Investigation of visual perception of position based on the reafferent theory

In relation to the historical controversy between the outflow theorists and inflow theorists, a clear-cut model is presented to clucidate the visual perception of movement. It may be regarded as an extention of reafferent theory. The model makes it possible to perform examinations into available experimental data. Namely, it is assumed that there is a simulator of muscle-eye-ball dynamics, the input to which is supplied from the voluntary efferent signal generated to fix the visual target on the retina. Then the perceived sensation is obtained as the sum of the target position on the retina and the output of the simulator. Experimental data concerning the larget tracking, oculogyral illusion, oculogravic illusion, and autokinesis are examined. In most cases the model works well. In some cases, however, where mutually contradictory experimental results are reported, the validity of the model cannot be tested until unified and reliable data are obtained.     

基于最大熵模型的不同尺度物种分布概率优化热点分析: 以红色木莲为例

单一空间尺度构建的最大熵(maximum entropy, MaxEnt)模型是否具有代表性, 是MaxEnt模型应用与发展中面临的重要问题。本研究基于有效的地理分布位点数据, 利用最小凸多边形法(the minimum convex polygon method)在三江并流、云南省及全国3个空间尺度下分别识别了红色木莲(Manglietia insignis)的建模区域, 并进一步建立MaxEnt模型: 使用ROC曲线分析法与遗漏率(omission rate, OR)检验评估MaxEnt模型预测精度; 基于ArcGIS分析分布概率及其热点区域的分布趋势, 并通过分区统计工具Zonal识别潜在适宜分布区域的质心位置; 采用刀切法检验环境因子贡献率。结果表明: (1)不同尺度下红色木莲的MaxEnt模型都有良好的预测效果, 三江并流、云南省及全国尺度下的AUC值分别为0.936、0.887和0.930, OR值分别为0.18、0.15和0.20; (2)各尺度红色木莲的适生区格局呈现一致性分布趋势, 集中在独龙江、怒江和澜沧江3个流域; (3) 3个空间尺度下红色木莲的地理分布受不同环境因子影响, 存在着尺度依赖效应。由此可见, 红色木莲在不同空间尺度下的预测模型有着稳定的性能表现与良好的预测效果。此外, 我们建议在野外实地调查与野生生物资源保护中加强对普通物种的关注, 在预测物种地理分布的研究中将MaxEnt模型与热点分析结合使用。     

A unified framework for unraveling the functional interaction structure of a biomolecular network based on stimulus-response experimental data

We propose a unified framework for the identification of functional interaction structures of biomolecular networks in a way that leads to a new experimental design procedure. In developing our approach, we have built upon previous work. Thus we begin by pointing out some of the restrictions associated with existing structure identification methods and point out how these restrictions may be eased. In particular, existing methods use specific forms of experimental algebraic equations with which to identify the functional interaction structure of a biomolecular network. In our work, we employ an extended form of these experimental algebraic equations which, while retaining their merits, also overcome some of their disadvantages. Experimental data are required in order to estimate the coefficients of the experimental algebraic equation set associated with the structure identification task. However, experimentalists are rarely provided with guidance on which parameters to perturb, and to what extent, to perturb them. When a model of network dynamics is required then there is also the vexed question of sample rate and sample time selection to be resolved. Supplying some answers to these questions is the main motivation of this paper. The approach is based on stationary and/or temporal data obtained from parameter perturbations, and unifies the previous approaches of Kholodenko et al. (PNAS 99 (2002) 12841-12846) and Sontag et al. (Bioinformatics 20 (2004) 1877-1886). By way of demonstration, we apply our unified approach to a network model which cannot be properly identified by existing methods. Finally, we propose an experiment design methodology, which is not limited by the amount of parameter perturbations, and illustrate its use with an in numero example.     

