Antigen and haplotype frequencies at three human leucocyte antigen loci (HLA-A, -B, -C) in the Pawaia of Papua New Guinea

The genetic profile of the Pawaia, a seminomadic, linguistic isolate from the highlands fringe of Papua New Guinea, is described in terms of antigen and haplotype frequencies at three class I human leucocyte antigen loci (HLA-A, -B, and -C). The Pawaia, like other Papua New Guinea populations, exhibit restricted polymorphisms at all three loci studied, both in the number of alleles segregating and in the level of average heterozygosity. An extremely high frequency (52.9%) of HLA-B27, the antigen implicated in the pathogenesis of seronegative arthropathies, was found. A novel HLA-C locus specificity, CNG, resulting probably from a gene duplication event, was also observed in significant numbers. Although the gene frequency comparisons suggest their strong affinities with the highlanders, the Pawaia haplotypes reveal significant admixture from other neighbouring groups as well. The usefulness of HLA haplotypes in tracing the movements of human populations in the New Guinea area is discussed.     

Joint modelling of longitudinal and time-to-event data with application to predicting abdominal aortic aneurysm growth and rupture

Shared random effects joint models are becoming increasingly popular for investigating the relationship between longitudinal and time‐to‐event data. Although appealing, such complex models are computationally intensive, and quick, approximate methods may provide a reasonable alternative. In this paper, we first compare the shared random effects model with two approximate approaches: a naïve proportional hazards model with time‐dependent covariate and a two‐stage joint model, which uses plug‐in estimates of the fitted values from a longitudinal analysis as covariates in a survival model. We show that the approximate approaches should be avoided since they can severely underestimate any association between the current underlying longitudinal value and the event hazard. We present classical and Bayesian implementations of the shared random effects model and highlight the advantages of the latter for making predictions. We then apply the models described to a study of abdominal aortic aneurysms (AAA) to investigate the association between AAA diameter and the hazard of AAA rupture. Out‐of‐sample predictions of future AAA growth and hazard of rupture are derived from Bayesian posterior predictive distributions, which are easily calculated within an MCMC framework. Finally, using a multivariate survival sub‐model we show that underlying diameter rather than the rate of growth is the most important predictor of AAA rupture.     

Subset clustering of binary sequences, with an application to genomic abnormality data

This article develops a model-based approach to clustering multivariate binary data, in which the attributes that distinguish a cluster from the rest of the population may depend on the cluster being considered. The clustering approach is based on a multivariate Dirichlet process mixture model, which allows for the estimation of the number of clusters, the cluster memberships, and the cluster-specific parameters in a unified way. Such a clustering approach has applications in the analysis of genomic abnormality data, in which the development of different types of tumors may depend on the presence of certain abnormalities at subsets of locations along the genome. Additionally, such a mixture model provides a nonparametric estimation scheme for dependent sequences of binary data.     

Combining genetic, historical and geographical data to reconstruct the dynamics of bioinvasions: application to the cane toad Bufo marinus

We developed a spatially explicit model of a bioinvasion and used an approximate Bayesian computation (ABC) framework to make various inferences from a combination of genetic (microsatellite genotypes), historical (first observation dates) and geographical (spatial coordinates of introduction and sampled sites) information. Our method aims to discriminate between alternative introduction scenarios and to estimate posterior densities of demographically relevant parameters of the invasive process. The performance of our landscape-ABC method is assessed using simulated data sets differing in their information content (genetic and/or historical data). We apply our methodology to the recent introduction and spatial expansion of the cane toad, Bufo marinus, in northern Australia. We find that, at least in the context of cane toad invasion, historical data are more informative than genetic data for discriminating between introduction scenarios. However, the combination of historical and genetic data provides the most accurate estimates of demographic parameters. For the cane toad, we find some evidence for a strong bottleneck prior to introduction, a small initial number of founder individuals (about 15), a large population growth rate (about 400% per generation), a standard deviation of dispersal distance of 19 km per generation and a high invasion speed at equilibrium (50 km per year). Our approach strengthens the application of the ABC method to the field of bioinvasion by allowing statistical inferences to be made on the introduction and the spatial expansion dynamics of invasive species using a combination of various relevant sources of information.     

