Initiation of Protein Synthesis with Non‐Canonical Amino Acids In Vivo

By transplanting identity elements into E. coli tRNA^fMet, we have engineered an orthogonal initiator tRNA (itRNA^Ty2) that is a substrate for Methanocaldococcus jannaschii TyrRS. We demonstrate that itRNA^Ty2 can initiate translation in vivo with aromatic non‐canonical amino acids (ncAAs) bearing diverse sidechains. Although the initial system suffered from low yields, deleting redundant copies of tRNA^fMet from the genome afforded an E. coli strain in which the efficiency of non‐canonical initiation equals elongation. With this improved system we produced a protein containing two distinct ncAAs at the first and second positions, an initial step towards producing completely unnatural polypeptides in vivo. This work provides a valuable tool to synthetic biology and demonstrates remarkable versatility of the E. coli translational machinery for initiation with ncAAs in vivo.     

A network-based pharmacology study of active compounds and targets of Fritillaria thunbergii against influenza

Seasonal and pandemic influenza infections are serious threats to public health and the global economy. Since antigenic drift reduces the effectiveness of conventional therapies against the virus, herbal medicine has been proposed as an alternative. Fritillaria thunbergii (FT) have been traditionally used to treat airway inflammatory diseases such as coughs, bronchitis, pneumonia, and fever-based illnesses. Herein, we used a network pharmacology-based strategy to predict potential compounds from Fritillaria thunbergii (FT), target genes, and cellular pathways to better combat influenza and influenza-associated diseases. We identified five compounds, and 47 target genes using a compound-target network (C-T). Two compounds (beta-sitosterol and pelargonidin) and nine target genes (BCL2, CASP3, HSP90AA1, ICAM1, JUN, NOS2, PPARG, PTGS1, PTGS2) were identified using a compound-influenza disease target network (C-D). Protein-protein interaction (PPI) network was constructed and we identified eight proteins from nine target genes formed a network. The compound-disease-pathway network (C-D-P) revealed three classes of pathways linked to influenza: cancer, viral diseases, and inflammation. Taken together, our systems biology data from C-T, C-D, PPI and C-D-P networks predicted potent compounds from FT and new therapeutic targets and pathways involved in influenza.     

基于支持向量机的肤色滤波器

为了探测图像中的肤色像素,提出了一种新的方法-支持向量机（SVM：Support Vector Machine）方法.它是一种基于肤色的非特定人的面部定位方法,是非接触人机交互技术和机器视觉中的一个重要内容.实验结果表明,采用支持向量机方法较传统人工神经网络方法不仅有更高的探测准确性,而且具有更好的推广性能.由于SVM采用结构风险最小化（SRM：Structural Risk Minimization）准则,在最小化训练误差（经验风险）的同时,尽量缩小模型预测误差的上界,从而使模型有更好的泛化能力.     

GPON体系结构研究

千兆比特无源光网络(GPON)是一种面向下一代网络(NGN)的接入技术,它具有速率高、传输距离长、效率高和可伸缩性强等关键优势.同时,GPON支持引入更高带宽的以太网新业务,并能低成本提供传统的语音服务.介绍了GPON的标准化进展,分析了GPON的系统结构和协议参考模型,并给出了传输汇聚层的分层结构.     

碳纳米管原子力显微镜针尖在结构生物学研究中的应用

碳纳米管以其较小的半径、较高的纵横比和高的柔韧性成为原子力显微镜对结构生物学进行研究的理想针尖。新的制备方法获得了亚纳米级半径的碳纳米管针尖,运用它们得到了生物大分子及其复合物的生物结构,并获得了新的生物信息,这用传统的原子力显微镜针尖是无法实现的。     

中药复杂组效关系的变结构神经网络辨识方法

针对中药复杂组效关系的辨识问题,研究了变结构多层前馈神经网络,推导出一种新型的变结构网络学习算法,成功地应用于中药川芎药效活性预测计算.该方法从一个规模较小的网络出发,当网络无法达到预定的学习精度时,自动增加隐含层神经元个数,并在原有学习结果的基础上确定新的网络参数,自适应地确定前馈神经网络结构,可用于处理复杂化学模式信息.计算机仿真实验结果表明,该方法能有效地确定多层前馈神经网络的最佳结构,提高网络学习效率和函数逼近精度,解决复杂非线性函数映射关系准确建模问题.     

浙北富硒土壤地球化学特征与生物学效应

通过对杭嘉湖平原富硒区研究,发现区内富硒土壤主要分布在环湖平原区,土壤具有特殊的地球化学性质,表现为土壤酸性,土壤硒全量0.3～0.5 mg/kg,有机质含量高、重金属含量低,土壤质地较黏重,土壤硒与有机质关系密切,而与土壤pH相关性不明显等特点。在土壤有机质丰富和氧化条件下,农产品中硒含量较高,重金属低于限量标准,具有较好的开发远景。     

Network dimensionality and ligand flexibility in lanthanide terephthalate hydrates

Various lanthanide open framework materials incorporating the terephthalate (TP) entity were prepared using hydrothermal synthesis methods at a moderate temperature of 170 °C. The compounds Nd₂(TP)₃(H₂O)₄(1), Er₂(TP)₃(H₂O)₄(2), Yb₂(TP)₃(H₂O)₂(3), Yb₂(TP)₃(H₂O)₆(4), and Yb₂(TP)₃(H₂O)₈·2H₂O (5), were characterized by single crystal structural analysis and FT-IR spectroscopy. While compounds 1 and 2 have been reported before on the basis of powder X-ray diffraction, the structural characterization of any ytterbium terephthalate species is unprecedented. Compounds 1-5 crystallize in triclinic settings with space group P-1. The compounds are compared with their previously reported Er and Tb-counterparts and the reduction of the dimensionality of the resulting networks from 3D over 2D to 1D with increasing level of hydration is discussed. Compounds 1, 2, and 3 with the lowest water content assemble in three-dimensional network lattices. Compounds 4 and 5, however, form 2D layered systems and 1D rod like chains, respectively, which are held together by hydrogen bonds originating from coordinating H₂O. The crystal lattices of the 3D networks experience higher levels of tension as can be seen by increasing out-of-plane torsion with regard to the terephthalate carboxylate groups. Moreover, there seems to be a correlation between the level of strain on the aromatic ligands and the reduction of the number of carboxylate oxygen atoms that are part of the coordination polyhedra.     

理、化、生不同专业大学生关于能量概念的认识现状研究

能量概念是科学教育的一个核心概念,也是近年来国际科学教育研究的一个热点话题。在柳秀峰、Wilson等人的研究基础上,构建了能量概念的认识模型。基于该模型,并结合国内物理、化学和生物等不同专业的中学、大学教材中涉及的能量相关概念,笔者编制了调查问卷,对北京师范大学物理、化学和生物等不同专业的共280名大学生进行了测查和访谈。通过Rasch模型和SPSS统计分析发现,不同学科背景的学生对能量概念的认识角度和水平存在差异,而且存在一些偏差认识。基于学生的认识现状,笔者最后构建了关于能量概念认识的难度进阶,并对能量概念的教学提出了建议。