Predicting the global areas for potential distribution of Gastrodia elata based on ecological niche models

Aims Previous studies on the globally suitable areas for growing the medicinal plant Gastrodia elata is lacking. This study aims to predict the global areas for potential distribution of this plant based on multiple ecological niche models. Methods A total of 220 global distribution points of G. elata and 19 ecological variables were compiled and eight environmental variables were selected for the model training. Three ecological niche models, including BIOCLIM, DOMAIN, and MAXENT, were used to predict the global areas for potential distribution of G. elata. The resulting data of different models were analyzed and compared with two statistical criteria: the area under the receiver operating characteristic curve (AUC) and Kappa value. Important findings The predictions of the three models are basically identical, showing that the global areas for potential distribution of G. elata are predominantly in the range of 20° N to 50° N in Asia, mainly in China, South Korea and Japan. A small proportion of the suitable areas occur in India, Nepal and the European countries near Mediterranean. The most suitable areas distribute in provinces close to the Sichuan Basin and the central East China, the mid-eastern parts of South Korea such as Chungcheongbuk-do, Gyeongsangbuk-do and Gyeongsangnam- do, and the Kyushu region and the Shikoku region on Japan’s main island. Therefore, these three countries can be used as the main production areas of G. elata for its commercial development. The AUC average values of the three models are all above 0.9 and the Kappa average values all above 0.65, justifying their applications for predicting the potential areas of G. elata. Among them, the MAXENT model appears to perform the best, followed by DOMAIN and BIOCLIM.     

Apparent discontinuities in the phase-resetting response of cardiac pacemakers

Injection of a brief stimulus pulse resets the spontaneous periodic activity of a sinoatrial node cell: a stimulus delivered early in the cycle generally delays the time of occurrence of the next action potential, while the same stimulus delivered later causes an advance. We investigate resetting in two models, one with a slow upstroke velocity and the other with a fast upstroke velocity, representing central and peripheral nodal cells, respectively. We first formulate each of these models as a classic Hodgkin-Huxley type of model and then as a model representing a population of single channels. In the Hodgkin-Huxley-type model of the slow-upstroke cell the transition from delay to advance is steep but continuous. In the corresponding single-channel model, due to the channel noise then present, repeated resetting runs at a fixed stimulus timing within the transitional range of coupling intervals lead to responses that span a range of advances and delays. In contrast, in the fast-upstroke model the transition from advance to delay is very abrupt in both classes of model, as it is in experiments on some cardiac preparations ("all-or-none" depolarization). We reduce the fast-upstroke model from the original seven-dimensional system to a three-dimensional system. The abrupt transition occurs in this reduced model when a stimulus transports the state point to one side or the other of the stable manifold of the trajectory corresponding to the eigendirection associated with the smaller of two positive eigenvalues. This stable manifold is close to the slow manifold, and so canard trajectories are seen. Our results demonstrate that the resetting response is fundamentally continuous, but extremely delicate, and thus suggest one way in which one can account for experimental discontinuities in the resetting response of a nonlinear oscillator.     

Modeling of glycerol production by fermentation in different reactor states

A kinetic model of glycerol production by fermentation with the osmophilic yeast Candida krusei was studied firstly by analogies to published works. Considering that the glycerol produced competes with glucose, as a second carbon source for energy maintenance, mathematical models of glucose utilization and glycerol accumulation were modified further. By adjusting only two variable macrokinetic parameters, K_S and β, the model simulations could fit experimental data well when the reactor was changed from Airlift Loop Reactor in different scale or airlift mode to Stirred Vessel. To avoid a significant reduction in glycerol production in the latter fermentation stage, the final condition of the fermentation, determined by the concentration ratio of glycerol to glucose, was also investigated in four different Reactor States. The kinetic models and simulation results can provide certain reference for scale up of glycerol production by fermentation.     

Fixation in haploid populations exhibiting density dependence II: the quasi-neutral case

We determine fixation probabilities in a model of two competing types with density dependence. The model is defined as a two-dimensional birth-and-death process with density-independent death rates, and birth rates that are a linearly decreasing function of total population density. We treat the 'quasi-neutral case' where both types have the same equilibrium population densities. This condition results in birth rates that are proportional to death rates. This can be viewed as a life history trade-off. The deterministic dynamics possesses a stable manifold of mixtures of the two types. We show that the fixation probability is asymptotically equal to the fixation probability at the point where the deterministic flow intersects this manifold. The deterministic dynamics predicts an increase in the proportion of the type with higher birth rate in growing populations (and a decrease in shrinking populations). Growing (shrinking) populations therefore intersect the manifold at a higher (lower) than initial proportion of this type. On the center manifold, the fixation probability is a quadratic function of initial proportion, with a disadvantage to the type with higher birth rate. This disadvantage arises from the larger fluctuations in population density for this type. These results are asymptotically exact and have relevance for allele fixation, models of species abundance, and epidemiological models.     