Joint analysis of longitudinal data and recurrent episodes data with application to medical cost analysis

This paper discusses regression analysis of longitudinal data in which the observation process may be related to the longitudinal process of interest. Such data have recently attracted a great deal of attention and some methods have been developed. However, most of those methods treat the observation process as a recurrent event process, which assumes that one observation can immediately follow another. Sometimes, this is not the case, as there may be some delay or observation duration. Such a process is often referred to as a recurrent episode process. One example is the medical cost related to hospitalization, where each hospitalization serves as a single observation. For the problem, we present a joint analysis approach for regression analysis of both longitudinal and observation processes and a simulation study is conducted that assesses the finite sample performance of the approach. The asymptotic properties of the proposed estimates are also given and the method is applied to the medical cost data that motivated this study.     

Population studies on an endemic troglobitic beetle: geographical patterns of genetic variation, gene flow and genetic structure compared with morphometric data

Highly specialized obligatory cave beetles endemic to the French Pyrenees offer an opportunity to investigate the relative importance of environmental conditions and ecological characteristics on the organization of genetic variability, to describe the genetic structure of populations, and to assess the extent of gene flow between local populations in relation to geologic structure. Twenty-three geographically close populations of the beetle Speonomus hydrophilus occurring both in caves (reduced fluctuations in many abiotic parameters) and under the deepest layer of soil in mountains (more exposed to climatic variations) were studied. Significant genetic differentiation at 17 allozyme loci was found among populations in close proximity, as well as among those from distant parts of range. On a larger scale, genetic differences among populations appear to result from low dispersal rates between populations. The spatial patterning observed suggests that allozyme frequencies are not responding to environmentally controlled selection. Substantial genetic divergence (F(ST) = 0.112) occurred throughout the range, with important variation in levels of genetic variability (H: 0.065-0.184) among populations. A significant level of substructuring has occurred among the populations with four major geographic areas of similarity indicated. The substructuring of the species into regions suggests an influence of paleoclimatic gradient and paleoenvironment on the population's genetic structure. Also, founder effect and reduced gene flow appear to have influenced populations in the southeastern portion of the range.     

Zero‐modified Poisson model: Bayesian approach,influence diagnostics,and an application to a Brazilian leptospirosis notification data

In this paper, a Bayesian method for inference is developed for the zero‐modified Poisson (ZMP) regression model. This model is very flexible for analyzing count data without requiring any information about inflation or deflation of zeros in the sample. A general class of prior densities based on an information matrix is considered for the model parameters. A sensitivity study to detect influential cases that can change the results is performed based on the Kullback–Leibler divergence. Simulation studies are presented in order to illustrate the performance of the developed methodology. Two real datasets on leptospirosis notification in Bahia State (Brazil) are analyzed using the proposed methodology for the ZMP model.     

Bayesian analysis of a time series of counts with covariates: an application to the control of an infectious disease

This paper presents a Bayesian analysis of a time series of counts to assess its dependence on an explanatory variable. The time series represented is the incidence of the infectious disease ESBL-producing Klebsiella pneumoniae in an Australian hospital and the explanatory variable is the number of grams of antibiotic (third generation) cephalosporin used during that time. We demonstrate that there is a statistically significant relationship between disease occurrence and use of the antibiotic, lagged by three months. The model used is a parameter-driven model in the form of a generalized linear mixed model. Comparison of models is made in terms of mean square error.     

Generalized estimating equations: A pragmatic and flexible approach to the marginal GLM modelling of correlated data in the behavioural sciences

Within behavioural research, non‐normally distributed data with a complicated structure are common. For instance, data can represent repeated observations of quantities on the same individual. The regression analysis of such data is complicated both by the interdependency of the observations (response variables) and by their non‐normal distribution. Over the last decade, such data have been more and more frequently analysed using generalized mixed‐effect models. Some researchers invoke the heavy machinery of mixed‐effect modelling to obtain the desired population‐level (marginal) inference, which can be achieved by using simpler tools—namely by marginal models. This paper highlights marginal modelling (using generalized estimating equations [GEE]) as an alternative method. In various situations, GEE can be based on fewer assumptions and directly generate estimates (population‐level parameters) which are of immediate interest to the behavioural researcher (such as population means). Using four examples from behavioural research, we demonstrate the use, advantages, and limits of the GEE approach as implemented within the functions of the ‘geepack’ package in R.     

Inclusion of phytosociological data in an index of vegetation fire danger: application and mapping on the Karst area around Trieste (Italy)

In this paper we propose a method to produce maps of fire danger index (FDI). The index includes in the formula a vegetation pyrogenic potential index (VPPI) based on floristic phytosociological data. The map of FDI is produced by integrating available phytosociological maps of vegetation, geomorphology and climate, using the Geographic Information System technology. The method is applied to an area of the coastal Classical Karst (NE-Italy). While fire risk maps based on the incidence of previous fires are useful for facilitating emergency operations, e.g. the allocation of fire fighting resources, we conclude that the proposed index offers an effective tool to plan actions for fire prevention.     

