Statistical methods for estimating doubling time in in vitro cell growth

Summary Doubling time has been widely used to represent the growth pattern of cells. A traditional method for finding the doubling time is to apply gray-scaled cells, where the logarithmic transformed scale is used. As an alternative statistical method, the log-linear model was recently proposed, for which actual cell numbers are used instead of the transformed gray-scaled cells. In this paper, I extend the log-linear model and propose the extended log-linear model. This model is designed for extra-Poisson variation, where the log-linear model produces the less appropriate estimate of the doubling time. Moreover, I compare statistical properties of the gray-scaled method, the log-linear model, and the extended log-linear model. For this purpose, I perform a Monte Carlo simulation study with three data-generating models: the additive error model, the multiplicative error model, and the overdispersed Poisson model. From the simulation study, I found that the gray-scaled method highly depends on the normality assumption of the gray-scaled cells; hence, this method is appropriate when the error model is multiplicative with the log-normally distributed errors. However, it is less efficient for other types of error distributions, especially when the error model is additive or the errors follow the Poisson distribution. The estimated standard error for the doubling time is not accurate in this case. The log-linear model was found to be efficient when the errors follow the Poisson distribution or nearly Poisson distribution. The efficiency of the log-linear model was decreased accordingly as the overdispersion increased, compared to the extended log-linear model. When the error model is additive or multiplicative with Gamma-distributed errors, the log-linear model is more efficient than the gray-scaled method. The extended log-linear model performs well overall for all three data-generating models. The loss of efficiency of the extended log-linear model is observed only when the error model is multiplicative with log-normally distributed errors, where the gray-scaled method is appropriate. However, the extended log-linear model is more efficient than the log-linear model in this case.     

Reliability Analysis of the Groundwater Conceptual Model

The hydrologic model is the foundation of water resource management and planning. Conceptual model is the essential component of groundwater model. Due to limited understanding of natural hydrogeological conditions, the conceptual model is always constructed incompletely. Therefore, the uncertainty in the model's output is evitable when natural groundwater field is simulated by a single groundwater model. A synthetic groundwater model is built and regarded as the true model, and three alternative conceptual models are constructed by considering incomplete hydrogeological conditions. The outputs (groundwater budget terms from boundary conditions) of these groundwater models are analyzed statistically. The results show that when the conceptual model is closer to the true hydrogeological conditions, the distributions of outputs of the groundwater model are more concentrated on the true outputs. Therefore, the more reliable the structure of the conceptual model is, the more reliable the output of the groundwater model is. Moreover, the uncertainty caused by the conceptual model cannot be compensated by parameter uncertainty.     

Interactions of small nonpolar molecules with biological membranes: an exactly solvable model

An exactly solvable model of the interaction of small nonpolar molecules with biological membranes is developed. This model, which is based upon a “decorated dimer model” extension of Nagle's membrane model, is demonstrated to qualitatively reproduce many of the changes in the order-disorder phase transition seen when biological membranes are exposed to anesthetic gases. The decorated dimer model is itself interesting because it provides an example of an exactly solvable monomer-dimer model in which phase transitions can occur in the presence of monomers.     

Patient-derived orthotopic xenograft (PDOX) mouse model of adult rhabdomyosarcoma invades and recurs after resection in contrast to the subcutaneous ectopic model

Rhabdomyosarcoma (RMS) is a rare mesenchymal tumor. The aim of the present study was to develop a patient-derived orthotopic xenograft (PDOX) mouse model of RMS and compare the PDOX model to a subcutaneous (s.c.)-transplant model. A patient RMS from a striated muscle was grown orthotopically in the right biceps femoris muscle and right quadriceps muscle of nude mice to establish a PDOX model, as well as under the skin to establish an s.c. model. PDOX tumors grew at a statistically-significant faster rate compared to the s.c. tumors. Recurrence after surgical resection occurred only in PDOX tumors, not in the s.c. model. Histologically, only the PDOX model was shown to be invasive. In conclusion, these results indicate that the PDOX model of adult RMS is malignant and the subcutaneous model is benign. These results emphasize that a proper tumor microenvironment is necessary for patient-like behavior of a tumor in a mouse model.     