基于多次重复液相质谱生物实验数据校准方法研究

在蛋白质组学中,进行液相质谱(LC-MS)实验谱数据处理,发现并分析生物标志物的复杂肽或蛋白质样本的差异是重点,而校准相同样本的多次重复实验中肽链产生的洗脱时间峰信号(LC峰)是进行量化、分析差异的关键。目前多个重复实验数据的校准通常是在重复的实验数据集中根据液相二级质谱(LC-MS/MS)实验标识LC峰的时间特征,然后使用翘曲函数对时间特征进行对齐。由于多重数据的洗脱时间误差产生是随机的,统一使用翘曲函数校准会产生较大误差。为了解决这个问题,本研究重点研究了多个重复实验数据中LC峰的时间校准算法。我们选取了两个重复实验数据,采用机器学习的思路,通过选用两个数据的LC-MS/MS中重复检测到的肽链数据作为可信数据,部分选为训练序列,部分作为测试序列,建立统计数学模型,提出了一种新的校准算法,并采用测试序列对该统计模型进行准确率测试,表明算法的准确性达到95%以上;然后,将该模型应用在两个实验数据的所有LC-MS/MS肽链检测值上,提高检测值在多个数据中的覆盖率,表明覆盖率可以到达85%以上。     

Uromyces scutellatus as a keystone species affecting Euphorbia spp. in Europe as shown by effects on density in the field

Nearest neighbor spatial analysis was used to assess the effect of systemic rust caused by Uromyces scutellatus on stand density of Euphorbia esula/virgata, a highly invasive deep-rooted perennial weed of rangelands and natural areas in North America. ANOVA applied to nearest neighbor measurements within four pairs of stands in close proximity, with and without rust, in Hungary and Austria indicated that the stand densities of plants of E. esula/virgata in three of four rusted stands were less than companion stands with little or no rust. Using the nearest neighbor distance data, E. esula/virgata densities within stands where rust was prevalent were 48-73% of those with little or no rust. The fourth stand with rust was denser than a symptomless companion stand in 2004, but nearly all plants had symptoms. The same diseased stand was dramatically reduced in density when surveyed the following year and all plants observed in 2005 displayed rust symptoms. These findings indicate the potential impact of the microcyclic autoecious rust U. scutellatus should it be introduced as a biocontrol agent for E. esula/virgata in North America.     

Automatic 3D protein structure classification without structural alignment.

In this paper, we present a new scheme named ProtClass for automatic classification of three-dimensional (3D) protein structures. It is a dedicated and unified multiclass classification scheme. Neither detailed structural alignment nor multiple binary classifications are required in this scheme. We adopt a nearest neighbor-based classification strategy. We use a filter-and-refine scheme. In the first step, we filter out the improbable answers using the precalculated parameters from the training data. In the second, we perform a relatively more detailed nearest neighbor search on the remaining answers. We use very concise and effective encoding schemes of the 3D protein structures in both steps. We compare our proposed method against two other dedicated protein structure classification schemes, namely SGM and CPMine. The experimental results show that ProtClass is slightly better in accuracy than SGM and much faster. In comparison with CPMine, ProtClass is much more accurate, while their running times are about the same. We also compare ProtClass against a structural alignment-based classification scheme named DALI, which is found to be more accurate, but extremely slow. The software is available upon request from the authors. The supplementary information on ProtClass method can be found at: http://xena1.ddns.comp.nus.edu.sg/ approximately genesis/PClass.htm.     

