Publication trends of shared decision making in 15 high impact medical journals: a full-text review with bibliometric analysis.

BACKGROUND: Shared Decision Making (SDM) is increasingly advocated as a model for medical decision making. However, there is still low use of SDM in clinical practice. High impact factor journals might represent an efficient way for its dissemination. We aimed to identify and characterize publication trends of SDM in 15 high impact medical journals. METHODS: We selected the 15 general and internal medicine journals with the highest impact factor publishing original articles, letters and editorials. We retrieved publications from 1996 to 2011 through the full-text search function on each journal website and abstracted bibliometric data. We included publications of any type containing the phrase "shared decision making" or five other variants in their abstract or full text. These were referred to as SDM publications. A polynomial Poisson regression model with logarithmic link function was used to assess the evolution across the period of the number of SDM publications according to publication characteristics. RESULTS: We identified 1285 SDM publications out of 229,179 publications in 15 journals from 1996 to 2011. The absolute number of SDM publications by journal ranged from 2 to 273 over 16 years. SDM publications increased both in absolute and relative numbers per year, from 46 (0.32% relative to all publications from the 15 journals) in 1996 to 165 (1.17%) in 2011. This growth was exponential (P < 0.01). We found fewer research publications (465, 36.2% of all SDM publications) than non-research publications, which included non-systematic reviews, letters, and editorials. The increase of research publications across time was linear. Full-text search retrieved ten times more SDM publications than a similar PubMed search (1285 vs. 119 respectively). CONCLUSION: This review in full-text showed that SDM publications increased exponentially in major medical journals from 1996 to 2011. This growth might reflect an increased dissemination of the SDM concept to the medical community.

Time-series regression models to study the short-term effects of environmental factors on health

Time series regression models are especially suitable in epidemiology for evaluating short-term effects of time-varying exposures on health. The problem is that potential for confounding in time series regression is very high. Thus, it is important that trend and seasonality are properly accounted for. Our paper reviews the statistical models commonly used in time-series regression methods, specially allowing for serial correlation, make them potentially useful for selected epidemiological purposes. In particular, we discuss the use of time-series regression for counts using a wide range Generalised Linear Models as well as Generalised Additive Models. In addition, recently critical points in using statistical software for GAM were stressed, and reanalyses of time series data on air pollution and health were performed in order to update already published. Applications are offered through an example on the relationship between asthma emergency admissions and photochemical air pollutants

Evolutionary implications of a high selfing rate in the freshwater snail Lymnaea truncatula.

Self-compatible hermaphroditic organisms that mix self-fertilization and outcrossing are of great interest for investigating the evolution of mating systems. We investigate the evolution of selfing in Lymnaea truncatula, a self-compatible hermaphroditic freshwater snail. We first analyze the consequences of selfing in terms of genetic variability within and among populations and then investigate how these consequences along with the species ecology (harshness of the habitat and parasitism) might govern the evolution of selfing. Snails from 13 localities (classified as temporary or permanent depending on their water availability) were sampled in western Switzerland and genotyped for seven microsatellite loci. F(IS) (estimated on adults) and progeny array analyses (on hatchlings) provided similar selfing rate estimates of 80%. Populations presented a low polymorphism and were highly differentiated (F(ST) = 0.58). Although the reproductive assurance hypothesis would predict higher selfing rate in temporary populations, no difference in selfing level was observed between temporary and permanent populations. However, allelic richness and gene diversity declined in temporary habitats, presumably reflecting drift. Infection levels varied but were not simply related to either estimated population selfing rate or to differences in heterozygosity. These findings and the similar selfing rates estimated for hatchlings and adults suggest that within-population inbreeding depression is low in L. truncatula.

Robust regression in biological assay: application to the evaluation of alternative experimental techniques.

Robust Huber type regression and testing of linear hypotheses are adapted to statistical analysis of parallel line and slope ratio assays. They are applied in the evaluation of results of several experiments carried out in order to compare and validate alternatives to animal experimentation based on embryo and cell cultures. Computational procedures necessary for the application of robust methods of analysis used the conversational statistical package ROBSYS. Special commands for the analysis of parallel line and slope ratio assays have been added to ROBSYS.

Evolutionary histories of expanded peptidase families in Schistosoma mansoni

Schistosoma mansoni is one of the three main causative agents of human schistosomiasis, a major health problem with a vast socio-economic impact. Recent advances in the proteomic analysis of schistosomes have revealed that peptidases are the main virulence factors involved in the pathogenesis of this disease. In this context, evolutionary studies can be applied to identify peptidase families that have been expanded in genomes over time in response to different selection pressures. Using a phylogenomic approach, we searched for expanded endopeptidase families in the S. mansoni predicted proteome with the aim of contributing to the knowledge of such enzymes as potential therapeutic targets. We found three endopeptidase families that comprise leishmanolysins (metallopeptidase M8 family), cercarial elastases (serine peptidase S1 family) and cathepsin D proteins (aspartic peptidase A1 family). Our results suggest that the Schistosoma members of these families originated from successive gene duplication events in the parasite lineage after its diversification from other metazoans. Overall, critical residues are conserved among the duplicated genes/proteins. Furthermore, each protein family displays a distinct evolutionary history. Altogether, this work provides an evolutionary view of three S. mansoni peptidase families, which allows for a deeper understanding of the genomic complexity and lineage-specific adaptations potentially related to the parasitic lifestyle.

