An improved method for estimating sequence divergence of DNA using restriction endonuclease mappings

Summary The method proposed by Kaplan and Langley for estimating the extent of sequence divergence between related DNA's using restriction endonuclease maps is modified so that the estimates are easier to compute. In the two-species case, these modifications lead via a maximum likelihood approach to an estimate which is closely related to one recently suggested by Nei and Li (1979) and Gotoh et al. (1979). Simulation studies show that the modified estimates are comparable to those of Kaplan and Langley, providing that there is sufficient homology in the DNA segments of the related species. The M-species case, M 3, is also discussed.     

Interplanetary crew exposure estimates for galactic cosmic rays.

Using the Langley Research Center galactic cosmic-ray transport computer code and the Computerized Anatomical Man model, initial estimates of interplanetary exposure of astronauts to galactic cosmic rays, during periods of solar minimum activity, are made for a realistic human geometry shielded by various thickness of spacecraft aluminum shielding. Conventional dose assessment in terms of total absorbed dose and dose equivalent is made for the skin, ocular lens, and bone marrow. Included in the analyses are separate evaluations of the contributions from the incident primary ions, from subsequent-generation fragmentation products, and from target fragments. In all cases considered, the equivalent sphere approximation yielded conservative overestimates for the actual organ exposures.     

Individualized performance prediction of sleep-deprived individuals with the two-process model.

We present a new method for developing individualized biomathematical models that predict performance impairment for individuals restricted to total sleep loss. The underlying formulation is based on the two-process model of sleep regulation, which has been extensively used to develop group-average models. However, in the proposed method, the parameters of the two-process model are systematically adjusted to account for an individual's uncertain initial state and unknown trait characteristics, resulting in individual-specific performance prediction models. The method establishes the initial estimates of the model parameters using a set of past performance observations, after which the parameters are adjusted as each new observation becomes available. Moreover, by transforming the nonlinear optimization problem of finding the best estimates of the two-process model parameters into a set of linear optimization problems, the proposed method yields unique parameter estimates. Two distinct data sets are used to evaluate the proposed method. Results of simulated data (with superimposed noise) show that the model parameters asymptotically converge to their true values and the model prediction accuracy improves as the number of performance observations increases and the amount of noise in the data decreases. Results of a laboratory study (82 h of total sleep loss), for three sleep-loss phenotypes, suggest that individualized models are consistently more accurate than group-average models, yielding as much as a threefold reduction in prediction errors. In addition, we show that the two-process model of sleep regulation is capable of representing performance data only when the proposed individualized model is used.     

John Newport Langley and His Construction of the Autonomic (Vegetative) Nervous System

The paper describes the scientific career of Professor John Newport Langley, an outstanding English physiologist and histologist, member of the London Royal Society and its Vice-President. The main scientific achievements of Langley are dealing with anatomy and physiology of the autonomic (vegetative) nervous system that he considered as an entirely efferent system. The autonomic nervous system was divided by Langley into three parts: sympathetic, parasympathetic, and enteral (intestinal) systems. He has also established functional differences of the autonomic nervous system from the somatic one. He suggested the presence of synaptic contacts on muscle and secretory cells, as well as the existence in these synaptic structures of a peculiar receptor substance providing interaction of nerve fibers with postganglionic neurons and effector cells of visceral organs. The examples of development of several Langley's concepts at present are given.     

Bias Reduction and a Solution for Separation of Logistic Regression with Missing Covariates

Summary Logistic regression is an important statistical procedure used in many disciplines. The standard software packages for data analysis are generally equipped with this procedure where the maximum likelihood estimates of the regression coefficients are obtained iteratively. It is well known that the estimates from the analyses of small‐ or medium‐sized samples are biased. Also, in finding such estimates, often a separation is encountered in which the likelihood converges but at least one of the parameter estimates diverges to infinity. Standard approaches of finding such estimates do not take care of these problems. Moreover, the missingness in the covariates adds an extra layer of complexity to the whole process. In this article, we address these three practical issues—bias, separation, and missing covariates by means of simple adjustments. We have applied the proposed technique using real and simulated data. The proposed method always finds a solution and the estimates are less biased. A SAS macro that implements the proposed method can be obtained from the authors.     

