计算机虚拟筛选技术在害虫行为调节剂研究中的应用

害虫行为调节剂是一种以嗅觉系统为靶标的绿色农药,在害虫的田间管理中发挥着重要的作用。然而,其先导化合物的发现通常依赖一系列生物测定的方法,不仅费时费力,且发现效率低。近年来,随着昆虫嗅觉功能数据的积累和结构生物学的飞速发展,以机器学习技术和分子对接为代表的2种基于计算机的药物虚拟筛选方法在害虫行为调节剂的先导化合物研究中发挥着重要的作用,极大地促进了先导化合物的发现效率,减少了筛选的盲目性。本文系统综述了2种虚拟筛选方法及其在害虫行为调节剂先导化合物研究中的应用,并对2种筛选策略在实际应用中存在的问题及应用前景进行了讨论。     

Four-dimensional imaging with virtual reality to quantitatively explore jigsaw puzzle-like morphogenesis of Arabidopsis cotyledon pavement cells

In most dicotyledonous plants, leaf pavement cells exhibit complex jigsaw puzzle-like cell morphogenesis during leaf expansion. Although detailed molecular biological information and mathematical modeling of this jigsaw puzzle-like cell morphogenesis are now available, a full understanding of this process remains elusive. Recent reports have highlighted the importance of three-dimensional (3D) structures (i.e., anticlinal and periclinal cell wall) in understanding the mechanical models that describe this morphogenetic process. We believe that it is important to acquire 3D shapes of pavement cells over time, i.e., acquire and analyze four-dimensional (4D) information when studying the relationship between mechanical modeling and simulations and the actual cell shape. In this report, we have developed a framework to capture and analyze 4D morphological information of Arabidopsis thaliana cotyledon pavement cells by using both direct water immersion observations and computational image analyses, including segmentation, surface modeling, virtual reality and morphometry. The 4D cell models allowed us to perform time-lapse 3D morphometrical analysis, providing detailed quantitative information about changes in cell growth rate and shape, with cellular complexity observed to increase during cell growth. The framework should enable analysis of various phenotypes (e.g., mutants) in greater detail, especially in the 3D deformation of the cotyledon surface, and evaluation of theoretical models that describe pavement cell morphogenesis using computational simulations. Additionally, our accurate and high-throughput acquisition of growing cell structures should be suitable for use in generating in silico model cell structures.     

Ecological memory at millennial time-scales: the importance of data constraints,species longevity and niche features

Ecological memory describes how antecedent conditions drive the dynamics of an ecological system. Palaeoecological records are paramount to understand ecological memory at millennial time-scales, but the concept is widely neglected in the literature, and a formal approach is lacking. Here, we fill such a gap by introducing a quantitative framework for ecological memory in palaeoecology, and assessing how data constraints and taxa traits shape ecological memory patterns. We simulate the population dynamics and pollen abundance of 16 virtual taxa with different life and niche traits as a response to an environmental driver. The data is processed to mimic a realistic sediment deposition and sampled at increasing depth intervals. We quantify ecological memory with Random Forests, and assess how data properties and taxa traits shape ecological memory. We find that life-span and niche features modulate the relative importance of the antecedent values of the driver and the pollen abundance over periods of 240 yr and longer. Additionally, we find that accumulation rate and decreasing pollen-sampling resolution inflate the importance of antecedent pollen abundance. Our results suggest that: 1) ecological memory patterns are sensitive to varying accumulation rates. A better understanding on the numerical basis of this effect may enable the assimilation of ecological memory concepts and methods in palaeoecology; 2) incorporating niche theory and models is essential to better understand the nature of ecological memory patterns at millennial time-scales. 3) Long-lived generalist taxa are highly decoupled from the environmental signal. This finding has implications on how we interpret the abundance-environment relationship of real taxa with similar traits, and how we use such knowledge to forecast their distribution or reconstruct past climate.     

Exploring the carbohydrate‐binding ability of Canavalia bonariensis lectin in inflammation models

Lectins are a group of proteins of non‐immune origin recognized for their ability to bind reversibly to carbohydrates. Researchers have been intrigued by oligosaccharides and glycoconjugates for their involvement as mediators of complex cellular events and then many biotechnological applications of lectins are based on glycocode decoding and their activities. Here, we report a structural and biological study of a ConA‐like mannose/glucose‐specific lectin from Canavalia bonariensis seeds, CaBo. More specifically, we evaluate the binding of CaBo with α‐methyl‐D‐mannoside (MMA) and mannose‐1,3‐α‐D‐mannose (M13) and the resultant in vivo effects on a rat model of acute inflammation. A virtual screening was also carried out to cover a larger number of possible bindings of CaBo. In silico analysis demonstrated the stability of CaBo interaction with mannose‐type ligands, and the lectin was able to induce acute inflammation in rats with the participation of the carbohydrate recognition domain (CRD) and histamine release. These results confirm the ability of CaBo to interact with hybrid and high‐mannose N‐glycans, supporting the hypothesis that CaBo's biological activity occurs primarily through its interaction with cell surface glycosylated receptors.     

