Production of the Carboxylate Reductase from Nocardia otitidiscaviarum in a Soluble,Active Form for in vitro Applications

Accessing aldehydes from carboxylate moieties is often a challenging task. In this regard, carboxylate reductases (CARs) are promising catalysts provided by nature that are able to accomplish this task in just one step, avoiding over-reduction to the alcohol product. However, the heterologous expression of CARs can be quite difficult due to the excessive formation of insoluble protein, thus hindering further characterization and application of the enzyme. Here, the heterologous production of the carboxylate reductase from Nocardia otitidiscaviarum (NoCAR) was optimized by a combination of i) optimized cultivation conditions, ii) post-translational modification with a phosphopantetheinyl transferase and iii) selection of an appropriate expression strain. Especially, the selection of Escherichia coli tuner cells as host had a strong effect on the final 110-fold increase in the specific activity of NoCAR. This highly active NoCAR was used to reduce sodium benzoate to benzaldehyde, and it was successfully assembled with an in vitro regeneration of ATP and NADPH, being capable of reducing about 30 mM sodium benzoate with high selectivity in only 2 h of reaction.     

Sirtuins as Important Factors in Pathological States and the Role of Their Molecular Activity Modulators

Sirtuins (SIRTs), enzymes from the family of NAD⁺-dependent histone deacetylases, play an important role in the functioning of the body at the cellular level and participate in many biochemical processes. The multi-directionality of SIRTs encourages scientists to undertake research aimed at understanding the mechanisms of their action and the influence that SIRTs have on the organism. At the same time, new substances are constantly being sought that can modulate the action of SIRTs. Extensive research on the expression of SIRTs in various pathological conditions suggests that regulation of their activity may have positive results in supporting the treatment of certain metabolic, neurodegenerative or cancer diseases or this connected with oxidative stress. Due to such a wide spectrum of activity, SIRTs may also be a prognostic markers of selected pathological conditions and prove helpful in assessing their progression, especially by modulating their activity. The article presents and discusses the activating or inhibiting impact of individual SIRTs modulators. The review also gathered selected currently available information on the expression of SIRTs in individual disease cases as well as the biological role that SIRTs play in the human organism, also in connection with oxidative stress condition, taking into account the progress of knowledge about SIRTs over the years, with particular reference to the latest research results.     

No-reference quality assessment of dynamic sports videos based on a spatiotemporal motion model

This paper proposes an approach to improve the performance of no-reference video quality assessment for sports videos with dynamic motion scenes using an efficient spatiotemporal model. In the proposed method, we divide the video sequences into video blocks and apply a 3D shearlet transform that can efficiently extract primary spatiotemporal features to capture dynamic natural motion scene statistics from the incoming video blocks. The concatenation of a deep residual bidirectional gated recurrent neural network and logistic regression is used to learn the spatiotemporal correlation more robustly and predict the perceptual quality score. In addition, conditional video block-wise constraints are incorporated into the objective function to improve quality estimation performance for the entire video. The experimental results show that the proposed method extracts spatiotemporal motion information more effectively and predicts the video quality with higher accuracy than the conventional no-reference video quality assessment methods.     

A recurrent neural network using historical data to predict time series indoor PM2.5 concentrations for residential buildings

Due to the severe outdoor PM2.5 pollution in China, many people have installed air-cleaning systems in homes. To make the systems run automatically and intelligently, we developed a recurrent neural network (RNN) that uses historical data to predict the future indoor PM2.5 concentration. The RNN architecture includes an autoencoder and a recurrent part. We used data measured in an apartment over the course of an entire year to train and test the RNN. The data include indoor/outdoor PM2.5 concentration, environmental parameters and time of day. By comparing three different input strategies, we found that a strategy employing historical PM2.5 and time of day as inputs performed best. With this strategy, the model can be applied to predict the relatively stable trend of indoor PM2.5 concentration in advance. When the input length is 2 h and the prediction horizon is 30 min, the median prediction error is 8.3 µg/m³ for the whole test set. For times with indoor PM2.5 concentrations between (20,50] µg/m³ and (50,100] µg/m³, the median prediction error is 8.3 and 9.2 µg/m³, respectively. The low prediction error between the ground-truth and predicted values shows that the RNN can predict indoor PM2.5 concentrations with satisfactory performance.     

