Two-stage models for the analysis of cancer screening data

Methods are proposed for the analysis of the natural history of disease from screening data when it cannot be assumed that untreated preclinical disease always progresses to clinical disease. The methodology is based on a two-stage model for preclinical disease in which stage 1 lesions may or may not progress to stage 2, but all stage 2 lesions progress to clinical disease. The focus is on joint estimation of the total preclinical duration and the sensitivity of the screening test. A partial likelihood is proposed for the analysis of prospectively collected screening data, and an analogous conditional likelihood is proposed for retrospective data. Some special cases for the joint sojourn distribution of the two stages are considered, including the independent model and limiting models where the duration of stage 2 is short relative to stage 1. The methods are applied to a case-control study of cervical cancer screening in Northeast Scotland.     

The duration of copepod life stages estimated from stage-frequency data

Current methods to determine the stage duration of copepodsfrom stage-frequency dataare often based on inappropriate distributionfunctions of the stage development time; they also lack a clearprobability model that describes the random noise in the data.This study aims to estimate the duration of copepod life stages,using an asymmetrical probability distribution function of developmenttime. Data on stage frequency were collected from cultured cohortsof Acartia clausi, Temora longicornis and Pseudocalanus elongatus.In addition, data from cultures of Calanoides carinatus andCalanus australis by Peterson and Painting (J. Plankton Res.,12, 283–293, 1990) were used. Following Landry(Limnol.Oceanogr., 20, 854–858, 1975), for each stage the numberof animals that did not yet pass that stage was plotted as afunction of time. A gamma distribution function appeared todescribe the expected proportion of these animals versus time.The number of animals is assumed to follow a binomial distributionand the model parameters are estimated by maximizing the likelihood.This method enables individuals with a retarded development,which are usually deleted from the data material, to be dealtwith. The median development time was estimated from the gammadistribution functions, from which the duration of the stageswas derived. Isochronal development was confirmed for most stages.However, the first feeding naupliar stage, as well as the lastcopepodite stage (CV), took longer in most species, whereasthe pre-feeding naupliar stages had a shorter duration, particularlyin P.elongatus. Differences betweensexes were not apparent.Contradicting results among cultures and with published resultsbyother workers suggest that part of the observed deviation fromnear-isochronal development may be due to the culture conditions.     

The estimation of recruitment from stage frequency data

Summary A general relationship is derived for the area of the sample curve for a given stage in the life-cycle, in terms of the mean survival rate and duration and the number entering the stage. The influence of recruitment, development and mortality patterns on the area of the sample curve is investigated. The results indicate a simple method of analysing stage frequency data to produce a best estimate of the number entering each stage. A test example, using simulated data, is provided with a discussion of the method in relation to other techniques based on the area of the sample curve.     

The effect of environmental disturbances on the dynamics of marine intertidal populations

A model is proposed for studying the influence of the duration of a nonreproducing life stage on the dynamics of marine intertidal populations. Analysis of the model shows that this system, in which the time delay (the nonreproducing stage) is in a density independent term, has two solutions. When the nonzero solution exists it is a stable point. A randomly occurring environmental disturbance, to which only the nonreproducing stage is resistant, is superimposed on the basic deterministic equation. Average extinction time, estimated by simulation, appears as a a nonmonotonic function of the duration of disturbance. The graph of extinction time has multiple extrema with minima occuring where the ratio between the duration of the resistant stage and the duration of disturbance is an integer. This phenomenon is more sharply manifested when the intrinsic growth rate and frequency of disturbance are relatively large and when the variance in the duration of disturbance and the duration of the resistant stage is not too large. Increasing patchiness of the habitat has a minor effect on the pattern of dependence of the extinction time on the ratio between the juvenile and environmental periods. The suitability of the model for describing the marine intertidal system of the northern Red Sea is discussed, and it is suggested that the duration of the larval stage can determine adult population dynamics.     

