体外多酶分子机器的现状和最新进展

体外多酶分子机器遵循所设计的多酶催化路径,将若干种纯化或部分纯化的酶元件进行合理的优化与适配,高效地在体外将特定的底物转化为目标化合物。体外多酶分子机器反应系统呈现元件化和模块化的特点,在设计、组装和调控方面具有较高的自由度。近年来,体外多酶分子机器在实现反应过程的精准调控和提高产品得率方面的优势逐渐体现,展示了其在生物制造领域重要的应用潜力。对体外多酶分子机器的相关研究已成为合成生物学的一个重要分支领域,日益受到广泛的关注。文中系统地综述了基于酶元件/模块的体外多酶分子机器的构建策略,以及改善该分子机器中酶元件/模块之间适配性的研究进展,并分析了该生物制造平台的发展前景与挑战。     

The Promises and the Challenges of Biotransformations in Microflow

The challenges of transition toward the postpetroleum world shed light on the biocatalysis as the most sustainable way for the valorization of biobased raw materials. However, its industrial exploitation strongly relies on integration with innovative technologies such as microscale processing. Microflow devices remarkably accelerate biocatalyst screening and engineering, as well as evaluation of process parameters, and intensify biocatalytic processes in multiphase systems. The inherent feature of microfluidic devices to operate in a continuous mode brings additional interest for their use in chemoenzymatic cascade systems and in connection with the downstream processing units. Further steps toward automation and analytics integration, as well as computer‐assisted process development, will significantly affect the industrial implementation of biocatalysis and fulfill the promises of the bioeconomy. This review provides an overview of recent examples on implementation of microfluidic devices into various stages of biocatalytic process development comprising ultrahigh‐throughput biocatalyst screening, highly efficient biocatalytic process design including specific immobilization techniques for long‐term biocatalyst use, integration with other (bio)chemical steps, and/or downstream processing.     

变豆菜属15种植物的果实微形态特征及其分类学意义

采用扫描电镜对来自北美和东亚的变豆菜属植物(美国7个种,中国8个种)的果实表面微形态进行观察,结合前人对伞形科其他类群果实微形态特征的研究及近年来分子系统学证据,对变豆菜属的种间分类进行研究。结果显示,变豆菜属植物果实的形态大小、皮刺弯曲程度和果柄蜡质纹饰丰富多样。研究表明变豆菜属是一个自然类群,果实表面钩刺结构有利于该属植物的传播及扩散,果实微形态特征具有分类学价值,可作为种间分类的依据。根据变豆菜属果实表面微形态特征,编制了该属植物分种检索表。     

Estimation of Respiratory Nasal Pressure and Flow Rate Signals Using Different Respiratory Sound Features

BackgroundRespiratory sounds are associated with the flow rate, nasal flow pressure, and physical characteristics of airways. In this study, we aimed to develop the flow rate and nasal flow pressure estimation models for the clinical application, and find out the optimal feature set for estimation to achieve the optimal model performance.MethodsRespiratory sounds and flow rate were acquired from nine healthy volunteers. Respiratory sounds and nasal flow pressure were acquired from twenty-three healthy volunteers. Four types of respiratory sound features were extracted for flow rate and nasal flow pressure estimation using different estimation models. Effects of estimations using these features were evaluated using Bland-Altman analysis, estimation error, and respiratory sound feature calculation time. Besides, expiratory and inspiratory phases divided estimation errors were compared with united estimation errors.ResultsThe personalized logarithm model was selected as the optimal flow rate estimation model. Respiratory nasal flow pressure estimation based on this model was also performed. For the four different respiratory sound features, there is no statistically significant difference in flow rate and pressure estimation errors. LogEnvelope was, therefore, chosen as the optimal feature because of the lowest computational cost. In addition, for any type of respiratory sound feature, no statistically significant difference was observed between divided and united estimation errors (flow rate and pressure).ConclusionRespiratory flow rate and nasal flow pressure can be estimated accurately using respiratory sound features. Expiratory and inspiratory phases united estimation using respiratory sounds is a more reasonable estimation method than divided estimation. LogEnvelope can be used for this united respiratory flow rate and nasal flow pressure estimation with minimum computational cost and acceptable estimation error.     

Learning the drug target-likeness of a protein

Current drug discovery and development approaches rely extensively on the identification and validation of appropriate targets; for example, those with marketable and robust therapeutics. Wide-ranging efforts have been directed at this problem and various approaches have been developed to identify disease-associated genes as candidates. In this work, we show with statistical significance that successful drug targets, in addition to their linkage to disease, share common characteristics that are disease-independent. For example, marked differences in functional category, tissue specificity, and sequence variability are observed between known targets and average proteins. These results lead to an interesting hypothesis: potentially good drug targets shall have some desired properties, which we refer to as "drug target-likeness" that are beyond their disease-associations. Because of the limited availability of comprehensive protein characteristics data, we tried to learn the drug target-likeness property at the sequence level. Results show that a support vector machine model is able to accurately distinguish targets from nontargets entirely with sequence features. It is our hope that these encouraging results will invite future systematic proteomic scale experiments to gather necessary protein characteristics data for the accurate and predictive definition of "drug target-likeness", providing a new perspective toward understanding and pursuing effective therapeutics.     

子宫内膜癌组织KIF20A、LAPTM4B-35表达与临床病理特征及预后的关系研究

摘要 目的：探讨子宫内膜癌组织驱动蛋白家族成员20A(KIF20A)、溶酶体相关4次跨膜蛋白B-35(LAPTM4B-35)表达与临床病理特征及预后的关系。方法：选择2012年4月至2015年8月期间于我院行手术治疗的80例子宫内膜癌患者作为研究对象。检测子宫内膜癌组织以及距离肿瘤边缘2 cm以上癌旁组织中KIF20A、LAPTM4B-35 mRNA表达水平。分析子宫内膜癌组织中KIF20A、LAPTM4B-35 mRNA表达与临床病理特征的关系。分析不同KIF20A、LAPTM4B-35 mRNA表达患者5年总生存率的差异。分析子宫内膜癌患者预后的影响因素。结果：与癌旁组织相比,子宫内膜癌组织中KIF20A、LAPTM4B-35 mRNA表达水平明显升高,差异有统计学意义（P<0.05）。有淋巴结转移以及FIGO分期Ⅲ期患者的癌组织KIF20A、LAPTM4B-35 mRNA表达水平明显高于无淋巴结转移以及FIGO分期I～II期患者的癌组织,差异有统计学意义（P<0.05）。KIF20A低表达组患者5年总生存率明显高于KIF20A高表达组;LAPTM4B-35低表达组患者5年总生存率明显高于LAPTM4B-35高表达组患者,差异有统计学意义（P<0.05）。Cox回归分析结果显示：FIGO分期Ⅲ期、有淋巴结转移、KIF20A mRNA高表达和LAPTM4B-35 mRNA高表达是子宫内膜癌患者预后的影响因素（P<0.05）。结论：在子宫内膜癌组织中KIF20A、LAPTM4B-35 mRNA表达水平升高,有淋巴结转移、FIGO分期较高患者癌组织KIF20A、LAPTM4B-35 mRNA表达水平上调。KIF20A 、LAPTM4B-35高表达患者5年总生存率下降。