水稻花粉扩散的模拟研究

水稻花粉扩散可导致基因飘流问题,尤其是转基因水稻,其外源基因的扩散可能会引发一系列的环境安全问题。为了模拟花粉扩散过程,2007年和2009年分别在南京(32°01′N,118°52′E)和溧水(31°35′N,119°11′E),以两优培九为材料,各组织了一次田间试验。通过空气中的花粉扩散浓度的观测和微气象塔梯度环境要素的采集,采用高斯烟羽模型为基础,利用最小二乘法,模拟了水稻花粉的扩散浓度,并利用独立试验数据验证了模型效果。结果表明:花粉释放集中在始花期后第1天到第5天的09:00-11:00,且花粉释放量与开花量显著相关(r=0.880**)。花粉浓度的模拟值和实测值变化趋势一致,其均方根误差和相对误差分别为0.509粒/(m2.d)和3.47%。该花粉扩散模型可以正确反映花粉扩散浓度的分布特征。但在花粉浓度的预测精度上,尤其是预测花粉远距离传播时,仍需要改进。     

A model for self-recognition and regulation of the incompatibility response of pollen

Summary Recent biochemical studies with Brassica indicate that the pollen grain has a primary role in the control of self incompatibility. Combining this new evidence with that from prior genetic, biochemical, and ultrastructural studies, a working model is hypothesized for the molecular events which occur during self recognition and the subsequent control of pollen germination. Self recognition is postulated to involve the interaction of a presynthesized, genotype-specific recognition molecule (effector) produced by the stigma with a presynthesized receptor molecule produced by and located in or on the pollen grain. The consequence of self recognition is a selective inhibition of pollen protein synthesis within about 2–4 minutes after imbibition. We deduced that protein synthesis is programmed to occur in pollen — unless interrupted as a consequence of self-recognition — and leads to the sequential production of opposing regulators: first a germination inhibitor (G-Inh), then a germination activator (G-Act). These regulators in turn control the activities of presynthesized, and probably sequestered enzymes required for germ tube formation. Sequential appearances of the G-Inh and G-Act occur unless synthesis of the G-Act is blocked as a result of self recognition. Thus, following a self pollination, recognition occurs in sufficient time to block production of the G-Act but not of the G-Inh, and inhibition of germination (incompatibility) results. For a cross pollination, there is no self recognition and production of the G-Act is unimpeded; it then nullifies the effect of the G-Inh and pollen germination (compatibility) results. The model and evidence for its support are discussed in detail.Department of Vegetable Crops Paper No. 719     

A polynomial based model for cell fate prediction in human diseases

Background

Cell fate regulation directly affects tissue homeostasis and human health. Research on cell fate decision sheds light on key regulators, facilitates understanding the mechanisms, and suggests novel strategies to treat human diseases that are related to abnormal cell development.

Results

In this study, we proposed a polynomial based model to predict cell fate. This model was derived from Taylor series. As a case study, gene expression data of pancreatic cells were adopted to test and verify the model. As numerous features (genes) are available, we employed two kinds of feature selection methods, i.e. correlation based and apoptosis pathway based. Then polynomials of different degrees were used to refine the cell fate prediction function. 10-fold cross-validation was carried out to evaluate the performance of our model. In addition, we analyzed the stability of the resultant cell fate prediction model by evaluating the ranges of the parameters, as well as assessing the variances of the predicted values at randomly selected points. Results show that, within both the two considered gene selection methods, the prediction accuracies of polynomials of different degrees show little differences. Interestingly, the linear polynomial (degree 1 polynomial) is more stable than others. When comparing the linear polynomials based on the two gene selection methods, it shows that although the accuracy of the linear polynomial that uses correlation analysis outcomes is a little higher (achieves 86.62%), the one within genes of the apoptosis pathway is much more stable.

Conclusions

Considering both the prediction accuracy and the stability of polynomial models of different degrees, the linear model is a preferred choice for cell fate prediction with gene expression data of pancreatic cells. The presented cell fate prediction model can be extended to other cells, which may be important for basic research as well as clinical study of cell development related diseases.

     

A model for the mechanism of tip extension in pollen tubes

Three main mechanisms are proposed to account for the tip growth of pollen tubes. (1) The tip region is supported against the internal osmotic pressure of the cell by a fibrillar network, composed mainly of microfilaments, that is stabilized by calcium ions. Tip extension is promoted by a lowering of the local cytoplasmic calcium ion concentration, through uptake by the mitochondria and/or endoplasmic reticulum, which leads to a weakening of the fibrillar network. (2) Vesicles, derived from dictyosomes in the main body of the tube, fuse with the apical plasma membrane, providing new membrane and further carbohydrate for the wall. The rate of fusion is proportional to the rate of diffusion of calcium ion across the plasma membrane at the tip. (3) The callose lining present in the pollen tube wall, except at the tip, renders the wall impermeable and restricts entry of calcium ions to the apical plasma membrane. This restriction limits the rate of vesicle fusion, and tube growth, to the tip.This model is discussed in the light of previous observations on the growth and structure of pollen tubes under normal and experimental conditions.     