从临床到基础：硝酸甘油实验性偏头痛大鼠模型信度和效度评价

具有良好信度和效度的动物模型是从实验室到临床转译研究成功的保证,为进一步应用硝酸甘油（glycerol trinitrate,GTN）偏头痛大鼠模型,对其信度和效度进行评价。效度包括表面效度、建构效度、标准关联效度。衡量表面效度的标准是症状同源性。GTN偏头痛大鼠模型行为学表现与人类偏头痛有一定的相似性。建构效度主要指动物模型对理论假说的解释度,GTN模型复制了偏头痛的神经源性炎症及痛觉增敏,具有较好的建构效度。标准关联效度即预测效度主要表现为药理学反应及其在临床的干预实验。GTN模型对典型抗偏头痛药物麦角胺的反应较敏感,但是该模型的预测力效度仍未有效建立。GTN偏头痛大鼠在不同的地区、不同的实验室均已成功复制,表明其有较好的信度。     

Escherichia coil growth dynamics: A three-pool biochemically based description

A three-pool growth model of an individual Escherichia coli cell is described herein. The model is based on a previously developed chemically structured complex single cell growth model. The reduction in model complexity and the identification of the essential modes of motion, over the time scale of growth, is achieved by temporal decomposition and analysis of hierarchy in relaxation times. The three-pool model faithfully simulates the changes in cell size, cell shape, cell macromolecular composition, DNA initiation and termination periods, and the dependence of cell growth under abiotic glucose limitation. The predictions made by the reduced model compare favorably with both the experimental data and those of the full single cell model (SCM) without any parameter adjustments. The three-pool model has very few significant parameters and has the potential to find immediate practical use in bioreactor design and process control strategies. The model development illustrates the use of modal analysis to yield reduced physiologically realistic dynamic model of complex microbial system such as E. coll.     

Modelling Holling type II functional response in deterministic and stochastic food chain models with mass conservation

The Rosenzweig-MacArthur predator-prey model is the building block in modeling food chain, food webs and ecosystems. There are a number of hidden assumptions involved in the derivation. For instance the prey population growth is logistic without predation but also with predation. In order to reveal these we will start with modelling a resource-predator-prey system in a closed spatially homogeneous environment. This allows us to keep track of the nutrient flow. With an instantaneous remineralisation of the products excreted in the environment by the populations and dead body mass there is conservation of mass. This allows for a model dimension reduction and yields the mass balance predator-prey model. When furthermore the searching and handling processes are much faster that the population changing rates, the trophic interaction is described by a Holling type II functional response, also assumed in the Rosenzweig-MacArthur model. The derivation uses an extended deterministic model with number of searching and handling predators as model variables where the ratio of the predator/prey body masses is used as a mechanistic time-scale parameter. This extended model is also used as a starting point for the derivation of a stochastic model. We will investigate the stochastic effects of random switching between searching and handling of the predators and predator dying. Prey growth by consumption of ambient resources is still deterministic and therefore the stochastic model is hybrid. The transient dynamics is studied by numerical Monte Carlo simulations and also the quasi-equilibrium distribution for the population quantities is calculated. The body mass of the prey individual is the scaling parameter in the stochastic model formulation. This allows for a quantification of the mean-field approximation criterion for the justification of replacement of the stochastic by a deterministic model.     

Haplotype reconstruction from SNP fragments by minimum error correction

MOTIVATION: Haplotype reconstruction based on aligned single nucleotide polymorphism (SNP) fragments is to infer a pair of haplotypes from localized polymorphism data gathered through short genome fragment assembly. An important computational model of this problem is the minimum error correction (MEC) model, which has been mentioned in several literatures. The model retrieves a pair of haplotypes by correcting minimum number of SNPs in given genome fragments coming from an individual's DNA. RESULTS: In the first part of this paper, an exact algorithm for the MEC model is presented. Owing to the NP-hardness of the MEC model, we also design a genetic algorithm (GA). The designed GA is intended to solve large size problems and has very good performance. The strength and weakness of the MEC model are shown using experimental results on real data and simulation data. In the second part of this paper, to improve the MEC model for haplotype reconstruction, a new computational model is proposed, which simultaneously employs genotype information of an individual in the process of SNP correction, and is called MEC with genotype information (shortly, MEC/GI). Computational results on extensive datasets show that the new model has much higher accuracy in haplotype reconstruction than the pure MEC model.     

Some interrelationships among the regression coefficient estimates arising in a class of models appropriate to response-time data.

