Temporal changes in the abundance, leaf growth and photosynthesis of three co-occurring Philippine seagrasses

The analysis of the temporal changes in shoot density, areal leaf biomass, leaf growth and parameters of the photosynthesis–irradiance relationship of three tropical seagrass species (Enhalus acoroides, Thalassia hemprichii and Cymodocea rotundata), co-existing in a shallow subtidal meadow in Cape Bolinao, Philippines, shows that species-specific traits are significant sources of temporal variability, and indicates that these seagrass species respond differently to a common environmental forcing. Species-specific differences are much less important as source of variability of the temporal change in chlorophyll concentration of seagrass leaves. The results indicate that the temporal changes in photosynthetic performance of these seagrasses were driven by environmental forcing and their specific responses to it mostly, but the temporal change in their abundance and leaf growth was also controlled by other factors. The significant contribution of species-specific factors in the temporal changes of biomass, growth and photosynthetic performance of co-occurring seagrass species in Cape Bolinao should contribute to the maintenance of the multispecific, highly productive meadows characteristic of pristine coastal ecosystems in Southeast (SE) Asia.     

Detecting interaction between random region and fixed age effects in disease mapping

The purpose of this article is to draw attention to the possible need for inclusion of interaction effects between regions and age groups in mapping studies. We propose a simple model for including such an interaction in order to develop a test for its significance. The assumption of an absence of such interaction effects is a helpful simplifying one. The measure of relative risk related to a particular region becomes easily and neatly summarized. Indeed, such a test seems warranted because it is anticipated that the simple model, which ignores such interaction, as is in common use, may at times be adequate. The test proposed is a score test and hence only requires fitting the simpler model. We illustrate our approaches using mortality data from British Columbia, Canada, over the 5-year period 1985-1989. For this data, the interaction effect between age groups and regions is quite large and significant.     

Robust two-stage estimation in hierarchical nonlinear models

Hierarchical models encompass two sources of variation, namely within and among individuals in the population; thus, it is important to identify outliers that may arise at each sampling level. A two-stage approach to analyzing nonlinear repeated measurements naturally allows parametric modeling of the respective variance structure for the intraindividual random errors and interindividual random effects. We propose a robust two-stage procedure based on Huber's (1981, Robust Statistics) theory of M-estimation to accommodate separately aberrant responses within an experimental unit and subjects deviating from the study population when the usual assumptions of normality are violated. A toxicology study of chronic ozone exposure in rats illustrates the impact of outliers on the population inference and hence the advantage of adopting the robust methodology. The robust weights generated by the two-stage M-estimation process also serve as diagnostics for gauging the relative influence of outliers at each level of the hierarchical model. A practical appeal of our proposal is the computational simplicity since the estimation algorithm may be implemented using standard statistical software with a nonlinear least squares routine and iterative capability.     

Zinc inhibits the mixed lymphocyte culture

The mixed lymphocyte culture (MLC) is an established clinical method for bone marrow transplantation, as it serves as an in vitro model for allogenic reaction and transplantation. We previously showed that cytokine release into the supernatant is a more specific and sensitive parameter for cross-reactivity in the MLC than the common measurement of cell proliferation. Therefore we tried to find an inhibitor of the MLC in vitro with the least side effects in vivo, measuring interferon (IFN)-γ as one of the most important cytokines in posttransplant medicine. Earlier studies showed that zinc is an important trace element for immune function with both stimulatory and inhibitory effects on immune cells. We found that slightly elevated zinc concentrations (three to four times the physiological level), which do not decrease T-cell proliferation in vitro nor produce immunosuppressive effects in vivo, suppress alloreactivity in the mixed lymphocyte culture. In this report we analyzed the mechanism whereby zinc influences the MLC to possibly find a nontoxic way of immunosuppression.     

Nonlinear estimation and statistical testing of periods in nonsinusoidal longitudinal time series with unequidistant observations

The analysis of multiple components is often used to model biological variables that show nonsinusoidal predictable changes of known periods. In general, to anticipate the periods is not easy, and even in cases when we have some a priori information, it is advisable to have a statistical tool to test the chosen periods. In this work, we introduce a statistical procedure to estimate periods of longitudinal series by applying nonlinear regression techniques to the multiple sinusoidal model, as well as to the general linear model. Approximate inferences about the parameters of the model are carried out under the usual hypothesis of normality, independence, and constant variance of the errors. Confidence intervals (CIs) for each individual parameter, as well as for the amplitude-acrophase pair or for any other subgroup of parameters of interest, can be computed. As in the linear analysis of multiple components, it is possible to check the existence of rhythm by means of a zero-amplitude test. The method also allows statistical testing of several hypotheses related to the periods. For example, it is possible to test if the periods are equal to certain values of chronobiologic interest and to check if some components included in the model are harmonically related. On the other hand, when the fitted components have proximal periods, the method allows one to verify if they are modeling the same or different spectral peaks. The method, which was validated by a simulation study for a model of two components and is illustrated by an example of modeling the diastolic blood pressure of two subjects, represents a new step in the development of statistical procedures in chronobiology. (Chronobiology International, 18(2), 285-308, 2001)     