Anatomical Feature Segmentation of Femur Point Cloud Based on Medical Semantics

Feature segmentation is an essential phase for geometric modeling and shape processing in anatomical study of human skeleton and clinical digital treatment of orthopedics. Due to various degrees of freedom of bone surface, the existing segmentation algorithms can hardly meet specific medical need. To address this, a novel segmentation methodology for anatomical features of femur model based on medical semantics is put forward. First, anatomical reference objects (ARO) are created to represent typical characteristics of femur anatomy by 3D point fitting in combination with medical priori knowledge. Then, local point clouds between adjacent anatomies are selected according to the AROs to extract boundary feature point (BFP)s. Finally, the complete model of femur is divided into anatomical regions by executing the enhanced watershed algorithm guided with BFPs. Experimental results show that the proposed method has the advantages of automatic segmentation of femoral head, neck and other complex areas, and the segmentation results have better medical semantics. In addition, the slight modification of segmentation results can be achieved by adjusting a few threshold parameter values, which improves the convenience of modification for ordinary users.     

Morphometric study of the mandibular condyle of the rat during postnatal development

A morphometric technique for the use of the temporomandibular joint (TMJ) of the rat as an experimental model was developed to study TMJ growth from birth to 120 days of age. Experimental conditions for the reduction and embedding of the specimen, as well as for data collection were standardized. Morphometric data were obtained from projected drawings and the areas occupied by the various structures were determined by counting points with a specially constructed integration grid. The areas occupied by the layers making up the mandibular condyle remained relatively constant, forming an architectural pattern from the 30th postnatal day on. Between the 10th and 30th day they underwent modifications interpreted to be functional adaptations conditioned by changes in the animal's feeding habits.     

Pharmacodynamics simulation of HOEC by a computational model of arachidonic acid metabolic network

Background: Arachidonic acid (AA) metabolic network is activated in the most inflammatory related diseases, and small-molecular drugs targeting AA network are increasingly available. However, side effects of above mentioned drugs have always been the biggest obstacle. (+)-2-(1-hydroxyl-4-oxocyclohexyl) ethyl caffeate (HOEC), a natural product acted as an inhibitor of 5-lipoxygenase (5-LOX) and 15-LOX in vitro, exhibited weaker therapeutic effect in high dose than that in low dose to collagen induced arthritis (CIA) rats. In this study, we tried to elucidate the potential regulatory mechanism by using quantitative pharmacology. Methods: First, we generated an experimental data set by monitoring the dynamics of AA metabolites’ concentration in A23187 stimulated and different doses of HOEC co-incubated RAW264.7. Then we constructed a dynamic model of A23187-stimulated AA metabolic model to evaluate how a model-based simulation of AA metabolic data assists to find the most suitable treatment dose by predicting the pharmacodynamics of HOEC. Results: Compared to the experimental data, the model could simulate the inhibitory effect of HOEC on 5-LOX and 15-LOX, and reproduced the increase of the metabolic flux in the cyclooxygenase (COX) pathway. However, a concomitant, early-stage of stimulation-related decrease of prostaglandins (PGs) production in HOEC incubated RAW264.7 cells was not simulated in the model. Conclusion: Using the model, we predict that higher dose of HOEC disrupts the flux balance in COX and LOX of the AA network, and increased COX flux can interfere the curative effects of LOX inhibitor on resolution of inflammation which is crucial for the efficient and safe drug design.     

中国北方5种栎属树木多度分布及其对未来气候变化的响应

植物分布与气候之间的关系是预估未来气候变化对生态系统影响的实现基础。以往的物种分布模型通常以物种的分布区或者分布点的物种存在数据作为物种分布的响应变量。相较于物种存在数据, 多度反映了一个物种占用资源并把资源分配给个体的能力, 更能衡量物种对区域生态系统的影响。该研究通过野外调查获取了华北及周边地区1 045个样方的栎属树木多度, 利用广义线性模型、广义加性模型和随机森林模型模拟栓皮栎(Quercus variabilis)、麻栎(Q. acutissima)、槲栎(Q. aliena)、锐齿槲栎(Q. aliena var. acuteserrata)和蒙古栎(Q. mongolica) 5个树种多度的地理分布及未来2个不同时期(2050年和2070年)的潜在分布。结果表明: 随机森林模型对5个栎属树种的多度的拟合结果要优于广义线性模型和广义加性模型; 典型浓度路径(RCP) 8.5下的5个栎属树种在未来两个时期的多度变化幅度都要大于RCP 2.6下的变化, 在超过一半面积的区域中麻栎、槲栎、锐齿槲栎和蒙古栎的多度减少, 其中内蒙古东北部和黑龙江北部地区是5种栎属植物多度减少的集中分布地区。未来气候变化背景下, 需要加强对这几个区域的监测与物种保护。     