Pfcrt haplotypes and the evolutionary history of chloroquine-resistant Plasmodium falciparum

Mutations in the Pfcrt gene that change the resulting amino acids and form different haplotypes are common and correlate with the prevalence of chloroquine resistant (CQR) field isolates of the malaria parasite, Plasmodium falciparum. This correlation provides opportunities to infer the global evolutionary history of CQ resistance by analysing CQR Pfcrt haplotype data. We collated data on the Pfcrt haplotypes from different global studies and performed evolutionary genetic analysis to present comprehensive and comparative information on the global distribution of five major CQR-Pfcrt haplotypes and evolutionary inter-relationships among 38 different countries. Using the haplotype diversity data, inter-continental genetic differentiation was also ascertained.

Plastic and evolutionary responses of cell size and number to larval malnutrition in Drosophila melanogaster.

Both development and evolution under chronic malnutrition lead to reduced adult size in Drosophila. We studied the contribution of changes in size vs. number of epidermal cells to plastic and evolutionary reduction of wing size in response to poor larval food. We used flies from six populations selected for tolerance to larval malnutrition and from six unselected control populations, raised either under standard conditions or under larval malnutrition. In the control populations, phenotypic plasticity of wing size was mediated by both cell size and cell number. In contrast, evolutionary change in wing size, which was only observed as a correlated response expressed on standard food, was mediated entirely by reduction in cell number. Plasticity of cell number had been lost in the selected populations, and cell number did not differ between the sexes despite males having smaller wings. Results of this and other experimental evolution studies are consistent with the hypothesis that alleles which increase body size through prolonged growth affect wing size mostly via cell number, whereas alleles which increase size through higher growth rate do so via cell size.

Chromosomal divergence and evolutionary inferences in Rhodniini based on the chromosomal location of ribosomal genes

In this study, we used fluorescence in situ hybridisation to determine the chromosomal location of 45S rDNA clusters in 10 species of the tribe Rhodniini (Hemiptera: Reduviidae: Triatominae). The results showed striking inter and intraspecific variability, with the location of the rDNA clusters restricted to sex chromosomes with two patterns: either on one (X chromosome) or both sex chromosomes (X and Y chromosomes). This variation occurs within a genus that has an unchanging diploid chromosome number (2n = 22, including 20 autosomes and 2 sex chromosomes) and a similar chromosome size and genomic DNA content, reflecting a genome dynamic not revealed by these chromosome traits. The rDNA variation in closely related species and the intraspecific polymorphism in Rhodnius ecuadoriensis suggested that the chromosomal position of rDNA clusters might be a useful marker to identify recently diverged species or populations. We discuss the ancestral position of ribosomal genes in the tribe Rhodniini and the possible mechanisms involved in the variation of the rDNA clusters, including the loss of rDNA loci on the Y chromosome, transposition and ectopic pairing. The last two processes involve chromosomal exchanges between both sex chromosomes, in contrast to the widely accepted idea that the achiasmatic sex chromosomes of Heteroptera do not interchange sequences.

Uncertainty Quantification Of A Semi-Supervised Support Vector Regression Reservoir Model

Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. Recent advances in machine learning offer a novel approach to model spatial distribution of petrophysical properties in complex reservoirs alternative to geostatistics. The approach is based of semisupervised learning, which handles both ?labelled? observed data and ?unlabelled? data, which have no measured value but describe prior knowledge and other relevant data in forms of manifolds in the input space where the modelled property is continuous. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic geological features and describe stochastic variability and non-uniqueness of spatial properties. On the other hand, it is able to capture and preserve key spatial dependencies such as connectivity of high permeability geo-bodies, which is often difficult in contemporary petroleum reservoir studies. Semi-supervised SVR as a data driven algorithm is designed to integrate various kind of conditioning information and learn dependences from it. The semi-supervised SVR model is able to balance signal/noise levels and control the prior belief in available data. In this work, stochastic semi-supervised SVR geomodel is integrated into Bayesian framework to quantify uncertainty of reservoir production with multiple models fitted to past dynamic observations (production history). Multiple history matched models are obtained using stochastic sampling and/or MCMC-based inference algorithms, which evaluate posterior probability distribution. Uncertainty of the model is described by posterior probability of the model parameters that represent key geological properties: spatial correlation size, continuity strength, smoothness/variability of spatial property distribution. The developed approach is illustrated with a fluvial reservoir case. The resulting probabilistic production forecasts are described by uncertainty envelopes. The paper compares the performance of the models with different combinations of unknown parameters and discusses sensitivity issues.

Evolutionary simulations to detect functional lineage-specific genes.

MOTIVATION: Supporting the functionality of recent duplicate gene copies is usually difficult, owing to high sequence similarity between duplicate counterparts and shallow phylogenies, which hamper both the statistical and experimental inference. RESULTS: We developed an integrated evolutionary approach to identify functional duplicate gene copies and other lineage-specific genes. By repeatedly simulating neutral evolution, our method estimates the probability that an ORF was selectively conserved and is therefore likely to represent a bona fide coding region. In parallel, our method tests whether the accumulation of non-synonymous substitutions reveals signatures of selective constraint. We show that our approach has high power to identify functional lineage-specific genes using simulated and real data. For example, a coding region of average length (approximately 1400 bp), restricted to hominoids, can be predicted to be functional in approximately 94-100% of cases. Notably, the method may support functionality for instances where classical selection tests based on the ratio of non-synonymous to synonymous substitutions fail to reveal signatures of selection. Our method is available as an automated tool, ReEVOLVER, which will also be useful to systematically detect functional lineage-specific genes of closely related species on a large scale. AVAILABILITY: ReEVOLVER is available at http://www.unil.ch/cig/page7858.html.

When population and evolutionary genetics met behaviour

In this review, we analyse the impact of a population and evolutionary genetics approach on the study of insect behaviour. Our attention is focused on the model organism Drosophila melanogaster and several other insect species. In particular, we explore the relationship between rhythmic behaviours and the molecular evolution of clock and ion channel genes.