Recursive implementations of temporal filters for image motion computation

 Efficient algorithms for image motion computation are important for computer vision applications and the modelling of biological vision systems. Intensity-based image motion computation proceeds in two stages: the convolution of linear spatiotemporal filter kernels with the image sequence, followed by the non-linear combination of the filter outputs. If the spatiotemporal extent of the filter kernels is large, then the convolution stage can be very intensive computationally. One effective means of reducing the storage required and computation involved in implementing the temporal convolutions is the introduction of recursive filtering. Non-recursive methods require the number of frames of the image sequence stored at any given time to be equal to the temporal extent of the slowest temporal filter. In contrast, recursive methods encode recent stimulus history implicitly in the values of a small number of variables updated through a series of feedback equations. Recursive filtering reduces the number of values stored in memory during convolution and the number of mathematical operations involved in computing the filters' outputs. This paper extends previous recursive implementations of gradient- and correlation-based motion analysis algorithms [Fleet DJ, Langley K (1995) IEEE PAMI 17: 61–67; Clifford CWG, Ibbotson MR, Langley K (1997) Vis Neurosci 14: 741–749], describing a recursive implementation of causal band-pass temporal filters suitable for use in energy- and phase-based algorithms for image motion computation. It is shown that the filters' temporal frequency tuning curves fit psychophysical estimates of the temporal properties of human visual filters [Hess RF, Snowden RJ (1992) Vision Res 32: 47–60]. Received: 20 April 1999 /Accepted in revised form: 8 November 1999     

The effect of homozygosity of selective differences between sites of transposable elements

The behavior of the frequency spectrum of sites of transposable elements for the model proposed by Langley, Brookfield, and Kaplan ((1983) Genetics 104) is studied when some of the sites have weak additive selection against the host. In particular, it is shown that under certain conditions, the expected homozygosity at equilibrium will always be larger when there is variation in selection between sites than when such variation is absent.     

Creating spatially continuous maps of past land cover from point estimates: A new statistical approach applied to pollen data

Reliable estimates of past land cover are critical for assessing potential effects of anthropogenic land-cover changes on past earth surface-climate feedbacks and landscape complexity. Fossil pollen records from lakes and bogs have provided important information on past natural and human-induced vegetation cover. However, those records provide only point estimates of past land cover, and not the spatially continuous maps at regional and sub-continental scales needed for climate modelling.We propose a set of statistical models that create spatially continuous maps of past land cover by combining two data sets: 1) pollen-based point estimates of past land cover (from the REVEALS model) and 2) spatially continuous estimates of past land cover, obtained by combining simulated potential vegetation (from LPJ-GUESS) with an anthropogenic land-cover change scenario (KK10). The proposed models rely on statistical methodology for compositional data and use Gaussian Markov Random Fields to model spatial dependencies in the data.Land-cover reconstructions are presented for three time windows in Europe: 0.05, 0.2, and 6 ka years before present (BP). The models are evaluated through cross-validation, deviance information criteria and by comparing the reconstruction of the 0.05 ka time window to the present-day land-cover data compiled by the European Forest Institute (EFI). For 0.05 ka, the proposed models provide reconstructions that are closer to the EFI data than either the REVEALS- or LPJ-GUESS/KK10-based estimates; thus the statistical combination of the two estimates improves the reconstruction. The reconstruction by the proposed models for 0.2 ka is also good. For 6 ka, however, the large differences between the REVEALS- and LPJ-GUESS/KK10-based estimates reduce the reliability of the proposed models. Possible reasons for the increased differences between REVEALS and LPJ-GUESS/KK10 for older time periods and further improvement of the proposed models are discussed.     

A Life Table Regression Analysis for Complex Survey Data

A methodology for obtaining maximum likelihood estimates of life table regression coefficients from complex survey data is presented. Certain of the issues of writing a likelihood for survey data are presented and discussed. The proposed methodology includes consideration of the sampling design in any inference by using design based variance estimates for the parameters. An example is given using data from the 1973 United States National Survey of Family Growth.     

Log-linear models in the analysis of disease prevalence data from survival/sacrifice experiments.

