Phylodynamic analysis of ebola virus in the 2014 sierra leone epidemic.

BACKGROUND: The Ebola virus (EBOV) epidemic in Western Africa is the largest in recorded history and control efforts have so far failed to stem the rapid growth in the number of infections. Mathematical models serve a key role in estimating epidemic growth rates and the reproduction number (R0) from surveillance data and, recently, molecular sequence data. Phylodynamic analysis of existing EBOV time-stamped sequence data may provide independent estimates of the unobserved number of infections, reveal recent epidemiological history, and provide insight into selective pressures acting upon viral genes. METHODS: We fit a series mathematical models of infectious disease dynamics to phylogenies estimated from 78 whole EBOV genomes collected from distinct patients in May and June of 2014 in Sierra Leone, and perform evolutionary analysis on these genomes combined with closely related EBOV genomes from previous outbreaks. Two analyses are conducted with values of the latent period that have been used in recent modelling efforts. We also examined the EBOV sequences for evidence of possible episodic adaptive molecular evolution during the 2014 outbreak. RESULTS: We find evidence for adaptive evolution affecting L and GP protein coding regions of the EBOV genome, which is unlikely to bias molecular clock and phylodynamic analyses. We estimate R0=2.40 (95% HPD:1.54-3.87 ) if the mean latent period is 5.3 days, and R0=3.81, (95% HPD:2.47-6.3) if the mean latent period is 12.7 days. The estimated coefficient of variation (CV) of the number of transmissions per infected host is very high, and a large proportion of infections yield no transmissions. CONCLUSIONS: Estimates of R0 are sensitive to the unknown latent infectious period which can not be reliably estimated from genetic data alone. EBOV phylogenies show significant evidence for superspreading and extreme variance in the number of transmissions per infected individual during the early epidemic in Sierra Leone

Putting a Squeeze on PubMed

How do you squeeze a 13-hour professional development class on PubMed into a 1-hour staff development workshop? This was the challenge that we, the workshop organizers, faced after completing the PubMed for Trainers class in the summer of 2013. Although the University hosted the class, there were several UVM librarians who could not attend. The issue facing us was how to effectively pass along the valuable information from the workshop to those absent colleagues. Our solution was to distill the most essential information from the class into a series of micro-presentations and deliver them using a modified Pecha Kucha format. This poster outlines that process

Vicarious and autobiographical memory: exploring associations with mood, identity and meaning-making

Vicarious memories are memories that people have in reference to events that they have not directly experienced; rather, they heard them secondhand. Previous studies of vicarious memory have predominantly focused on vicarious trauma and intergenerational narratives. There are few studies that have specifically examined non-traumatic vicarious memories beyond intergenerational narratives. The purpose of this study was to contribute new information to the memory literature regarding vicarious memory reports. University students (N = 142) completed an in-person interview in which they recalled four memories: a highly positive personal memory, a highly negative personal memory, a highly positive vicarious memory and a highly negative vicarious memory. Participants also completed questionnaires regarding identity development (Ego Identity Process Questionnaire), identity distress (Identity Distress Survey) and psychological distress (Depression Anxiety Stress Questionnaire 21). Personal and vicarious memory reports were compared and contrasted in terms of various memory qualities, memory functions, event centrality and the ways in which participants made meaning from the events. The results indicate that vicarious and personal memory reports share many phenomenological and functional properties. Although to a lesser degree than personal memories, vicarious memories do influence decision-making and problem-solving. A particularly important function of vicarious memory is enhancing intimacy. Furthermore, participants endorsed vicarious memories as a reference point for interpreting other life experiences. Young adults create meaning about themselves from highly emotional vicarious memories, and they do so in a pattern that parallels meaning-making of highly emotional personal memories. Current models of episodic memory only include events that individuals have directly experienced. The current study adds to a growing body of literature, which suggests that current models of episodic memory are too restrictive and should expand to include vicarious memory reports

CodonTest: Modeling Amino Acid Substitution Preferences in Coding Sequences

Codon models of evolution have facilitated the interpretation of selective forces operating on genomes. These models, however, assume a single rate of non-synonymous substitution irrespective of the nature of amino acids being exchanged. Recent developments have shown that models which allow for amino acid pairs to have independent rates of substitution offer improved fit over single rate models. However, these approaches have been limited by the necessity for large alignments in their estimation. An alternative approach is to assume that substitution rates between amino acid pairs can be subdivided into rate classes, dependent on the information content of the alignment. However, given the combinatorially large number of such models, an efficient model search strategy is needed. Here we develop a Genetic Algorithm (GA) method for the estimation of such models. A GA is used to assign amino acid substitution pairs to a series of rate classes, where is estimated from the alignment. Other parameters of the phylogenetic Markov model, including substitution rates, character frequencies and branch lengths are estimated using standard maximum likelihood optimization procedures. We apply the GA to empirical alignments and show improved model fit over existing models of codon evolution. Our results suggest that current models are poor approximations of protein evolution and thus gene and organism specific multi-rate models that incorporate amino acid substitution biases are preferred. We further anticipate that the clustering of amino acid substitution rates into classes will be biologically informative, such that genes with similar functions exhibit similar clustering, and hence this clustering will be useful for the evolutionary fingerprinting of genes

Multilevel Modeling of Interval-Contingent Data In Neuropsychology Research Using the \u3ci\u3eImerTest\u3c/i\u3e Package In R

Intensive longitudinal research designs are becoming more common in the field of neuropsychology. They are a powerful approach to studying development and change in naturally occurring phenomena. However, to fully capitalize on the wealth of data yielded by these designs, researchers have to understand the nature of multilevel data structures. The purpose of the present article is to describe some of the basic concepts and techniques involved in modeling multilevel data structures. In addition, this article serves as a step-by-step tutorial to demonstrate how neuropsychologists can implement basic multilevel modeling techniques with real data and the R package, lmerTest. R may be an ideal option for some empirical scientists, applied statisticians, and clinicians, because it is a free and open-source programming language for statistical computing and graphics that offers a flexible and powerful set of tools for analyzing data. All data and code described in the present article have been made publicly available

Coriolis force in Geophysics: an elementary introduction and examples

We show how Geophysics may illustrate and thus improve classical Mechanics lectures concerning the study of Coriolis force effects. We are then interested in atmospheric as well as oceanic phenomena we are familiar with, and are for that reason of pedagogical and practical interest. Our aim is to model them in a very simple way to bring out the physical phenomena that are involved.Comment: Accepted for publication in European Journal of Physic

Correcting the Bias of Empirical Frequency Parameter Estimators in Codon Models

Markov models of codon substitution are powerful inferential tools for studying biological processes such as natural selection and preferences in amino acid substitution. The equilibrium character distributions of these models are almost always estimated using nucleotide frequencies observed in a sequence alignment, primarily as a matter of historical convention. In this note, we demonstrate that a popular class of such estimators are biased, and that this bias has an adverse effect on goodness of fit and estimates of substitution rates. We propose a “corrected” empirical estimator that begins with observed nucleotide counts, but accounts for the nucleotide composition of stop codons. We show via simulation that the corrected estimates outperform the de facto standard estimates not just by providing better estimates of the frequencies themselves, but also by leading to improved estimation of other parameters in the evolutionary models. On a curated collection of sequence alignments, our estimators show a significant improvement in goodness of fit compared to the approach. Maximum likelihood estimation of the frequency parameters appears to be warranted in many cases, albeit at a greater computational cost. Our results demonstrate that there is little justification, either statistical or computational, for continued use of the -style estimators