STUDIES ON THE KINETICS OF INITIAL CYCLE PROGRESSION IN VITRO OF ASCITES TUMOUR CELLS SUBSEQUENT TO ISOLATION FROM ASCITES FLUID

A method is described for determining the duration of cell cycle phases traversed by cells responding to release from proliferation restraint. Experiments have been performed with arrested Yoshida ascites hepatoma cells allowed to re-enter the growing stage after transfer of cells from the late stage of ascites into an in vitro incubation system. Experimentally, this method requires information on the rate of incorporation of labelled thymidine and on the rate of increase in cell number. The rate of [¹⁴C]thymidine incorporation in vitro was shown to be directly proportional to the number of cells synthesizing DNA. This was shown by correlating data from measurements of the rate of thymidine incorporation with those from measurements of the labelling index of the cell population. Theoretically, the method is based on analysis of the region limited by two integral curves, one corresponding to the kinetics of cell entry into and the other to the kinetics of exit from the S-phase. From data on the actual rate of increase in the total number of cells and data on the S-phase duration it is possible to obtain information on the cytokinetics of growth resumption by the ascites cell population.     

A Study on the Model for Estimation Winter Wheat Yield Using Spectral Data of Wheat Field

A new dynamic vegetation index (VI)-yield model, that is, the leaf area duration (LAD)-yield model was structured for estimating winter wheat yield according to the measured reflection spectral data on the wheat field, and the relationship between wheat yield and LAI. The model had the information on the photosynthetic area and time during the later period of wheat growth, i. e., the period from the heading stage to the end of filling stage. The accuracy of the estimated wheat yield arrived up to 98% .In addition, the winter wheat yield was also estimated by a VI-yield model in a given wheat growing stage, and the VI in several main wheat growing stages were used for this purpose. The results suggested that the best season for estimating wheat yield using the VI-yield model was in the middle of wheat filling stage for the case study in Yucheng, Shandong province. The accuracy of the estimation could arrive at 96%.     

冬小麦单产的光谱数据估测模型研究

 本文在分析冬小麦群体经济产量与叶面积系数关系的基础上,以地面实测冬小麦反射光谱数据为依据,提出了一种新的动态VI-产量模型,即LAD-产量模型。该模型具有冬小麦生育后期(抽穗一灌浆末期)光合面积和光合时间等信息,其冬小麦单位面积产量(简称单产)估测精度为98%。另外,本文根据常用的某一特定生育期VI-产量模型,用冬小麦各生育期的VI值分别估测小麦单产,确定山东省禹城市冬小麦的灌浆中期为最佳估产时间。此时期．小麦单产估测精度为96%。     

Using Nested Models and Laboratory Data for Predicting Population Effects of Contaminants on Fish: A Step Toward a Bottom-Up Approach for Establishing Causality in Field Studies

Predicting the effects of contaminants on fish populations is difficult due to their complex life history and high interannual variation in their population abundances. We present an approach that extrapolates laboratory data on contaminant effects, including behavioral effects, to the population level by using a series of nested statistical and simulation models. The approach is illustrated using PCB effects on Atlantic croaker. Laboratory experiments were performed that estimated PCB effects on fecundity, egg mortality, and the swimming speed and predator evasion behavior of larvae. A statistical model converted impaired predator evasion to reduced probability of escaping a predatory fish. An individual-based model then converted the output of the statistical model into changes in larval stage duration and survival, which were used to change elements of the matrix model. A matrix projection model simulated population dynamics for 100 years for baseline conditions and for two hypothetical PCB exposure scenarios. PCB effects were imposed in the model by reducing the fecundity of exposed adults, increasing egg mortality, and increasing the larval stage duration and mortality rate. Predicted population effects of PCBs were small relative to the interannual variation. Our analysis is a step toward understanding population responses to stressors and for ultimately establishing causality in field situations.     