Influence of tetraploid wheat (Triticum dicoccum) on low glycaemic index pizza base processing and its starch digestibility

The present study aimed to utilise Dicoccum wheat (DW), barley (BF) and soya flour (SF) in the development of low in vitro starch digestibility (IVSD) and estimated glycaemic index (EGI) PB. The BF and SF are mixed (1:1) (BFSF) and used to replace DW at 25%, 50% and 75% level and compared with 100% DW. The quality characteristics (rheological, physical, textural and chemical), IVSD and EGI of PB were determined. The incorporation of BFSF to DW increased the farinograph water absorption capacity (58.1%–64.2%) and mixing tolerance index (21-68 FU), and decreased the dough development time (4.3–2.8 min) and amylograph pasting properties, respectively. Further, the thickness, shear force and redness were decreased and lightness and yellowness increased. Based on the physico-sensory studies, 50% of BFSF along with emulsifier’s incorporation was optimum without affecting any sensory parameters and this PB had decreased IVSD (31) and EGI (54) when compared to the control 37 and 63, respectively.     

浓香型白酒窖泥放线菌的原位分离及代谢特性研究

以川南某浓香型白酒生产企业50年窖龄且发酵正常的窖泥为研究对象。通过高通量测序技术分析细菌群落结构以及放线菌群落结构,利用原位分离法从中分离得到2株放线菌,结合形态鉴定、生理生化和16S rRNA基因序列比对分析确定菌种属,并对其进行耐酸、耐乙醇特性研究,基于风味导向思路,分别对2株菌进行液态培养和固态培养,采用顶空固相微萃取法和气相色谱质谱联用对发酵挥发性产物进行分析,为放线菌的相关研究和应用提供理论参考。结果显示,放线菌在该窖泥样品含有较高操作分类单元(operational taxonomic unit,OTU),相对丰度达(10.7±3.4)%,且主要分布于链霉菌亚目(Streptomycineae)和科里氏杆菌亚目(Coriobacterineae)。采用原位分离法分离放线菌,将分离得到的2株菌编号为A1、A2,菌株A1鉴定为桑氏链霉菌(Streptomyces sampsonii),菌株A2鉴定为鲁地链霉菌(Streptomyces rutgersensis)。菌株A1、A2均可在pH>4.3或乙醇体积分数<6%的环境中生长。菌株A1在液态和固态发酵条件下都会产生大量土臭素以及萜烯类物质,菌株A2在液态条件下能产生多种酯类,其中己酸乙酯相对含量(5.384%)较高,而固态条件下能够检测出大量的3-羟基-2丁酮、2,3-丁二醇和吡嗪类物质。     

Using deep learning to combine static and dynamic power analyses of cryptographic circuits

Side-channel attacks have shown to be efficient tools in breaking cryptographic hardware. Many conventional algorithms have been proposed to perform side-channel attacks exploiting the dynamic power leakage. In recent years, with the development of processing technology, static power has emerged as a new potential source for side-channel leakage. Both types of power leakage have their advantages and disadvantages. In this work, we propose to use the deep neural network technique to combine the benefits of both static and dynamic power. This approach replaces the classifier in template attacks with our proposed long short-term memory network schemes. Hence, instead of deriving a specific probability density model for one particular type of power leakage, we gain the ability of combining different leakage sources using a structural algorithm. In this paper, we propose three schemes to combine the static and dynamic power leakage. The performance of these schemes is compared using simulated test circuits designed with a 45-nm library.     