Visualizing biomolecular electrostatics in virtual reality with UnityMol‐APBS

Virtual reality is a powerful tool with the ability to immerse a user within a completely external environment. This immersion is particularly useful when visualizing and analyzing interactions between small organic molecules, molecular inorganic complexes, and biomolecular systems such as redox proteins and enzymes. A common tool used in the biomedical community to analyze such interactions is the Adaptive Poisson‐Boltzmann Solver (APBS) software, which was developed to solve the equations of continuum electrostatics for large biomolecular assemblages. Numerous applications exist for using APBS in the biomedical community including analysis of protein ligand interactions and APBS has enjoyed widespread adoption throughout the biomedical community. Currently, typical use of the full APBS toolset is completed via the command line followed by visualization using a variety of two‐dimensional external molecular visualization software. This process has inherent limitations: visualization of three‐dimensional objects using a two‐dimensional interface masks important information within the depth component. Herein, we have developed a single application, UnityMol‐APBS, that provides a dual experience where users can utilize the full range of the APBS toolset, without the use of a command line interface, by use of a simple graphical user interface (GUI) for either a standard desktop or immersive virtual reality experience.     

长江中游鱼类资源量的估算

为了解长江中游的鱼类资源现状,于2018年5和6月以及9和10月在宜昌、石首、洪湖、武汉和湖口5个江段进行了渔获物调查工作。通过统计各江段的渔业捕捞情况,计算年捕捞量。用体长股分析方法,对铜鱼(Coreius heterodon)、鳊(Parabramis pekinensis)和瓦氏黄颡鱼(Tachysurus vachelli)的资源量进行估算,并以此推算各江段的鱼类总资源量。结果显示,宜昌江段的鱼类年总资源量1077.36 t,其中,铜鱼为623.25 t;石首江段的年总资源量为2190.74 t,铜鱼为698.19 t;洪湖江段的鱼类年总资源量为58.57 t,其中,瓦氏黄颡鱼为0.41 t;武汉江段的鱼类年总资源量1010.54 t,其中,鳊为148.65 t;湖口江段的年鱼类总资源量14.55 t,瓦氏黄颡鱼为0.032 t。估算结果可以为长江中游鱼类资源保护措施的制定提供数据参考。     

新工科背景下生物反应工程课程的多元化教学模式 改革与探索

生物反应工程作为一门理论性与应用性都很强的专业课程,在生物工程等相关专业的课程设置中处于桥梁和纽带地位,对新型应用型工科人才的培养发挥着重要的作用。但由于该课程中公式等抽象理论知识过多,导致学生学习效率十分低下。因此,为了适应新工科教育背景下对创新型人才培养的需求,提高学生的学习兴趣和积极性,并培养学生的自主学习等创新能力,教学团队在课程教学中通过引入虚拟仿真技术、开展微课教学、采用案例式教学模式、利用科研平台等多元化方式,对该课程的教学模式、方法和手段尝试改革和探索,取得了一定的教学效果,并就此进行了一些探讨,以期能为相关课程的教学改革提供一些思路和启示。     

A gait index may underestimate changes of gait: a comparison of the Movement Deviation Profile and the Gait Deviation Index

The ability of the Movement Deviation Profile (MDP) and Gait Deviation Index (GDI) to detect gait changes was compared in a child with cerebral palsy who underwent game training. Conventional gait analysis showed that sagittal plane angles became mirrored about normality after training. Despite considerable gait changes, the GDI showed minimal change, while the MDP detected a difference equal to a shift between 10-9 on the Functional Assessment Questionnaire scale. Responses of the GDI and MDP were examined during a synthetic transition of the patient's curves from before intervention to a state mirrored about normality. The GDI showed a symmetric response on the two opposite sides of normality but the neural network based MDP gave an asymmetric response reflecting faithfully the unequal biomechanical consequences of joint angle changes. In conclusion, the MDP can detect altered gait even if the changes are missed by the GDI.