Interrelationships among three response-time models which incorporate covariate information are explored. The most general of these models is the logistic-exponential in which the log odds of the probability of responding in a fixed interval is assumed to be a linear function of the covariates; this model includes a parameter W for the width of discrete time intervals in which responses occur. As W leads to O this model is equivalent to a continuous time exponential model in which the log hazard is linear in the covariates. As W leads to infininity it is equivalent to a continuous time exponential model in which the hazard itself is a linear function of the covariates. This second model was fitted to the data used in an earlier publication describing the logistic exponential model, and very close agreement of the estimates of the regression coefficients is demonstrated.     

The Effect of Carrier Distribution on Performance of ENZ-Based Electro-Absorption Modulator

Recently, epsilon-near-zero (ENZ) has been emerging as an important field of research which is the study of light-matter interactions in the presence of materials with zero permittivity. Since in many scientific works the uniform model of carrier distribution of Indium tin oxide (ITO) has been utilized, we want to investigate ENZ effect in ITO material and the effect of accurate carrier distribution on the performance of a modulator. For this reason, an electro-absorption (EA) modulators with a new configuration based on silicon slot modulator with indium thin oxide material is proposed. To study the effect of ENZ effect in ITO, the semiconductor model (realistic model) is utilized to model the carrier distribution in the ITO material. In this model, there is not any assumption. As a result, by applying the gate voltage, the insertion loss is increased 1.61 dB/μm in comparison with unbiased conditions. Also, the uniform model is used. Compared with the realistic model, the extinction ratio and figure-of-merit significantly enhance based on the uniform model, but the trends of results like insertion loss are so far from the realistic model. It can be found that the realistic model is reliable and the results are closer to reality.

     

田间作物蒸腾量测算方法研究

本文依据Penman-Monteith方法对田间蒸腾量的测算进行了探讨,从理论上分析并导出蒸腾量的估算模式,对参数的估算也做了详细分析和讨论。最后用大屯农业生态系统试验站的观测资料对模式进行验证,结果表明,采用本模式计算田间蒸腾量效果很好。     

A modified mathematical model of the anatomy of the cardiac left ventricle

A modification of the mathematical model of the shape and fiber direction field of the left cardiac ventricle is presented. The model was developed based on the idea of nested spiral surfaces. The ventricle is composed of surfaces that model myocardial layers. Each layer is filled with curves corresponding to myocardial fibers. The tangents to these curves form the myofiber direction field. A modified spherical coordinate system is linked with the model left ventricle, where the ventricular boundaries are coordinate surfaces. The model is based on echocardiographic, computed-tomography, or magnetic-resonance-imaging data. For this purpose, four-chamber and two-chamber echocardiography views or sections along the long axis of the left ventricle from these tomographic data in several positions are approximated with a model profile. To construct a 3D model, we then interpolate model parameters by periodic cubic splines and the vector field of the tangents to the model fibers is calculated. For verification of the model, we used diffusion-tensor magneticresonance-imaging data of the human heart.     

Noninteracting local-structure model of folding and unfolding transition in globular proteins. II. Application to two-dimensional lattice proteins

The noninteracting local-structure model of the folding and unfolding transition in globular proteins, the formulation of which was given in the preceding paper, is applied to the analysis of the two-dimensional lattice model of proteins. The lattice model of proteins is a theoretical tool designed to study the statistical-mechanical aspect of the folding and unfolding transition. Its dynamics have been studied by a method of Monte Carlo simulation. The noninteracting local-structure model reproduces the equilibrium properties of the lattice model obtained previously by computer simulation remarkably well, when the specificity of the long-range interactions is strong. This observation indicates that the basic assumption of the noninteracting local-structure model is equivalent to the assumption of strong specificity of intramolecular interactions. It is argued that by assuming this strong specificity, we can emphasize the correct main paths of folding and unfolding transition. The way local structures grow and/or merge along the most probable path of folding in the lattice model is discussed by the noninteracting local-structure model.     

Towards the development of a minimal cell model by generalization of a model of Escherichia coli: use of dimensionless rate parameters.