It doesn’t take a village to fall for misinformation: Social media use,discussion heterogeneity preference,worry of the virus,faith in scientists,and COVID-19-related misinformation beliefs

With the circulation of misinformation about the COVID-19 pandemic, the World Health Organization has raised concerns about an “infodemic,” which exacerbates people’s misperceptions and deters preventive measures. Against this backdrop, this study examined the conditional indirect effect of social media use and discussion heterogeneity preference on COVID-19-related misinformation beliefs in the United States, using a national survey. Findings suggested that social media use was positively associated with misinformation beliefs, while discussion heterogeneity preference was negatively associated with misinformation beliefs. Furthermore, worry of COVID-19 was found to be a significant mediator as both associations became more significant when mediated through worry. In addition, faith in scientists served as a moderator that mitigated the indirect effect of discussion heterogeneity preference on misinformation beliefs. That is, among those who had stronger faiths in scientists, the indirect effect of discussion heterogeneity preference on misinformation belief became more negative. The findings revealed communication and psychological factors associated with COVID-19-related misinformation beliefs and provided insights into coping strategies during the pandemic.     

Synthesis of cubic and monoclinic hafnia nanoparticles by pulsed plasma in liquid method

Hafnia (HfO₂, hafnium dioxide) is a wide band gap and high-κ material, and the metastable cubic hafnia has a much higher permittivity compared with the normal monoclinic hafnia. Here, we employ a one-step process, the pulsed plasma in liquid (PPL) method to synthesize two types of hafnia nanoparticles (NPs): one which is mainly in cubic phase (cubic: 81.7 at%, monoclinic: 18.3 at%) and the other which is in monoclinic phase. High-resolution transmission electron microscopy images showed that the particles were small (particle size ~3 nm). X-ray absorption fine structure analysis showed no chemical shifts, indicating that the synthetic hafnia NPs contained no oxygen vacancy. The synthetic hafnia NPs mainly in cubic phase showed a much higher relative permittivity than that of the commercial hafnia (monoclinic), and have a larger band gap than the synthetic monoclinic hafnia NPs.     

煤矿冲击地压与冒顶复合灾害研究

随着煤矿向深部发展,矿井动力灾害既表现出冲击地压的部分特征,又表现出冒顶的部分特征。2种典型的灾害打破以往冒顶与冲击地压的发生具有一种互为逆向性的认知规律,在深部高应力煤巷,特别是留顶煤巷道中出现了相互诱导、复合发生的新灾害类型。在总结山东、山西和新疆矿区典型巷道冲击致顶板(顶煤)动力灾害特征的基础上,提出了深部巷道冲击地压与冒顶复合灾害的概念、机理与分类,指出复合灾害机理关键点在于揭示巷道整体系统和破碎区子系统的稳定原理及其2者间的相互影响。建立了巷道发生复合灾害的力学模型,根据扰动响应失稳判据,提出并得到了巷道发生复合灾害的临界应力Pcr、临界软化区半径ρ_cr和最大容许采扰应力增量σ_max,厘清了灾害发生的主控因素,分析了煤岩冲击倾向指数K、支护强度ps、巷道半径ρ₀、煤岩强度σ_c等对灾害发生的影响规律,同时阐明了围岩塑性软化、破碎深度随地应力增加的发育规律。研究结果表明,破碎发育巷道的动力失稳主体为弹性区、软化区与破碎区构成的不稳定系统,垮落主体为破碎区;稳定的破碎区提升了巷道冲击启动临界值,使其启动难度增大,但破碎区的发育又易引起顶煤垮落;巷道稳定支护是解决复合灾害的关键,科学合理支护既能有效调控围岩破碎防冒,又能提升冲击启动临界值。通过理论研究,揭示了巷道冲击地压与冒顶复合灾害的发生机理,阐明了巷道软化与破碎区及其稳控支护对深部破碎发育巷道动力灾害防治的重要性。