培养液对胚胎早期发育动态表型和动力学参数的影响:一项time-lapse研究

目的探讨胚胎早期发育动态表型和动力学参数是否受培养液组分差异的影响。方法回顾性队列研究分析广西壮族自治区人民医院生殖医学与遗传中心2016年10月至2018年12月期间收治的体外受精(in vitro fertilization,IVF)周期患者的临床资料,根据使用的培养液品牌不同,将IVF周期分为Cook组和Vitrolife组,经1∶1倾向性评分匹配后,每组纳入59个,采用延时成像技术分析正常受精卵裂胚胎授精后68 h内的早期发育形态动力学。记录胚胎发育动态表型,比较两组胚胎7种发育动态表型构成的差异;计算正常表型胚胎的13个早期发育动力学参数,比较两组之间动力学参数的差异;基于两个已发表的time-lapse胚胎筛选模型,比较两组正常动态表型胚胎的等级分布差异。结果①Cook组胚胎发育动态表型构成如下:正常表型54.0%、胞质异常波动(abnormal first cytokinesis,A1^(cyt))3.0%、不规则卵裂(abnormal cleavage,AC)17.4%、逆向卵裂(reverse cleavage,RC)5.2%、无序卵裂(chaotic cleavage,CC)3.2%、多核(multinucleation,Mn)3.5%以及混合表型13.7%;Vitrolife组胚胎发育动态表型构成如下:正常表型49.3%、A1^(cyt) 4.0%、AC 19.1%、RC 7.5%、CC 2.1%、Mn 6.4%以及混合表型11.6%,两组间表型构成差异没有统计学意义(P>0.05)。②相较于Vitrolife组,Cook组正常动态表型胚胎13个发育动力学参数(tPNa、tPNf、t2、t3、t4、t5、t6、t7、t8、cc2、s2、t5_PNf和t8_PNf)均略长,授精后68 h胚胎平均卵裂球数略少,但差异均无统计学意义(均P>0.05)。③基于模型A,Vitrolife组与Cook组胚胎等级分布差异没有统计学意义(P>0.05);基于模型B,两组胚胎等级分布差异存在统计学意义(P=0.040),其中Vitrolife组A+级胚胎比例较Cook组高[59.8%(125/209)比43.3%(94/217)],而C级胚胎比例较Cook组低[9.6%(20/209)比20.3%(44/217)]。结论胚胎早期发育动态表型及动力学参数不受Cook与Vitrolife序贯培养液差异的影响,但不同time-lapse胚胎筛选模型对不同培养液体系的适用性存在差异,选择或建立模型时应充分考虑所使用的胚胎培养液体系。

种子动态萌发表型分析算法的研究和软件实现

[目的]种子是植物研究中重要的对象之一,本研究旨在对关键种子萌发表型进行动态监测及量化分析,为了解不同植物生存、生长和繁衍提供表型依据。[方法]本研究以小麦(Triticum aestivum)为研究对象,利用监督式机器学习算法(如K近邻、支持向量机、随机森林),在不同颜色空间上对3种弱筋小麦品种的种子萌发图像序列进行前、背景对象训练及背景分割,然后通过构建自动化图像处理算法进行目标提取,再结合图论和二维骨架动态分析幼根和根尖点的位置变化,实现关键萌发性状的高通量数字化提取。[结果]本研究可获得大量人工难以计量的萌发性状,包括种子长、宽、面积、周长,幼根和幼芽长度及生长速率等。通过与人工统计数据的线性回归分析,关键动态性状如幼根长、根生长速率、芽长的决定系数R 2值分别为0.922(n=188,P<0.001,RMSE=1.727)、0.719(n=191,P<0.001,RMSE=0.406)、0.897(n=115,P<0.001,RMSE=2.726)。[结论]本研究提出的算法能有效获取种子萌发动态表型组,并可扩展至棉花(Gossypium barbadense)和油菜(Brassica napus),为遗传育种和植物研究提供表型分型依据和智能化解析技术。

口腔癌引流区淋巴结细胞培养不同时间的表型动态分析

通过流式细胞仪，利用抗人Ｔ细胞单克隆抗体系列（ＯＫＴ３，ＯＫＴ４，ＯＫＴ８），对６例口腔癌引流区淋巴结细胞（ＤＮＬ）进行了培养前后的动态定量分析。结果显示：培养前后均以Ｔ淋巴细胞为主，平均为５８．３７％和７２．１３％；ＯＫＴ３＋和ＯＫＴ８＋亚群由培养前１３．１８％，１７．２１％，上升到培养后的５０．３９％，５２．６５％，ＯＫＴ４／ＯＫＴ８值为１：１．１５。结果还揭示：ＤＮＬ细胞主要是Ｔ淋巴细胞组成，其中亚群以Ｔ８（细胞毒Ｔ细胞）占多数；ＯＫＴ４／ＯＫＴ８比值同健康人外周血比值相比呈现例置；机体免疫功能的稳定在一定程度上依赖Ｔ细胞亚群之间协调的比例。

