Use of SMS texts for facilitating access to online alcohol interventions: a feasibility study

A41 Use of SMS texts for facilitating access to online alcohol interventions: a feasibility study In: Addiction Science & Clinical Practice 2017, 12(Suppl 1): A4

An observational study exploring amplitude-integrated electroencephalogram and Spectral Edge Frequency during paediatric anaesthesia

Processed electroencephalography is used in adults to guide anaesthesia, but the algorithms used may not apply to infants. Knowledge of infants' electroencephalogram (EEG) responses to anaesthetics is fragmentary. An earlier pilot study suggested amplitude-integrated EEG (aEEG) may be a useful measure of anaesthetic effect. The aim of this study was to determine how aEEG changes between awake and anaesthetised children of varying ages and to compare the response to that seen with Spectral Edge Frequency 90% (SEF90). A prospective observational study of children receiving a general anaesthetic was conducted. Anaesthetic regimen remained at the discretion of the treating anaesthetist. EEG data were collected using the BrainZ ReBrim(TM) monitor using forehead and biparietal montages. SEF90 and aEEG were compared across age groups, EEG montage and between awake and anaesthetised states. A total of 178 children (aged 24 days to 14 years) were recruited. All aEEGs were greater during anaesthesia compared to when awake and this difference varied with age. Only children older than two years showed lower SEF90 while anaesthetised compared to when awake. SEF90 from children younger than six months was higher during anaesthesia compared to when awake. Analysis of parietal and forehead EEG montages revealed age-related differences. These findings suggest that SEF90 and aEEG can discriminate between awake and anaesthetised states in older children. In younger children aEEG changes are less pronounced and SEF90 either cannot discriminate between states or responds paradoxically. The aEEG may be marginally better than other EEG parameters in measuring anaesthetic depth in children

The BaBar detector: Upgrades, operation and performance

Contains fulltext : 121729.pdf (preprint version ) (Open Access

Estimation of effective population sizes from data on genetic markers

The effective population size (N(e)) is an important parameter in ecology, evolutionary biology and conservation biology. It is, however, notoriously difficult to estimate, mainly because of the highly stochastic nature of the processes of inbreeding and genetic drift for which N(e) is usually defined and measured, and because of the many factors (such as time and spatial scales, systematic forces) confounding such processes. Many methods have been developed in the past three decades to estimate the current, past and ancient effective population sizes using different information extracted from some genetic markers in a sample of individuals. This paper reviews the methodologies proposed for estimating N(e) from genetic data using information on heterozygosity excess, linkage disequilibrium, temporal changes in allele frequency, and pattern and amount of genetic variation within and between populations. For each methodology, I describe mainly the logic and genetic model on which it is based, the data required and information used, the interpretation of the estimate obtained, some results from applications to simulated or empirical datasets and future developments that are needed