SLLE for predicting membrane protein types

Introduction of the concept of pseudo amino acid composition (PROTEINS: Structure, Function, and Genetics 43 (2001) 246; Erratum: ibid. 44 (2001) 60) has made it possible to incorporate a considerable amount of sequence-order effects by representing a protein sample in terms of a set of discrete numbers, and hence can significantly enhance the prediction quality of membrane protein type. As a continuous effort along such a line, the Supervised Locally Linear Embedding (SLLE) technique for nonlinear dimensionality reduction is introduced (Science 22 (2000) 2323). The advantage of using SLLE is that it can reduce the operational space by extracting the essential features from the high-dimensional pseudo amino acid composition space, and that the cluster-tolerant capacity can be increased accordingly. As a consequence by combining these two approaches, high success rates have been observed during the tests of self-consistency, jackknife and independent data set, respectively, by using the simplest nearest neighbour classifier. The current approach represents a new strategy to deal with the problems of protein attribute prediction, and hence may become a useful vehicle in the area of bioinformatics and proteomics.     

Stochastic modeling of nonlinear epidemiology

The objectives of this paper to analyse, model and simulate the spread of an infectious disease by resorting to modern stochastic algorithms. The approach renders it possible to circumvent the simplifying assumption of linearity imposed in the majority of the past works on stochastic analysis of epidemic processes. Infectious diseases are often transmitted through contacts of those infected with those susceptible; hence the processes are inherently nonlinear. According to the classical model of Kermack and McKendrick, or the SIR model, three classes of populations are involved in two types of processes: conversion of susceptibles (S) to infectives (I) and conversion of infectives to removed (R). The master equations of the SIR process have been formulated through the probabilistic population balance around a particular state by considering the mutually exclusive events. The efficacy of the present methodology is mainly attributable to its ability to derive the governing equations for the means, variances and covariance of the random variables by the method of system-size expansion of the nonlinear master equations. Solving these equations simultaneously along with rates associated influenza epidemic data yields information concerning not only the means of the three populations but also the minimal uncertainties of these populations inherent in the epidemic. The stochastic pathways of the three different classes of populations during an epidemic, i.e. their means and the fluctuations around these means, have also been numerically simulated independently by the algorithm derived from the master equations, as well as by an event-driven Monte Carlo algorithm. The master equation and Monte Carlo algorithms have given rise to the identical results.     

Novel Zn (II) and Pb (II) coordination networks with large circuits: Synthesis, crystal structures and self-focusing effects

Two coordination polymers {[Zn(btx)₂(NO₃)₂]}_n (1) and {[Pb(btx)_1.5(NCS)]NO₃}_n (2) (btx = 1,4-bis(triazol-1-ylmethyl)benzene) have been synthesized and characterized by X-ray diffraction. Polymer 1 exhibits a 2-D network with square grid units and polymer 2 possesses an unusual 2-D layered structure with 78-membered rings. By studying the third-order nonlinear optical properties of ligand btx, polymers 1 and 2, we find that they all show strong self-focusing effects. A reasonably good fit between the experimental data and the theoretical curves suggests that the experimentally obtained NLO effects are effectively third-order in nature. The refractive index n₂ values are 4.50 × 10⁻¹⁸ m² W⁻¹ for btx, 3.09 × 10⁻¹⁸ m² W⁻¹ for 1, and 6.01 × 10⁻¹⁸ m² W⁻¹ for 2. All these data can match those of the best-known third-order NLO materials such as inorganic oxides, semiconductors, and cluster compounds. In addition, we discuss the influence of the ligand and central metals on the third-order NLO properties of coordination polymers.     

Maximum likelihood analysis of a general latent variable model with hierarchically mixed data

A general two-level latent variable model is developed to provide a comprehensive framework for model comparison of various submodels. Nonlinear relationships among the latent variables in the structural equations at both levels, as well as the effects of fixed covariates in the measurement and structural equations at both levels, can be analyzed within the framework. Moreover, the methodology can be applied to hierarchically mixed continuous, dichotomous, and polytomous data. A Monte Carlo EM algorithm is implemented to produce the maximum likelihood estimate. The E-step is completed by approximating the conditional expectations through observations that are simulated by Markov chain Monte Carlo methods, while the M-step is completed by conditional maximization. A procedure is proposed for computing the complicated observed-data log likelihood and the BIC for model comparison. The methods are illustrated by using a real data set.