A diffusion model for the fate of tandem gene duplicates in diploids

Suppose one chromosome in one member of a population somehow acquires a duplicate copy of the gene, fully linked to the original gene's locus. Preservation is the event that eventually every chromosome in the population is a descendant of the one which initially carried the duplicate. For a haploid population in which the absence of all copies of the gene is lethal, the probability of preservation has recently been estimated via a diffusion approximation. That approximation is shown to carry over to the case of diploids and arbitrary strong selection against the absence of the gene. The techniques used lead to some new results. In the large population limit, it is shown that the relative probability that descendants of a small number of individuals carrying multiple copies of the gene fix in the population is proportional to the number of copies carried. The probability of preservation is approximated when chromosomes carrying two copies of the gene are subject to additional, fully non-functionalizing mutations, thereby modelling either an additional cost of replicating a longer genome, or a partial duplication of the gene. In the latter case the preservation probability depends only on the mutation rate to null for the duplicated portion of the gene.     

A mathematical model for mugwort (Artemisia vulgaris L.) pollen forecasts

Pollen forecasts are a fundamental prerequisite to obtain prophylactic measures for allergic individuals. Mugwort belongs to the most relevant allergenic pollen types after grasses and birch. An approach to modeling of mugwort pollen concentrations has not been attempted previously in Germany. A process-oriented mathematical model for the relative local daily average mugwort airborne pollen concentration was developed on the basis of pollen and weather data measured during a 6-year period. The model depends on the daily minimum and maximum temperature, amount of precipitation and atmospheric pressure, which have to and can be supplied by measurement and prediction. The comparison of modeling results and pollen counting for an additional year confirms the fitness of the model. A computer program was written, which rests upon the model and supplies daily predictions of mugwort pollen flight during the period of the weather forecast. The latter should allow a pollen forecasting period of about 5 days, with an accuracy of about 32–63% explained variance, which in view of the low mugwort pollen counts (nine grains/m³ maximum in the validation year) represents a high relative measurement error. The mathematical model may serve to improve and rationalize of present pollen forecasts.     

A simulation model for the fate of pesticide residues in a field soil

The model employed for simulating the fate of pesticides in soil was based on the one dimensional convective-dispersive-reaction equation. The model assumed a constant pore-water velocity (v), linear equilibrium adsorption, and first-order degradation. The adsorption parameter (k_d) was calculated from molecular structure with the help of a first-order molecular connectivity index. On the basis of the results of sensitivity analysis the model was made partially stochastic in order to account for horizontal heterogenity in a field soil. Concentration profiles were obtained by employing the mode, median and mean values of (v, D) while the values of k_d and t_1/2 were kept constants; where D and t_1/2 were the apparent diffusion coefficient and the degradation half-life, respectively. The resulted extremes in concentration profiles were expected to be observed within a relatively small area of the heterogeneous filed soil. A random variable, namely the contaminated depth, was defined so that the soil beneath it would be practically free of pesticide during its entire life-time. The values of (₁, ₂, ₃) under continuous leaching were (0.14, 0.56, 1.00 m), (0.29, 1.50, 2.62 m), and (0.65, 2.25, 4.00m) for DDT, toxaphene and lindane, respectively; where ₁, ₂ and ₃ were values of calculated by employing the mode, median, and mean values of (v, D), respectively. Within a relatively small area the first value would be frequently observed whereas the others would be less pronounced. The depth and shape of the resultant base of the contaminated zone were substantially more sensitive to changes in the surface rates of recharge than to changes in the values of the chemical parameters k_d and t_1/2. The implication of the results for the assesment of pesticide contamination of groundwaters were discussed.     

A model of sequential branching in hierarchical cell fate determination

Multipotent stem or progenitor cells undergo a sequential series of binary fate decisions, which ultimately generate the diversity of differentiated cells. Efforts to understand cell fate control have focused on simple gene regulatory circuits that predict the presence of multiple stable states, bifurcations and switch-like transitions. However, existing gene network models do not explain more complex properties of cell fate dynamics such as the hierarchical branching of developmental paths. Here, we construct a generic minimal model of the genetic regulatory network controlling cell fate determination, which exhibits five elementary characteristics of cell differentiation: stability, directionality, branching, exclusivity, and promiscuous expression. We argue that a modular architecture comprising repeated network elements reproduces these features of differentiation by sequentially repressing selected modules and hence restricting the dynamics to lower dimensional subspaces of the high-dimensional state space. We implement our model both with ordinary differential equations (ODEs), to explore the role of bifurcations in producing the one-way character of differentiation, and with stochastic differential equations (SDEs), to demonstrate the effect of noise on the system. We further argue that binary cell fate decisions are prevalent in cell differentiation due to general features of the underlying dynamical system. This minimal model makes testable predictions about the structural basis for directional, discrete and diversifying cell phenotype development and thus can guide the evaluation of real gene regulatory networks that govern differentiation.     