Histogram-Based Calibration Method for Pipeline ADCs

Measurement and calibration of an analog-to-digital converter (ADC) using a histogram-based method requires a large volume of data and a long test duration, especially for a high resolution ADC. A fast and accurate calibration method for pipelined ADCs is proposed in this research. The proposed calibration method composes histograms through the outputs of each stage and calculates error sources. The digitized outputs of a stage are influenced directly by the operation of the prior stage, so the results of the histogram provide the information of errors in the prior stage. The composed histograms reduce the required samples and thus calibration time being implemented by simple modules. For 14-bit resolution pipelined ADC, the measured maximum integral non-linearity (INL) is improved from 6.78 to 0.52 LSB, and the spurious-free dynamic range (SFDR) and signal-to-noise-and-distortion ratio (SNDR) are improved from 67.0 to 106.2dB and from 65.6 to 84.8dB, respectively.     

The importance of individual developmental variation in stage‐structured population models

Population stage structure is fundamental to ecology, and models of this structure have proven useful in many different systems. Many ecological variables other than stage, such as habitat type, site occupancy and metapopulation status are also modelled using transitions among discrete states. Transitions among life stages can be characterised by the distribution of time spent in each stage, including the mean and variance of each stage duration and within‐individual correlations among multiple stage durations. Three modelling traditions represent stage durations differently. Matrix models can be derived as a long‐run approximation from any distribution of stage durations, but they are often interpreted directly as a Markov model for stage transitions. Statistical stage‐duration distribution models accommodate the variation typical of cohort development data, but such realism has rarely been incorporated in population theory or statistical population models. Delay‐differential equation models include lags but no variation, except in limited cases. We synthesise these models in one framework and illustrate how individual variation and correlations in development can impact population growth. Furthermore, different development models can yield the same long‐term matrix transition rates but different sensitivities and elasticities. Finally, we discuss future directions for estimating realistic stage duration models from data.     

A Markov chain model for animal estrous cycling data

Estrous cycling data contain sequences of characters (e.g., DPEMD). Each sequence represents an animal's estrous cycle, with each character indicating the daily estrous cycle stage. Changes in the estrous cycle pattern, which is determined by estrous stage lengths, can provide information on adverse events. Stage lengths are not directly observable. However interval censored lengths for all but the first and the last stages in a sequence can be extracted from the data. We propose a Markov chain model to approximate the estrous cycling process. The transition probabilities from one stage to another can be derived by conditioning on stage lengths. Assuming Weibull distribution for stage lengths, with the second Weibull parameter depending upon treatment effects and animal-specific random effects, regression models on censored stage lengths are fitted. A Bayesian approach is used for inference on dose effects. The analysis is implemented with MCMC method in WinBUGS. An estrous cycling data set from a National Toxicology Program study is analyzed as an example.     

Modelling gastric evacuation in gadoids feeding on crustaceans

A mechanistic, prey surface‐dependent model was expanded to describe the course and rate of gastric evacuation in predatory fishes feeding on crustacean prey with robust exoskeletons. This was accomplished by adding a layer of higher resistance to the digestive processes outside the inner softer parts of a prey cylinder abstraction and splitting up the prey evacuation into two stages: an initial stage where the exoskeleton is cracked and a second where the prey remains are digested and evacuated. The model was parameterized for crustaceans with different levels of armour fed to Atlantic cod Gadus morhua or whiting Merlangius merlangus and recovered from the stomachs at different post‐prandial times. The prey species were krill Meganyctiphanes norvegica; shrimps and prawns Crangon crangon, Pandalus borealis, Pandalus montagui and Eualus macilentus; crabs Liocarcinus depurator and Chionoecetes opilio. In accordance with the apparent intraspecific isometric relationship between exoskeleton mass and total body mass, the model described stage duration and rate of evacuation of the crustacean prey independently of meal and prey sizes. The duration of the first stage increased (0–33 h) and the evacuation rate of both stages decreased (by a half) with increasing level of the crustacean armament in terms of chitin and ash. A common, interspecific parameterization of the model within each of the categories krill, shrimp and crab can probably be used if the contents of chitin and ash are similar among prey species per prey category. The model offers a simple way for estimating evacuation rates from stomach content data in order to obtain food consumption rates of wild fishes, provided that information about digestion stage of crustacean prey is available.     

