Inequal distribution of nursing personnel: a subnational analysis of the distribution of nurses across 58 countries.

Background: Nursing personnel are critical for enabling access to health service in primary health care. However, the State of the World's Nursing 2020 report showed important inequalities in nurse availability between countries.

Methods: The purpose of this study/analysis was to describe the differences in nurse-to-population density in 58 countries from six regional areas and the relationship between differences in access to nurses and other indicators of health equity.

Efforts needed for preventing breast and colorectal cancer through changes in dietary patterns.

Background: Prospective cohort studies on diet and cancer report risk associations as hazard ratios. But hazard ratios do not inform on the number of people who need to alter their dietary behaviours for preventing cancer. The objective of this study is to estimate the number of people that need to alter their diet for preventing one additional case of female breast or colorectal cancer.

Latitudinal variation in climate-associated genes imperils range edge populations.

The ecological impacts of increasing global temperatures are evident in most ecosystems on Earth, but our understanding of how climatic variation influences natural selection and adaptive resilience across latitudes remains largely unknown. Latitudinal gradients allow testing general ecosystem-level theories relevant to climatic adaptation. We assessed differences in adaptive diversity of populations along a latitudinal region spanning highly variable temperate to subtropical climates.

Dose-response analysis of toxicological and pharmacological mixtures with the model deviation ratio method: Problems and solutions.

Risk assessment for mixtures of chemicals requires to investigate the magnitude of their potential adverse effects on living organisms. This is usually done by assessing how experimental toxicological mixture data depart from the model of Loewe additivity. Several recent scientific studies propose to perform this task using an ad hoc method known as model deviation ratio (MDR) method.

Investigating combined toxicity of binary mixtures in bees: Meta-analysis of laboratory tests, modelling, mechanistic basis and implications for risk assessment.

Bees are exposed to a wide range of multiple chemicals "chemical mixtures" from anthropogenic (e.g. plant protection products or veterinary products) or natural origin (e.

Serological monitoring on milk and serum samples in a BVD eradication program: A field study in Belgium showing antibody ELISA performances and epidemiological aspects.

In a cross-sectional field study involving 51 cattle herds in Belgium, 3159 serum samples and 557 individual milk samples were collected and tested by four different commercial antibody (Ab) ELISAs on serum and two Ab ELISAs on milk. A virus neutralization test (VNT) was performed on serum samples with discording ELISA results and on all samples from non-vaccinating herds. An epidemiological survey was carried out in the same herds to collect information about herd characteristics, management practices, BVD vaccination and BVD infection status.

Inverse effects of the gas feed positioning on sonochemistry and sonoluminescence.

Purging of solutions to enhance sonochemical reactions is a common practice. A fundamental study combining sonoluminescence spectroscopy and sonochemical activity is adopted to study the effects of continuous Ar gas flow in the solution and of the position of the gas inlet tube on high-frequency sonolysis of aqueous solutions. It has been observed that neither sonochemical activity nor sonoluminescence intensity is controlled by the gas solubility only.

Guidance on dermal absorption.

This guidance on the assessment of dermal absorption has been developed to assist notifiers, users of test facilities and Member State authorities on critical aspects related to the setting of dermal absorption values to be used in risk assessments of active substances in Plant Protection Products (PPPs). It is based on the 'scientific opinion on the science behind the revision of the guidance document on dermal absorption' issued in 2011 by the EFSA Panel on Plant Protection Products and their Residues (PPR). The guidance refers to the EFSA PPR opinion in many instances.

Accurate continuous geographic assignment from low- to high-density SNP data.

Motivation: Large-scale genotype datasets can help track the dispersal patterns of epidemiological outbreaks and predict the geographic origins of individuals. Such genetically-based geographic assignments also show a range of possible applications in forensics for profiling both victims and criminals, and in wildlife management, where poaching hotspot areas can be located. They, however, require fast and accurate statistical methods to handle the growing amount of genetic information made available from genotype arrays and next-generation sequencing technologies.

A unifying model for the analysis of phenotypic, genetic, and geographic data.

Recognition of evolutionary units (species, populations) requires integrating several kinds of data, such as genetic or phenotypic markers or spatial information in order to get a comprehensive view concerning the differentiation of the units. We propose a statistical model with a double original advantage: (i) it incorporates information about the spatial distribution of the samples, with the aim to increase inference power and to relate more explicitly observed patterns to geography and (ii) it allows one to analyze genetic and phenotypic data within a unified model and inference framework, thus opening the way to robust comparisons between markers and possibly combined analyses. We show from simulated data as well as real data that our method estimates parameters accurately and is an improvement over alternative approaches in many situations.

Estimating the location and shape of hybrid zones.

We propose a new model to make use of georeferenced genetic data for inferring the location and shape of a hybrid zone. The model output includes the posterior distribution of a parameter that quantifies the width of the hybrid zone. The model proposed is implemented in the GUI and command-line versions of the Geneland program versions ≥ 3.

Using AFLP markers and the Geneland program for the inference of population genetic structure.