This paper considers the problem of analyzing disease prevalence data from survival experiments in which there may also be some serial sacrifice. The assumptions needed for "standard" analyses are reviewed in the context of a general model recently proposed by the authors. This model is then reparametrized in log-linear form, and a generalized EM algorithm is utilized to obtain maximum likelihood estimates of the parameters for a broad class of unsaturated models. Tests based on the relative likelihood are proposed to investigate the effects of treatment, time, and the presence of other diseases on the prevalences and lethalities of specific diseases of interest. An example is given, using data from a large experiment to investigate the effects of low-level radiation on laboratory mice. Finally, some possible directions for future research are indicated.     

The effect on homozygosity of selective differences between sites of transposable elements

The behavior of the frequency spectrum of sites of transposable elements for the model proposed by Langley, Brookfield, and Kaplan ((1983) Genetics 104) is studied when some of the sites have weak additive selection against the host. In particular, it is shown that under certain conditions, the expected homozygosity at equilibrium will always be larger when there is variation in selection between sites than when such variation is absent.     

Two-sample nonparametric estimation and confidence intervals under truncation.

We consider point estimates and confidence intervals for the difference in location or scale between two populations when the observations are subject to truncation. We suggest procedures analogous to those for the complete-sample case. A rigorous justification is presented to support the proposed confidence interval procedure. Finally, some simulations verify the properties of the estimators and confidence intervals. We illustrate the procedure using data on tumor size.     

DNA Polymorphism Detectable by Restriction Endonucleases

Data on DNA polymorphisms detected by restriction endonucleases are rapidly accumulating. With the aim of analyzing these data, several different measures of nucleon (DNA segment) diversity within and between populations are proposed, and statistical methods for estimating these quantities are developed. These statistical methods are applicable to both nuclear and nonnuclear DNAs. When evolutionary change of nucleons occurs mainly by mutation and genetic drift, all the measures can be expressed in terms of the product of mutation rate per nucleon and effective population size. A method for estimating nucleotide diversity from nucleon diversity is also presented under certain assumptions. It is shown that DNA divergence between two populations can be studied either by the average number of restriction site differences or by the average number of nucleotide differences. In either case, a large number of different restriction enzymes should be used for studying phylogenetic relationships among related organisms, since the effect of stochastic factors on these quantities is very large. The statistical methods developed have been applied to data of Shah and Langley on mitochondrial (mt)DNA from Drosophila melanogaster, simulans and virilis. This application has suggested that the evolutionary change of mtDNA in higher animals occurs mainly by nucleotide substitution rather than by deletion and insertion. The evolutionary distances among the three species have also been estimated.     

Efficiency and robustness of pedigree segregation analysis.

Different pedigree structures and likelihoods are examined to determine their efficiency for parameter estimation under one-locus models. For the cases simulated, family size has little effect; estimates based on unconditional likelihoods are generally more efficient than those based on conditional likelihoods. The proposed method of pedigree analysis under a one-locus model is found to be robust in the analysis of nuclear families: skewness of the data and polygenic inheritance will not lead to the spurious detection of major loci unless they occur simultaneously, and together with a moderate amount of environmental correlation among sibs.     

On the divergence of members of a transposable element family

Statistical properties of the amount of divergence of members of a transposable element family are studied. The analysis is based on the model proposed by Langley et al. [5], describing the evolution of a family of selectively neutral transposable elements in a finite haploid population of size 2N. By considering the time back to the most recent common ancestor of two copies, both the probability of identity and the moments of the number of sites that differ between two sampled copies are obtained. Our analytic results are consistent with the numerical results of Ohta [8] for a similar model. The effects of gene conversion are also examined. In agreement with Slatkin [9], we find that gene conversion has a minimal effect on the probability of identity providing that the rate of deletion is sufficiently large.     

Adenosine-5'-phosphate deaminase. A novel herbicide target.

The isolation of carbocyclic coformycin as the herbicidally active component from a fermentation of Saccharothrix species was described previously (B.D. Bush, G.V. Fitchett, D.A. Gates, D. Langley [1993] Phytochemistry 32: 737-739). Here we report that the primary mode of action of carbocyclic coformycin has been identified as inhibition of the enzyme AMP deaminase (EC 3.5.4.6) following phosphorylation at the 5' hydroxyl on the carbocyclic ring in vivo. When pea (Pisum sativum L. var Onward) seedlings are treated with carbocyclic coformycin, there is a very rapid and dramatic increase in ATP levels, indicating a perturbation in purine metabolism. Investigation of the enzymes of purine metabolism showed a decrease in the extractable activity of AMP deaminase that correlates with a strong, noncovalent association of the phosphorylated natural product with the protein. The 5'-phosphate analog of the carbocyclic coformycin was synthesized and shown to be a potent, tight binding inhibitor of AMP deaminase isolated from pea seedlings. Through the use of a synthetic radiolabeled marker, rapid conversion of carbocyclic coformycin to the 5'-phosphate analog could be demonstrated in vivo. It is proposed that inhibition of AMP deaminase leads to the death of the plant through perturbation of the intracellular ATP pool.     