A penalized likelihood approach for an illness-death model with interval-censored data: application to age-specific incidence of dementia

We consider the problem of estimating the intensity functions for a continuous time 'illness-death' model with intermittently observed data. In such a case, it may happen that a subject becomes diseased between two visits and dies without being observed. Consequently, there is an uncertainty about the precise number of transitions. Estimating the intensity of transition from health to illness by survival analysis (treating death as censoring) is biased downwards. Furthermore, the dates of transitions between states are not known exactly. We propose to estimate the intensity functions by maximizing a penalized likelihood. The method yields smooth estimates without parametric assumptions. This is illustrated using data from a large cohort study on cerebral ageing. The age-specific incidence of dementia is estimated using an illness-death approach and a survival approach.     

Replication of an association of variation in the FOXO3A gene with human longevity using both case–control and longitudinal data

Genetic variation in FOXO3A has previously been associated with human longevity. Studies published so far have been case–control studies and hence vulnerable to bias introduced by cohort effects. In this study we extended the previous findings in the cohorts of oldest old Danes (the Danish 1905 cohort, N = 1089) and middle‐aged Danes (N = 736), applying a longitudinal study design as well as the case–control study design. Fifteen SNPs were chosen in order to cover the known common variation in FOXO3A. Comparing SNP frequencies in the oldest old with middle‐aged individuals, we found association (after correction for multiple testing) of eight SNPs; 4 (rs13217795, rs2764264, rs479744, and rs9400239) previously reported to be associated with longevity and four novel SNPs (rs12206094, rs13220810, rs7762395, and rs9486902 (corrected P‐values 0.001–0.044). Moreover, we found association of the haplotypes TAC and CAC of rs9486902, rs10499051, and rs12206094 (corrected P‐values: 0.01–0.03) with longevity. Finally, we here present data applying a longitudinal study design; when using follow‐up survival data on the oldest old in a longitudinal analysis, we found no SNPs to remain significant after the correction for multiple testing (Bonferroni correction). Hence, our results support and extent the proposed role of FOXO3A as a candidate longevity gene for survival from younger ages to old age, yet not during old age.     

An extended probabilistic approach of plant vital attributes: an application to European pollen records at 0 and 6 ka

Aim This paper presents a probabilistic method of pollen spectra analysis. The method relies on a pollen taxon characterization using biotic and abiotic plant attribute modes, and their occurrence in a given pollen spectrum at a specific site. This type of analysis can provide an interpretation, which can lead to the reconstruction of the biome and, to an extent, of the abiotic conditions at the site. Methods The analysis has been carried out at the European scale using data provided by the European Pollen Database for about 1000 sites. This dataset contains about 50,000 pollen spectra from the last 21 ka. In these spectra, each pollen taxon has been characterized by a set of 10 chosen attributes. These have been selected with regard to their relevance in biome reconstruction, but also on the basis of available literature. By using the probability of occurrence of each taxon in a given pollen spectrum, it is possible to calculate an affinity index for the spectrum to the attribute considered. To overcome difficulties caused by pollen identification in low diversified pollen spectra, a co‐occurrence concept has been used to give more information. Results The method has been validated on a set of 1327 modern surface samples by comparing the results to the major climatic and environmental variables that control the distribution of the vegetation. A reconstruction exercise on various characteristics of the plants was then carried out on a 6‐ka dataset. This confirmed previous studies by showing a strong dominance of deciduous forest over most of Europe, related to a milder climate than at present in the north and a wetter and colder climate than at present in the south. By analysing the change in pollen/seed dispersion strategies and the light requirement, we show that the history of vegetation dynamics in relation to human influences can be assessed using this method. Main conclusions Our results show that the probabilistic method is an objective tool for pollen assemblage analysis. It allows reconstruction of various characteristics of the vegetation at the continental and global scale for periods and sites with significantly different climate conditions. This method can also be used to compare maps of vegetation attributes for the validation of the new generalized dynamic ecosystems models.     