The use of dominant markers such as amplified fragment length polymorphism (AFLP) for population genetics analyses is often impeded by the lack of appropriate computer programs and rarely motivated by objective considerations. The point of the present note is twofold: (i) we describe how the computer program Geneland designed to infer population structure has been adapted to deal with dominant markers; and (ii) we use Geneland for numerical comparison of dominant and codominant markers to perform clustering. AFLP markers lead to less accurate results than bi-allelic codominant markers such as single nucleotide polymorphisms (SNP) markers but this difference becomes negligible for data sets of common size (number of individuals n≥100, number of markers L≥200).

Identification of adipocyte genes regulated by caloric intake.

Context: Changes in energy intake have marked and rapid effects on metabolic functions, and some of these effects may be due to changes in adipocyte gene expression that precede alterations in body weight.

Objective: The aim of the study was to identify adipocyte genes regulated by changes in caloric intake independent of alterations in body weight.

Research Design And Methods: Obese subjects given a very low-caloric diet followed by gradual reintroduction of ordinary food and healthy subjects subjected to overfeeding were investigated.

Statistical methods in spatial genetics.

The joint analysis of spatial and genetic data is rapidly becoming the norm in population genetics. More and more studies explicitly describe and quantify the spatial organization of genetic variation and try to relate it to underlying ecological processes. As it has become increasingly difficult to keep abreast with the latest methodological developments, we review the statistical toolbox available to analyse population genetic data in a spatially explicit framework.

On the inference of spatial structure from population genetics data.

Motivation: In a series of recent papers, Tess, a computer program based on the concept of hidden Markov random field, has been proposed to infer the number and locations of panmictic population units from the genotypes and spatial locations of these individuals. The method seems to be of broad appeal as it is conceptually much simpler than other competing methods and it has been reported by its authors to be fast and accurate. However, this methodology is not grounded in a formal statistical inference method and seems to rely to a large extent on arbitrary choices regarding the parameters used.

A computer program to simulate multilocus genotype data with spatially autocorrelated allele frequencies.

Many models for inference of population genetic parameters are based on the assumption that the data set at hand consists of groups displaying within-group Hardy-Weinberg equilibrium at individual loci and linkage equilibrium between loci. This assumption is commonly violated by the presence of within-group spatial structure arising from nonrandom mating of individuals due to isolation by distance (IBD). This paper proposes a model and simulation method implemented in a computer program to flexibly simulate data displaying such patterns.

Correcting for ascertainment bias in the inference of population structure.

Background: The ascertainment process of molecular markers amounts to disregard loci carrying alleles with low frequencies. This can result in strong biases in inferences under population genetics models if not properly taken into account by the inference algorithm. Attempting to model this censoring process in view of making inference of population structure (i.

Population substructure in Finland and Sweden revealed by the use of spatial coordinates and a small number of unlinked autosomal SNPs.

Background: Despite several thousands of years of close contacts, there are genetic differences between the neighbouring countries of Finland and Sweden. Within Finland, signs of an east-west duality have been observed, whereas the population structure within Sweden has been suggested to be more subtle. With a fine-scale substructure like this, inferring the cluster membership of individuals requires a large number of markers.

Inference of structure in subdivided populations at low levels of genetic differentiation--the correlated allele frequencies model revisited.

Motivation: This article considers the problem of estimating population genetic subdivision from multilocus genotype data. A model is considered to make use of genotypes and possibly of spatial coordinates of sampled individuals. A particular attention is paid to the case of low genetic differentiation with the help of a previously described Bayesian clustering model where allele frequencies are assumed to be a priori correlated.

Analysing georeferenced population genetics data with Geneland: a new algorithm to deal with null alleles and a friendly graphical user interface.

Unlabelled: We introduce a new algorithm to account for the presence of null alleles in inferences of populations clusters from individual multilocus genetic data. We show by simulations that the presence of null alleles can affect the accuracy of inferences if not properly accounted for and that our algorithm improve signficantly their accuracy.

Availability: This new algorithm is implemented in the program Geneland.

Discrimination and scoring using small sets of genes for two-sample microarray data.

Comparison of gene expression for two groups of individuals form an important subclass of microarray experiments. We study multivariate procedures, in particular use of Hotelling's T2 for discrimination between the groups with a special emphasis on methods based on few genes only. We apply the methods to data from an experiment with a group of atopic dermatitis patients compared with a control group.

Bayesian clustering using hidden Markov random fields in spatial population genetics.

We introduce a new Bayesian clustering algorithm for studying population structure using individually geo-referenced multilocus data sets. The algorithm is based on the concept of hidden Markov random field, which models the spatial dependencies at the cluster membership level. We argue that (i) a Markov chain Monte Carlo procedure can implement the algorithm efficiently, (ii) it can detect significant geographical discontinuities in allele frequencies and regulate the number of clusters, (iii) it can check whether the clusters obtained without the use of spatial priors are robust to the hypothesis of discontinuous geographical variation in allele frequencies, and (iv) it can reduce the number of loci required to obtain accurate assignments.

A spatial statistical model for landscape genetics.

Landscape genetics is a new discipline that aims to provide information on how landscape and environmental features influence population genetic structure. The first key step of landscape genetics is the spatial detection and location of genetic discontinuities between populations. However, efficient methods for achieving this task are lacking.