A model of a minimal cell would be a valuable tool in identifying the organizing principles that relate the static sequence information of the genome to the dynamic functioning of the living cell. Our approach for developing a minimal cell model is to first generalize an existing model of Escherichia coli by expressing reaction rates as ratios to a set of reference parameters. This generalized model is a prototype minimal cell model that will be developed by adding detail to explicitly include each chemical species. We tested the concept of a generalized model by testing the effect of scaling all enzyme-catalyzed reactions in the E. coli model. The scaling has little effect on cellular function for a wide range of kinetic ratios, where the kinetic ratio is defined as the rate of all enzyme-catalyzed reactions in a given model relative to those in the E. coli model.     

枯落物分解研究方法和模型讨论

由于研究目的、尺度范围和要求精度的不同,枯落物分解的研究方法各异：野外分解袋法是最直接和最准确的方法,但是耗时太长;室内分解培养法与野外分解袋法相似,但具有灵活设计试验方案的优越性;现量估算法方法简捷,但是只对进入稳定发展和动态平衡阶段的生态系统可以获得较好的精度;综合平衡法能反映整个生长历史时期的枯落物分解速率平均水平,但其准确性取决于对历年凋落物量预测的精度。在枯落物分解模型中,分解率概算模型只适合于林地枯落物积累达到动态平衡时的情况,所以作者提出了另外的枯落物动态平衡模型予以修正;时间衰减模型以Olson指数模型为典型代表,但由于在应用过程中存在一些问题,也提出了相应的修正办法;影响因子关系模型包括基质质量因子关系模型、非生物环境因子关系模型和生物因子关系模型等类型。作者提出构建过程模型将是未来枯落物分解模型研究的方向。     

A Stochastic Model of Oscillatory Blood Testosterone Levels

A continuous-time, discrete-state stochastic model of testosterone secretion in men is considered. Blood levels of testosterone in men fluctuate periodically with a period of 2–3 h. The deterministic model, on which the stochastic model considered here is based, is well studied and has been shown to have a globally stable fixed point. Thus, no sustained oscillations are possible in the deterministic case. However, the stochastic model does observe periodic, pulsatile behavior. This demonstrates how oscillations can occur due to a switching behavior dependent on the random degradation of testosterone molecules in the system. The Gillespie algorithm is used to simulate the hormone secretion model. Important parameters of the model are discussed and results from the model are compared to experimental observations.     

Age-dependent predation is not a simple process. II. Wolves,ungulates, and a discrete time model for predation on juveniles with a stabilizing tail

A discrete time model for a predator-prey model, where the predator eats only juvenile prey is developed. The model is developed to capture some of the behavior of wolf-ungulate systems. Age-dependent predation is shown to be a stabilizing influence. The behavior of the model depends critically on the age of senescence of the prey—an extremely small number of old prey individuals represent a very powerful stabilizing factor. The model behaves in a similar fashion to, but is less stable than, an age structured Ricker model.     

Parameterization of Multivariate Random Effects Models for Categorical Data

Alternative parameterizations and problems of identification and estimation of multivariate random effects models for categorical responses are investigated. The issues are illustrated in the context of the multivariate binomial logit-normal (BLN) model introduced by Coull and Agresti (2000, Biometrics 56, 73-80). We demonstrate that the BLN model is poorly identified unless proper restrictions are imposed on the parameters. Moreover, estimation of BLN models is unduly computationally complex. In the first application considered by Coull and Agresti, an identification problem results in highly unstable, highly correlated parameter estimates and large standard errors. A probit-normal version of the specified BLN model is demonstrated to be underidentified, whereas the BLN model is empirically underidentified. Identification can be achieved by constraining one of the parameters. We show that a one-factor probit model is equivalent to the probit version of the specified BLN model and that a one-factor logit model is empirically equivalent to the BLN model. Estimation is greatly simplified by using a factor model.     

Multiscale Stochastic Reaction–Diffusion Modeling: Application to Actin Dynamics in Filopodia

Two multiscale (hybrid) stochastic reaction–diffusion models of actin dynamics in a filopodium are investigated. Both hybrid algorithms combine compartment-based and molecular-based stochastic reaction–diffusion models. The first hybrid model is based on the models previously developed in the literature. The second hybrid model is based on the application of a recently developed two-regime method (TRM) to a fully molecular-based model, which is also developed in this paper. The results of hybrid models are compared with the results of the molecular-based model. It is shown that both approaches give comparable results, although the TRM model better agrees quantitatively with the molecular-based model.