Characterizing and Analyzing the Airflow Field inside the Nozzle Block of Murata Vortex Spinning

A three-dimensional computational fluid dynamics model is developed by software Fluent 6.2, to simulate the flow field inside the nozzle block of the Murata vortex spinning. The flowing state and the distribution law of static pressure and velocity are characterized and analyzed. The relationship between the flowing state and the structure of the vortex spun yarn is also discussed. The research results can enhance the understanding of the yarn formation principle from viewpoint of the airflow field law inside the nozzle block of Murata vortex spinning.

Violent Transient Sloshing-Wave Interaction with a Baffle in a Three-Dimensional Numerical Tank

A finite difference model for solving Navier Stokes viscous liquid sloshing-wave interaction with baffles in a tank. equations with turbulence taken into accotmt is used to investigate The volume-of-fluid and virtual boundary force methods are employed to simulate free surface flow interaction with structures. A liquid sloshing experimental apparatus was established to evaluate the accuracy of the proposed model, as well as to study nonlinear sloshing in a prismatic tank with the baffles. Damping effects of sloshing in a rectangular tank with bottom-mounted vertical baffles and vertical baffles touching the free surface are studied numerically and experimentally. Good agreement is obtained between the present numerical results and experimental data. The numerical results match well with the current experimental data for strong nonlinear sloshing with large free surface slopes. The reduction in sloshing-wave elevation and impact pressure induced by the bottom-mounted vertical baffle and the vertical baffle touching the free surface is estimated by varying the external excitation frequency and the location and height of the vertical baffle under horizontal excitation.

Knowledge representation and rule-based solution system for dynamic programming model

A knowledge representation has been proposed using the state space theory of Artificial Intelligence for Dynamic Programming Model, in which a model can be defined as a six tuple M=(I,G,O,T,D,S). A building block modeling method uses the modules of a six tuple to form a rule based solution model. Moreover, a rule based system has been designed and set up to solve the Dynamic Programming Model. This knowledge based representation can be easily used to express symbolical knowledge and dynamic characteristics for Dynamic Programming Model, and the inference based on the knowledge in the process of solving Dynamic Programming Model can also be conveniently realized in computer.

Expression profiling suggests a regulatory role of gallbladder in lipid homeostasis

AIM: To examine expression profile of gallbladder using microarray and to investigate the role of gallbladder in lipid homeostasis.METHODS: 33P-labelled cDNA derived from total RNA of gallbladder tissue was hybridized to a cDNA array representing 17 000 cDNA clusters. Genes with intensities ≥2 and variation ＜0.33 between two samples were considered as positive signals with subtraction of background chosen from an area where no cDNA was spotted. The average gray level of two gallbladders was adopted to analyze its bioinformatics. Identified target genes were confirmed by touch-down polymerase chain reaction and sequencing.RESULTS: A total of 11 047 genes expressed in normal gallbladder, which was more than that predicted by another author, and the first 10 genes highly expressed (high gray level in hybridization image), e.g. ARPC5 (2 225.88±90.46), LOC55972 (2 220.32±446.51) and SLC20A2 (1 865.21±98.02), were related to the function of smooth muscle contraction and material transport. Meanwhile, 149 lipid-related genes were expressed in the gallbladder, 89 of which were first identified (with gray level in hybridization image), e.g. FASN (11.42±2.62), APOD (92.61±8.90) and CYP21A2 (246.11±42.36), and they were involved in each step of lipid metabolism pathway. In addition, 19 of those 149 genes were gallstone candidate susceptibility genes (with gray level in hybridization image), e.g. HMGCR (10.98±0.31), NPC1 (34.88±12.12) and NR1H4 (16.8±0.65), which were previously thought to be expressed in the liver and/or intestine tissue only. CONCLUSION: Gallbladder expresses 11 047 genes and takes part in lipid homeostasis.