Estimating the variation in S phase duration from flow cytometric histograms

A stochastic model for interpreting BrdUrd DNA FCM-derived data is proposed. The model is based on branching processes and describes the progression of the DNA distribution of BrdUrd-labelled cells through the cell cycle. With the main focus on estimating the S phase duration and its variation, the DNA replication rate is modelled by a piecewise linear function, while assuming a gamma distribution for the S phase duration. Estimation of model parameters was carried out using maximum likelihood for data from two different cell lines. The results provided quite a good fit to the data, suggesting that stochastic models may be a valuable tool for analysing this kind of data.     

Zooplankton cohort analysis using systems identification techniques

The linear-transfer and lag-Manly models of zooplankton cohortdevelopment were examined using data generated from a thirdmore realistic model. The more realistic multi-transfer modelincluded variance in development rate among individuals. Thelinear-transfer model produced highly biased estimates of developmentrate under conditions of rapidly changing recruitment. Althoughits performance was improved by increasing the number of modeledstages and thus decreasing the rate of change in recruitmentcompared to stage duration, a positive bias remained. The lag-Manlymodel also produced positively biased estimates of stage durationgiven non-zero variance in development rates. A comparison ofthe models' performances under different simulated samplingregimes recommended the multi-transfer model. Use of the multi-transfermodel was illustrated by determining the development and mortalityrates of the brine shrimp, Artemia monica reared under threedifferent conditions of food and temperature corresponding tonatural regimes in Mono Lake, California. The experimental conditionsand sampling regime resulted in high relative standard errors(mean, 33%) in stage abundance estimates not atypical of zooplanktonsampling regimes in lakes. A Monte Carlo analysis was used todetermine the uncertainty in estimated parameters and determinethe level of stage aggregation which maximized the amount ofinformation derived from the experiments.     

Census timing alters stage duration distributions in matrix population models

Matrix population models are widely used to study the dynamics of stage‐structured populations. A census in these models is an event monitoring the number of individuals in each stage and occurs at discrete time intervals. The two most common methods used in building matrix population models are the prebreeding census and postbreeding census. Models using the prebreeding and postbreeding censuses assume that breeding occurs immediately before or immediately after the censuses, respectively. In some models such as age‐structured models, the results are identical regardless of the method used, rendering the choice of method a matter of preference. However, in stage‐structured models, where the duration of the first stage of life varies among newborns, a choice between the prebreeding and postbreeding censuses may result in different conclusions. This is attributed to the different first‐stage duration distributions assumed by the two methods. This study investigated the difference emerging in the structures of these models and its consequence on conclusions of eigenvalue and elasticity analyses using two‐stage models. Considerations required in choosing a modeling method are also discussed.     

A simple method to estimate insect mortality from field census data: A modification of the Kiritani-Nakasuji-Manly method

Various methods have been proposed to estimate demographic parameters such as mortality from field census data. Simple methods proposed earlier are applicable only for limited situations. For example, the Kiritani-Nakasuji-Manly method is applicable only if individuals are observable until their death. Improved methods proposed later are not subject to such limitations, but are not so widely used in the field of applied entomology, probably because of the complexity of the calculations involved. In this paper, I propose an intermediate method that requires only a pocket calculator, considering the practical convenience for field scientists. This method, which is a modification of the Kiritani-Nakasuji-Manly method, gives an estimate of the number of individuals entering a stage from the frequency of two stages when the stage duration is known.     

