高通量计算与深度学习相结合的稠环含能化合物设计

含能化合物的设计效率决取于多方面因素，如筛选空间中潜在高性能样本的占比和关键性能的准确预测方法。本研究提出预筛选分子骨架提升虚拟筛选空间整体性能的方案，并将高通量计算与深度学习相结合用于含能化合物设计。研究发现，含能分子的晶体密度与其骨架密度之间存在中度的正相关性，通过预筛选高密度分子骨架可以有效提升虚拟筛选空间的整体密度。研究基于晶体学数据库CCDC提供的含能晶体密度数据集，采用深度学习方法获得含能晶体的密度预测模型，具有可靠的精度和泛化性。在此基础上，以稠环类含能化合物为研究对象，通过骨架预筛选获得高密度的稠环分子骨架，从而通过分子片段组装获得由潜在的高密度分子组成的虚拟筛选空间。研究采用量子化学计算和爆轰产物状态方程等方法实现了生成焓、爆轰性能和化学稳定性的预测，从而由性能排序筛选出能量水平优于RDX，稳定性优于TNT的新型含能分子6个。研究表明，分子骨架预筛选可以有效提升虚拟筛选空间的总体性能，在此基础上借助高通量计算与深度学习可实现含能分子的高效设计。     

数据驱动的蒸发器在线建模方法

针对蒸发器离线建模方法对变量运行工况范围要求较大的问题，利用K-means算法对辨识模型的观测数据进行聚类筛选处理，提出一种基于数据的蒸发器在线建模方法。首先利用DB准则和PSO算法提出K-means算法中最优分类数K*和最优初始聚类中心的确定方法，提高算法的收敛速度，并使用改进的K-means算法获得各簇聚类中心来代替辨识模型的观测数据，减少模型辨识的数据量。然后利用已有的蒸发器模型结构以及模型辨识方法，对模型进行辨识。实验结果表明：利用聚类筛选前、后的观测数据所辨识的模型精度基本相当，分别在±3%和±3.5%以内。最后利用在线观测数据到各聚类中心欧氏距离的分析判断，提出蒸发器的在线建模方法。该方法可以先采用小工况范围的少量离线数据辨识模型，再利用在线数据修正模型参数，扩大模型的适用范围。     

Effect of trace contaminants on cold soak filterability of canola biodiesel

A cold soak filtration test (CSFT; ASTM D 7501-09b) was included in B100 specifications under ASTM D 6751-09, bringing new challenges to biodiesel producers and researchers investigating B100 quality. For a plant breeding program evaluating canola biodiesel quality traits, rapid assessment of biodiesel quality is important. Typically, a limited amount of seed from new canola lines is available; therefore, obtaining the required volume of biodiesel for evaluating cold soak filterability (300 mL) is not possible. In order to rapidly screen canola breeding lines for B100 quality, cold soak filterability must be assessed with reduced volumes of biodiesel. The primary objective of this study was to evaluate the impact of saturated monoglycerides, glycerin, and soap on cold soak filterability. Biodiesel filtration time rapidly escalated when the SMG concentration was above 0.28%. The influence of saturated monoglycerides (0.04-0.46% w/w) on biodiesel precipitate formation was also evaluated. A regression model was generated to predict the filterability of biodiesel against the concentrations of trace contaminants. The results will be instrumental to scaling down biodiesel CSFT for a canola breeding program.     

A Case Study on the Keap1 Interaction with Peptide Sequence Epitopes Selected by the Peptidomic mRNA Display

Many protein–protein and peptide–protein interactions (PPIs) play key roles in the regulation of biological functions, and therefore, the modulation of PPIs has become an attractive target of new drug development. Although a number of PPIs have already been identified, over 100 000 unknown PPIs are predicted to exist. To uncover such unknown PPIs, it is important to devise a conceptually distinct method from that of currently available methods. Herein, an mRNA display by using a total RNA library derived from various human tissues, which serves as a unique method to physically isolate peptide epitopes that potentially bind to a target protein of interest, is reported. In this study, selection was performed against Kelch-like ECH-associated protein (Keap1) as a model target protein, leading to a peptide epitope originating from astrotactin-1 (ASTN1). It turned out that this ASTN1 peptide was able to interact with Keap1 more strongly than that with a known peptide derived from Nrf2; a well-known, naturally occurring Keap1 binder. This case study demonstrates the applicability of peptidomic mRNA display for the rapid exploration of consensus binding peptide motifs and the potential for the discovery of unknown PPIs with other proteins of interest.     

Screening of Nanocomposite Scaffolds Arrays Using Superhydrophobic‐Wettable Micropatterns

Platforms containing multiple arrays for high‐throughput screening are demanded in the development of biomaterial libraries. Here, an array platform for the combinatorial analysis of cellular interactions and 3D porous biomaterials is described. Using a novel method based on computer‐aided manufacturing, wettable regions are printed on superhydrophobic surfaces, generating isolated spots. This freestanding benchtop array is used as a tool to deposit naturally derived polymers, chitosan and hyaluronic acid, with bioactive glass nanoparticles (BGNPs) to obtain a scaffold matrix. The effect of fibronectin adsorption on the scaffolds is also tested. The biomimetic nanocomposite scaffolds are shown to be osteoconductive, non‐cytotoxic, promote cell adhesion, and regulate osteogenic commitment. The method proves to be suitable for screening of biomaterials in 3D cell cultures as it can recreate a multitude of combinations on a single platform and identify the optimal composition that drives to desired cell responses. The platforms are fully compatible with commercially routine cell culture labware and established characterization methods, allowing for a standard control and easy adaptability to the cell culture environment. This study shows the value of 3D structured array platforms to decode the combinatorial interactions at play in cell microenvironments.     

The analysis of dioxins and related compounds

The analysis of polychlorinated dibenzo‐p‐dioxins, polychlorinated dibenzofurans, polychlorinated biphenyls, and other related compounds requires complex sample preparation and analytical procedures using highly sensitive and selective state‐of‐the‐art instrumentation to meet very stringent data quality objectives. The analytical procedures (extraction, sample preparation), instrumentation (chromatographic separation and detection by mass spectrometry) and screening techniques for the determination of dioxins, furans, dioxin‐like polychlorinated biphenyls and related compounds with a focus on new approaches and alternate techniques to standard regulatory methods are reviewed. © 2009 Wiley Periodicals, Inc., Mass Spec Rev 29:526–559, 2010     

高产脂肪酶菌株的筛选及产酶条件研究

从油坊土壤、饭店、食堂油烟机排气孔等8个取样点获得16份样品,通过溴甲酚紫平板初筛和摇瓶发酵复筛选出9株产脂肪酶量高的菌株,其中一菌株A7的产量最高,其酶活为12.9U/mL,以菌株A7为出发菌株再进行发酵培养基的研究。经过单因素和正交试验,确定脂肪酶高产的最佳培养基为:大豆油5g/L、蛋白胨20g/L、MgSO_47H_2O 0.4g/L、初始pH 6.0,培养温度30℃,摇床转速200r/min,优化后产酶量达到19.8U/mL。     

几种灰霉病测定方法在新化合物筛选中应用

简述了几种灰霉病测定方法,提出在化合物筛选中应采用花器接种测定方法和幼苗接种测定方法.