO_x NRs_A, with a higher Ce³⁺/Ce⁴⁺ ratio on the surface, appear to spread better than CeO_x NRs_B in the injured lesions. The factors causing morphology-controlled biomedical performance, such as Ce³⁺/Ce⁴⁺ molar ratio, surface area, and aspect ratio, are discussed.