Significant population structure and asymmetric gene flow patterns amidst expanding populations of Clinus cottoides (Perciformes,Clinidae): application of molecular data to marine conservation planning in South Africa

Clinus cottoides is a fish endemic to the coast of South Africa, predominantly inhabiting rock pools. All South African clinids are viviparous, but probably breed throughout the year; as such, their dispersal may be limited, unlike species with pelagic larval stages. We analysed 343 fish from 14 localities on the west, south and east coasts using two mitochondrial genes and the second intron of the S7 ribosomal gene. Mitochondrial DNA analyses recovered significant genetic differentiation between fish populations from the east coast and other sampling locations, with a second break found between Gansbaai and Cape Agulhas on the south coast. Nuclear DNA recovered shallower, but significant, levels of population structure. Coalescent analyses suggested remarkably asymmetrical gene flow between sampling locations, suggesting that the cold Atlantic Benguela Current and Indian Ocean Agulhas counter‐current play important roles in facilitating dispersal. There was no gene flow between the east coast and the other sites, suggesting that these populations are effectively isolated. Divergence times between them were estimated to at least 68 000 years. Neutrality tests and mismatch distributions suggest recent population expansions, with the exception of peripheral western and eastern populations (possibly a consequence of environmental extremes at the edge of the species distribution). Analyses of the current South African marine protected areas network show that it is not connected and that De Hoop, one of South Africa's largest marine reserves, appears to be an important source population of recruits to both the south and southwest coasts.     

Evaluation of agomelatine stability under different stress conditions using an HPLC method with fluorescence detection: application to the analysis of tablets and human plasma

A simple and highly sensitive stability‐indicating HPLC method was developed and validated for the determination of the new antidepressant agent, agomelatine (AGM). Separation of AGM from its stress‐induced degradation products was achieved on a BDS Hypersil phenyl column (250 mm × 4.6 mm i.d., 5 µm particle size) using methanol–0.05 M phosphate buffer of pH 2.5 (35: 65, v/v) as a mobile phase with fluorescence detection at 230/370 nm. Naproxen was used as an internal standard. The method satisfied all the validation requirements, as evidenced by good linearity (correlation coefficient of 0.9999, over the concentration range 0.4–40.0 ng/mL), accuracy (recovery average 99.55 ± 0.90%), precision (intra‐day RSD 0.54–1.35% and inter‐day RSD 0.93–1.26%), robustness and specificity. The stability of AGM was investigated under different ICH recommended stress conditions including acidic, alkaline, neutral, oxidative and photolytic. AGM was found to be labile to acidic and alkaline degradation and a kinetic study was conducted to explore its degradation behavior. First‐order degradation rate constants and half‐life times were calculated in each case. The proposed method was applied for the determination of AGM in tablets and spiked human plasma with mean percentage recoveries of 99.87 ± 0.31 (n = 3) and 102.09 ± 5.01 (n = 5), respectively. Hence, the proposed method was successfully applied for the determination of AGM in human volunteer plasma. The results were compared statistically with those obtained by a comparison HPLC method revealing no significant differences between the two methods regarding accuracy and precision. Copyright © 2014 John Wiley & Sons, Ltd.     

'Crystal lattice engineering,' an approach to engineer protein crystal contacts by creating intermolecular symmetry: crystallization and structure determination of a mutant human RNase 1 with a hydrophobic interface of leucines

A protein crystal lattice consists of surface contact regions, where the interactions of specific groups play a key role in stabilizing the regular arrangement of the protein molecules. In an attempt to control protein incorporation in a crystal lattice, a leucine zipper-like hydrophobic interface (comprising four leucine residues) was introduced into a helical region (helix 2) of the human pancreatic ribonuclease 1 (RNase 1) that was predicted to form a suitable crystallization interface. Although crystallization of wild-type RNase 1 has not yet been reported, the RNase 1 mutant having four leucines (4L-RNase 1) was successfully crystallized under several different conditions. The crystal structures were subsequently determined by X-ray crystallography by molecular replacement using the structure of bovine RNase A. The overall structure of 4L-RNase 1 is quite similar to that of the bovine RNase A, and the introduced leucine residues formed the designed crystal interface. To characterize the role of the introduced leucine residues in crystallization of RNase 1 further, the number of leucines was reduced to three or two (3L- and 2L-RNase 1, respectively). Both mutants crystallized and a similar hydrophobic interface as in 4L-RNase 1 was observed. A related approach to engineer crystal contacts at helix 3 of RNase 1 (N4L-RNase 1) was also evaluated. N4L-RNase 1 also successfully crystallized and formed the expected hydrophobic packing interface. These results suggest that appropriate introduction of a leucine zipper-like hydrophobic interface can promote intermolecular symmetry for more efficient protein crystallization in crystal lattice engineering efforts.