A resolution of the ascertainment sampling problem. II. Generalizations and numerical results

The ascertainment problem arises when families are sampled by a nonrandom process and some assumption about this sampling process must be made in order to estimate genetic parameters. Under classical ascertainment assumptions, estimation of genetic parameters cannot be separated from estimation of the parameters of the ascertainment process, so that any misspecification of the ascertainment process causes biases in estimation of the genetic parameters. Ewens and Shute proposed a resolution to this problem, involving conditioning the likelihood of the sample on the part of the data which is "relevant to ascertainment." The usefulness of this approach can only be assessed by examining the properties (in particular, bias and standard error) of the estimates which arise by using it for a wide range of parameter values and family size distributions and then comparing these biases and standard errors with those arising under classical ascertainment procedures. These comparisons are carried out in the present paper, and we also compare the proposed method with procedures which condition on, or ignore, parts of the data.     

Estimates of a Treatment Effect Based on Censored Data Rank Tests

Linear rank test statistics are applied to the problem of estimating a treatment effect if two sets of censored failure time data are compared and the distributions of the log-failure times of the two samples are assumed to differ only in location. Rank tests for this accelerated failure time model are reviewed and Hodges-Lehmann type estimates for the shift parameter are proposed. Properties of these estimates are investigated, computational aspects are discussed and an example is presented.     

The effects of pollen and seed migration on nuclear-dicytoplasmic systems. II. A new method for estimating plant gene flow from joint nuclear-cytoplasmic data

A new maximum-likelihood method is developed for estimating unidirectional pollen and seed flow in mixed-mating plant populations from counts of joint nuclear-cytoplasmic genotypes. Data may include multiple unlinked nuclear markers with a single maternally or paternally inherited cytoplasmic marker, or with two cytoplasmic markers inherited through opposite parents, as in many conifer species. Migration rate estimates are based on fitting the equilibrium genotype frequencies under continent-island models of plant gene flow to the data. Detailed analysis of their equilibrium structures indicates when each of the three nuclear-cytoplasmic systems allows gene flow estimation and shows that, in general, it is easier to estimate seed than pollen migration. Three-locus nuclear-dicytoplasmic data only increase the conditions allowing seed migration estimates; however, the additional dicytonuclear disequilibria allow more accurate estimates of both forms of gene flow. Estimates and their confidence limits for simulated data sets confirm that two-locus data with paternal cytoplasmic inheritance provide better estimates than those with maternal inheritance, while three-locus dicytonuclear data with three modes of inheritance generally provide the most reliable estimates for both types of gene flow. Similar results are obtained for hybrid zones receiving pollen and seed flow from two source populations. An estimation program is available upon request.     

Spline-based semiparametric projected generalized estimating equation method for panel count data

We propose to analyze panel count data using a spline-based semiparametric projected generalized estimating equation (GEE) method with the proportional mean model E(N(t)|Z) = Λ(0)(t) e(β(0)(T)Z). The natural logarithm of the baseline mean function, logΛ(0)(t), is approximated by a monotone cubic B-spline function. The estimates of regression parameters and spline coefficients are obtained by projecting the GEE estimates into the feasible domain using a weighted isotonic regression (IR). The proposed method avoids assuming any parametric structure of the baseline mean function or any stochastic model for the underlying counting process. Selection of the working covariance matrix that accounts for overdispersion improves the estimation efficiency and leads to less biased variance estimations. Simulation studies are conducted using different working covariance matrices in the GEE to investigate finite sample performance of the proposed method, to compare the estimation efficiency, and to explore the performance of different variance estimates in presence of overdispersion. Finally, the proposed method is applied to a real data set from a bladder tumor clinical trial.