Analysis of pulsatile hormone concentration profiles with nonconstant Basal concentration: a bayesian approach

Many challenges arise in the analysis of pulsatile, or episodic, hormone concentration time series data. Among these challenges is the determination of the number and location of pulsatile events and the discrimination of events from noise. Analyses of these data are typically performed in two stages. In the first stage, the number and approximate location of the pulses are determined. In the second stage, a model (typically a deconvolution model) is fit to the data conditional on the number of pulses. Any error made in the first stage is carried over to the second stage. Furthermore, current methods, except two, assume that the underlying basal concentration is constant. We present a fully Bayesian deconvolution model that simultaneously estimates the number of secretion episodes, as well as their locations, and a nonconstant basal concentration. This model obviates the need to determine the number of events a priori. Furthermore, we estimate probabilities for all "candidate" event locations. We demonstrate our method on a real data set.     

Uncertain branch lengths, taxonomic sampling error, and the egg to body size allometry in temperate butterflies (Lepidoptera)

The allometry of egg to body size in temperate butterflies, and the relationships between egg size and larval host structure, taxonomy, voltinism, and duration of the egg stage, are investigated using cross-species analysis and the comparative analysis of independent contrasts. In addition, the effect of two sources of uncertainty that may affect continuous data when treated under a statistical, comparative, framework, is assessed: (1) unknown evolutionary distances, and (2) taxonomic representativity (proportion of species of a given taxon, from which data are available). It is suggested that the effects of taxonomic under-representation could be important in comparative, quantitative studies, but this problem may be tempered by means of weighted regression. Under the assumption that taxonomy represents butterfly phylogeny, egg and adult body size are related by negative allometry (i.e. the slope of the line fitted to the logarithmically transformed data is lower than 1.0). However, the precise slope (0.2-0.9) depends on the method used, branch lengths, and taxonomic sampling. There is evidence for a relationship between a species' voltinism and the number of days it spends in the egg stage, as well as between adult butterfly size and the gross structure of the plants used as larval hosts (woody plants or herbs). Egg size proves to be related to foodplant taxonomy, voltinism, and duration of the egg stage when the data are analysed using species means, but these relationships become non-significant when the comparative method is employed.     

物候模式识别在生态动力预报中的应用

以物候资料和数值天气预报模式输出图为基础,应用模式识别和数理逻辑判断的自动化技术,阐述制作生态动力预报的原理、方法和步骤.生态动力预报技术使传统的物候学在气象学和自动化技术支持下,扩展应用到生态预报业务领域,使物候预报从单站预报阶段发展到区域预报阶段,同时促进了农业气象预报方法从定性、统计阶段向动力预报阶段发展.该方法在农作物播种、长势、灌溉与施肥、病虫害防治等方面具有广阔的应用前景.     

Amygdala adenosine A1 receptors have no anticonvulsant effect on piriform cortex-kindled seizures in rat

Adenosine is an endogenous anticonvulsant that exerts its effects through A1 receptors. As the piriform/amygdala is a critical circuit for limbic seizure propagation, in this study, the role of basolateral amygdala A1 receptors on piriform cortex (PC)-kindled seizures was investigated. Rats were kindled by daily electrical stimulation of PC. In fully kindled animals, bilateral intra-amygdala N6-cyclohexyladenosine (CHA; 10-500 micromol/L, a selective A1 receptor agonist) had no effect on kindled-seizure parameters. However, bilateral intra-amygdala 2% lidocaine (reversal neuronal inhibitor) reduced the kindled seizure severity. There was significant increase in stage 4 latency and decrease in stage 5 duration. Bilateral lesion of basolateral amygdala of kindled animals (by electrical DC current) reduced the kindled seizure severity more dramatically. Our results showed afterdischarge duration, stage 5 duration, and seizure duration were decreased and stage 4 latency increased significantly. In addition, daily intra-amygdala CHA had no significant effect on PC kindling acquisition. Therefore, it may be concluded that although the basolateral amygdala neuronal activity has a critical role in the propagation of epileptic seizures from PC, the amygdala A1 receptors have no role in this regard. On the other hand, amygdala A1 receptors have no anticonvulsant or antiepileptogenic effect on PC-kindled seizures.