Establishment and characterization of a novel murine model for pollen allergy

Although there have been many studies revealing the mechanism and establishing the therapeutical method for allergic rhinitis, no suitable animal models for allergic rhinitis, especially for pollen allergy, are currently available. We therefore aimed in this study to develop a murine model producing IgE in response to an inhaled antigen without using any adjuvants. Ovalbumin (OVA)-specific T cell receptor transgenic mice (DO11.10) inhaled an OVA solution for one h, twice a week, for six weeks. The resulting increase of OVA-specific IgE in the serum was observed depending on the times of inhalation. Spleen cells from mice that had inhaled the antigen produced more IL-4 and less IFN-γ than those from the control mice in vitro. These results indicate that inhaled antigen enhanced the Th2-type responses and induced IgE production in a T cell-mediated manner. Our findings would contribute to studies on prevention and treatment of pollen allergy.     

A 30-day-ahead forecast model for grass pollen in north London, United Kingdom

A 30-day-ahead forecast method has been developed for grass pollen in north London. The total period of the grass pollen season is covered by eight multiple regression models, each covering a 10-day period running consecutively from 21 May to 8 August. This means that three models were used for each 30-day forecast. The forecast models were produced using grass pollen and environmental data from 1961 to 1999 and tested on data from 2000 and 2002. Model accuracy was judged in two ways: the number of times the forecast model was able to successfully predict the severity (relative to the 1961–1999 dataset as a whole) of grass pollen counts in each of the eight forecast periods on a scale of 1 to 4; the number of times the forecast model was able to predict whether grass pollen counts were higher or lower than the mean. The models achieved 62.5% accuracy in both assessment years when predicting the relative severity of grass pollen counts on a scale of 1 to 4, which equates to six of the eight 10-day periods being forecast correctly. The models attained 87.5% and 100% accuracy in 2000 and 2002, respectively, when predicting whether grass pollen counts would be higher or lower than the mean. Attempting to predict pollen counts during distinct 10-day periods throughout the grass pollen season is a novel approach. The models also employed original methodology in the use of winter averages of the North Atlantic Oscillation to forecast 10-day means of allergenic pollen counts.     

Mental lexicon and derivational rules

Lexical decision task in an event-related potential experiment was used in order to determine the organization of mental lexicon regarding the polimorphemic words: are they stored as unanalyzable items or as separate morphemes? The results indicate the later: while monomorphemic words elicit N400 component, usually related to lexical-semantic processing, prefixed words and prefixed pseudo-words elicit left anterior negativity (LAN), usually related to grammatical (morphosyntactic) processes. These components indicate that the speakers apply grammatical (i.e., word-formation) rules and combine morphemes in order to obtain lexical meaning of the prefixed word.     

A model for coding pollen size in reference to phylogeny using examples from the Ebenaceae

Most genetically based features should be available for use in cladistic analysis. Palynologists routinely measure polar (P) and equatorial (E) axes and place pollen into size classes defined by earlier pollen workers. Grouping of pollen into globally arbitrary classes may not correspond to statistically significant differences among the taxa of a study. We propose a model using conventional statistical procedures coupled with data visualization and Monte Carlo simulation. This approach is not a final solution to the general problem of coding continuous characters into discrete states; it is an attempt to address the problems of character state delimitation in pollen morphology. We suggest that the coding of continuous measurement variables (e.g., P, E) into character states should be done following a logical sequence of interactive visualization (2D and 3D) of bivariate frequency distributions including the inspection of prediction and confidence ellipses (e.g., 99%), and use of ANOVA. We illustrate our approach using realistic pollen data sets generated by a computer program (POLSIM) written to perform Monte Carlo sampling from normally distributed statistical populations of polar and equatorial axes. Our model is then applied to an original data set of 4,134 pollen grains from the Ebenaceae, resulting in the coding of the four genera into three character states for pollen size.     

A model of plasma membrane flow and cytosis regulation in growing pollen tubes

A model of cytosis regulation in growing pollen tubes is developed and simulations presented. The authors address the question on the minimal assumptions needed to describe the pattern of exocytosis and endocytosis reported recently by experimental biologists. Biological implications of the model are also treated. Concepts of flow and conservation of membrane material are used to pose an equation system, which describes the movement of plasma membrane in the tip of growing pollen tubes. After obtaining the central equations, relations describing the rates of endocytosis and exocytosis are proposed. Two cytosis receptors (for exocytosis and endocytosis), which have different recycling rates and activation times, suffice to describe a stable growing tube. Simulations show a very good spatial separation between endocytosis and exocytosis, in which separation is shown to depend strongly on exocytic vesicle delivery. In accordance to measurements, most vesicles in the clear zone are predicted to be endocytic. Membrane flow is essential to maintain cell polarity, and bi-directional flow seems to be a natural consequence of the proposed mechanism. For the first time, a model addressing plasma membrane flow and cytosis regulation were posed. Therefore, it represents a missing piece in an integrative model of pollen tube growth, in which cell wall mechanics, hydrodynamic fluxes and regulation mechanisms are combined.