Widespread allele-specific topological domains in the human genome are not confined to imprinted gene clusters

Neural networks such as variational autoencoders (VAE) perform dimensionality reduction for the visualization and analysis of genomic data, but are limited in their interpretability: it is unknown which data features are represented by each embedding dimension. We present siVAE, a VAE that is interpretable by design, thereby enhancing downstream analysis tasks. Through interpretation, siVAE also identifies gene modules and hubs without explicit gene network inference. We use siVAE to identify gene modules whose connectivity is associated with diverse phenotypes such as iPSC neuronal differentiation efficiency and dementia, showcasing the wide applicability of interpretable generative models for genomic data analysis.

     

The impact of local spatial resistance on the movement behaviour of Tenebrio molitor L.

Although the impact of vegetation and other environmental factors on the distribution of terrestrial invertebrates has been known since the 1950s, basic knowledge about their interaction with micro-landscape elements is lacking. In experimental model systems, the impact of varying local spatial resistance (LSR) on the distribution of Tenebrio molitor individuals was analysed in the laboratory. In the setups, LSR led to a reduction of the average distance covered (move step length) and a reduction of the velocity (the maximum speed ranging from 36.1 in the control groups to 20.4 [mm*step⁻¹] in areas with a maximum LSR). Also, the covered distances per individual varied among three groups, from 2.97 m in the control to 1.11 m in areas with medium LSR to 0.88 m in areas with maximum LSR. Thus, in areas with LSR, animals were forced by their habitats to perform shorter move steps on average and covered less distance. The distance covered (i.e., dispersal performances) were not correlated with such factors as sex, weight and length of the Tenebrio individuals from other studies. Analysis of the data for net squared displacement indicated that the dispersal of the beetles did not follow a diffusion process. The move step directions of the dispersal data showed pronounced autocorrelation, which means that in contrast to other findings, the individuals were not performing a random walk. This effect was strongly dependent on the temporal resolution (i.e. grain), and was also influenced by the experimental conditions. The entire array of data showed high variability among the sub-groups (as well as many outliers), revealing nonparametric characteristics. The results showed that the specific physical configuration of suitable habitat for Tenebrio is one of the key indicators of landscape connectivity on the micro-scale.     

Centers and angles of rotation of body joints: A study of errors and optimization

Large variations are generally reported in the locations of centers of rotation (CR) for each of various joints in the human body. Some of these reports present conflicting results. This paper shows that this may be due in part to suboptimal experimental design as well as the phenomenon of error magnification. An algorithm is presented for computing the coordinates of the CR and the angle of rotation from the x, y coordinate measurements of two point markers on a moving body in two different positions. Error analysis is performed using a mathematical model that introduces systematically a positive or a negative error into each of the 8 x, y coordinates in all possible combinations, resulting in 256 CR locations. CR error zones are computed and graphed. Parametric analysis of the experimental set-up leads to optimization of the set-up. A typical case is analyzed and its errors computed. It is shown that small errors present in the measurements of the x, y coordinates of the markers are magnified to relatively large errors in the CR coordinates. In a suboptimal case, this magnification may be 30–50 times or more. The results show that, besides the magnitude of x, y coordinate errors, other factors responsible for determining the magnitude of errors in the location of the CR are: the magnitude of angle of rotation, the orientation of the markers with respect to the CR and their distances from the CR. In conjunction with the CR, the angle of rotation is also analyzed. Guidelines for optimal experimental set-up for minimizing the output errors are presented.     