A KAD Network Evolution Model Based on Node Behavior

An evolution model of KAD Dynamic Model Network(KDMN) is proposed to study the reason of hot node and simulate the process of network evolution based on node behavior from a holistic perspective.First,some symbols and meanings are introduced to describe nodes relationship and network states at a time step.Second,some evolution rules for network are formulated when node behaviors of join,exit,routing table update,data retrieval and content index distribution happen with different contextual scene in KAD network.In addition,a lightweight simulator is designed to implement the KDMN model.Moreover,an example of how to use the simulator to simulate the network changes in order to observe the result is described in detail.Finally,the KDMN is applied to analyze the reason for the formation of hot nodes in the BT and eMule network in the experiment.The different evolution principles of local priority,global priority and hybrid random are adopted based on the provision of network protocol of BT and eMule.The result of this experiment demonstrates that there are some hot nodes exist in the KAD network.However,the principle of hybrid random can effectively alleviate the phenomenon that a node is widely linked with others compared with global and local priority.

A statistical dynamics model of the marine ecosystem and its application in Jiaozhou Bay

Models of marine ecosystem dynamics play an important role in revealing the evolution mechanisms of marine ecosystems and in forecasting their future changes. Most traditional ecological dynamics models are established based on basic physical and biological laws, and have obvious dynamic characteristics and ecological significance. However, they are not flexible enough for the variability of environment conditions and ecological processes found in offshore marine areas, where it is often difficult to obtain parameters for the model, and the precision of the model is often low. In this paper, a new modeling method is introduced, which aims to establish an evolution model of marine ecosystems by coupling statistics with differential dynamics. Firstly, we outline the basic concept and method of inverse modeling of marine ecosystems. Then we set up a statistical dynamics model of marine ecosystems evolution according to annual ecological observation data from Jiaozhou Bay. This was done under the forcing conditions of sea surface temperature and surface irradiance and considering the state variables of phytoplankton, zooplankton and nutrients. This model is dynamic, makes the best of field observation data, and the average predicted precision can reach 90% or higher. A simpler model can be easily obtained through eliminating the terms with smaller contributions according to the weight coefficients of model differential items. The method proposed in this paper avoids the difficulties of obtaining and optimizing parameters, which exist in traditional research, and it provides a new path for research of marine ecological dynamics.

An integrative view of the signaling phenotype： Dynamic links between signals, physiology, behavior and social context

Signal traits are often linked with the physiological state and behavior of their bearer. Direct examination of the causal links among these variables has provided substantial insight into the information content of signals, and into the costs and benefits of signal expression. Yet recent empirical work suggests that the social context in which signals are developed and displayed can play a major role not only in how signals are received, but also in coordinating and mediating the signaling phenotype itself. Here we review both well-established and emerging evidence for direct feedbacks among an individual＇s physiological state, be- havior, and signal elaboration. We then describe an integrative view of signaling that takes into account the bidirectional rela- tionships among components of phenotype and the social context in which signals are developed and displayed. Integrating dy- namic feedback between context and phenotype within models of the evolution and maintenance of signals may yield insights into how signals evolve, how signaling phenotypes are coordinated and maintained on ecological and evolutionary time scales, and how static signals continue to convey relevant phenotypic information about their bearer through time.

Cogitation on developing a dynamic model of soil wind erosion

Studies on soil wind erosion began with single factors affecting soil wind erosion; with increasing quantities of data being accumulated,the wind erosion equation(WEQ),the revised wind erosion equation(RWEQ),the wind erosion prediction system(WEPS),and other soil wind erosion models have been successively established,and great advances have been achieved.Here we briefly review the soil wind erosion research course and analyze the advantages and disadvantages of the current soil wind erosion models.From the perspective of the dynamics of wind erosion,we classified the factors affecting soil wind erosion into three categories,namely,wind erosivity factors(WEF),soil antierodibility factors(SAF),and roughness interference factors(RIF).We proposed the concept of a standard plot of soil wind erosion to solve the problem of uncertainty of the soil wind erosion modulus on a spatial scale,and provided methods to set similarity conditions in wind tunnel simulation experiments and to convert the spatial scale of the wind erosion modulus from the standard plot to a large scale field.We also proposed a conceptual model on the basis of the dynamics of soil wind erosion with the theoretical basis that wind produces a shear force on the soil surface.This shear force is partitioned by barely erodible soil surfaces and roughness elements on the ground,and the amount of soil loss by wind should be calculated by comparing the shear force of the wind on barely erodible soil surfaces with the anti-erosion force of the surface soil.One advantage of this conceptual model is that the calculated soil wind erosion modulus is not subject to changes of spatial scale.Finally,we recommended continual improvement of the existing models while also establishing new models.