Dual-Force ISOMAP: A New Relevance Feedback Method for Medical Image Retrieval

With great potential for assisting radiological image interpretation and decision making, content-based image retrieval in the medical domain has become a hot topic in recent years. Many methods to enhance the performance of content-based medical image retrieval have been proposed, among which the relevance feedback (RF) scheme is one of the most promising. Given user feedback information, RF algorithms interactively learn a user’s preferences to bridge the “semantic gap” between low-level computerized visual features and high-level human semantic perception and thus improve retrieval performance. However, most existing RF algorithms perform in the original high-dimensional feature space and ignore the manifold structure of the low-level visual features of images. In this paper, we propose a new method, termed dual-force ISOMAP (DFISOMAP), for content-based medical image retrieval. Under the assumption that medical images lie on a low-dimensional manifold embedded in a high-dimensional ambient space, DFISOMAP operates in the following three stages. First, the geometric structure of positive examples in the learned low-dimensional embedding is preserved according to the isometric feature mapping (ISOMAP) criterion. To precisely model the geometric structure, a reconstruction error constraint is also added. Second, the average distance between positive and negative examples is maximized to separate them; this margin maximization acts as a force that pushes negative examples far away from positive examples. Finally, the similarity propagation technique is utilized to provide negative examples with another force that will pull them back into the negative sample set. We evaluate the proposed method on a subset of the IRMA medical image dataset with a RF-based medical image retrieval framework. Experimental results show that DFISOMAP outperforms popular approaches for content-based medical image retrieval in terms of accuracy and stability.     

西南地区红花龙胆分布格局模拟与气候变化影响评价

应用最大熵(MaxEnt)模型,基于230条分布记录及33个气候因子数据,模拟全新世中期(约6000年前)、当前时期(1950—2000年)和未来(2050s、2070s)气候条件下,红花龙胆西南地区的潜在分布范围;结合多元统计分析和ArcGIS空间分析,筛选影响物种分布的关键气候因子,探讨不同分布区对气候变化的敏感性.结果表明: 模型训练集AUC值为0.942,验证集AUC值为0.849,表明模型预测的准确性较高.5个气候因子(7月最高气温、8月最低气温、昼夜温差与年温差比值、7月最低气温和6月最低气温)对模型贡献最大,累计贡献率达59.9%.随未来气候变化,红花龙胆适生区将呈现先减少后增加的变化趋势,在RCP 8.5情景下,至2070s阶段,西南地区红花龙胆适宜生境总面积与当前气候条件相比减少15.0%,但云南境内适生区和高适生区面积较当前分别增加32.8%和32.7%.红花龙胆适宜生长于温暖、湿润的气候条件下,气候变暖明显影响着适宜生境的面积和范围,尤其低海拔分布区对气候变化较敏感,适宜生境退缩严重,而高海拔地区由于降水、温度条件的改善适宜生境有所增加.随着全球气候的变化,未来西南地区红花龙胆主要分布区可能向西迁移,并向更高海拔扩张.     

Modeling of batch fermentation kinetics for succinic acid production by Mannheimia succiniciproducens

Kinetic models are proposed for the batch production of succinic acid from glucose by Mannheimia succiniciproducens MBEL55E. The models include terms accounting for both substrate and product inhibitions. Experimental data collected from a series of batch fermentations with different initial glucose concentrations were used to estimate parameters and also to validate the models proposed. The optimal values of the parameters were approximated by minimizing the discrepancy between the model predictions and corresponding experimental data. The growth of M. succiniciproducens could be expressed by a modified Monod model incorporating inhibitions of glucose and organic acids accumulated in the culture broth. The Luedeking–Piret model was able to describe the formation of organic acids as the fermentation proceeded, in which succinic, acetic, and formic acids followed a mixed-growth-associated pattern. However, unexpectedly, lactic acid fermentation by M. succiniciproducens was nearly nongrowth-associated. In all cases, the model simulation matched well with the experimental observations, which made it possible to elucidate the fermentation characteristics of M. succiniciproducens during efficient succinic acid production from glucose. These models thus can be employed for the development and optimization of biobased succinic acid production processes.