Publications

Model selection is a topic of special relevance in molecular phylogenetics that affects many, if not all, stages of phylogenetic inference. Here we discuss some fundamental concepts and techniques of model selection in the context of phylogenetics. We start by reviewing different aspects of the selection of substitution models in phylogenetics from a theoretical, philosophical and practical point of view, and summarize this comparison in table format. We argue that the most commonly implemented model selection approach, the hierarchical likelihood ratio test, is not the optimal strategy for model selection in phylogenetics, and that approaches like the Akaike Information Criterion (AIC) and Bayesian methods offer important advantages. In particular, the latter two methods are able to simultaneously compare multiple nested or nonnested models, assess model selection uncertainty, and allow for the estimation of phylogenies and model parameters using all available models (model-averaged inference or multimodel inference). We also describe how the relative importance of the different parameters included in substitution models can be depicted. To illustrate some of these points, we have applied AIC-based model averaging to 37 mitochondrial DNA sequences from the subgenus Ohomopterus(genus Carabus) ground beetles described by Sota and Vogler (2001).

The authors have examined prospectively whether the combined approach of establishing tolerance intervals for the circadian variability of blood pressure (BP) as a function of gestational age, and then computing the hyperbaric index (HBI) by comparison of any patient's BP profile (obtained by ambulatory BP monitoring, ABPM) with those intervals, provides a new high sensitivity test for the early detection of pregnant women who subsequently will develop gestational hypertension or preeclampsia. The authors analyzed 503 BP series from 71 women with healthy pregnancies, and 256 series from 42 complicated pregnancies. BP was sampled for about 48 hours once every 4 weeks from the first visit to the hospital to delivery. 90% tolerance limits were computed for each trimester of gestation from 497 series previously obtained from a reference group of 189 normotensive pregnant women. The HBI was then computed for each individual BP series in the validation sample. Sensitivity of this tolerance-hyperbaric test was 90% in the first trimester, and increased up to 99% in the third trimester. The positive predictive value was above 97% in all trimesters, providing, on the average, an early identification of gestational hypertension or preeclampsia 23 weeks prior to the clinical confirmation of the disease. The approach presented here, now validated prospectively, represents a simple, reproducible, noninvasive, and high sensitivity test for the very early identification of gestational hypertension and preeclampsia.

Quantitative genetics is the study of continuously varying traits which make up the majority of biological attributes of evolutionary and commercial interest. This book provides a much-needed up-to-date, in-depth yet accessible text for the field. In lucid language, the author guides readers through the main concepts of population and quantitative genetics and their applications. It is written to be approachable to even those without a strong mathematical background, including applied examples, a glossary of key terms, and problems and solutions to support students in grasping important theoretical developments and their relevance to real-world biology. An engaging, must-have textbook for advanced undergraduate and postgraduate students. Given its applied focus, it also equips researchers in genetics, genomics, evolutionary biology, animal and plant breeding, and conservation genetics with the understanding and tools for genetic improvement, comprehension of the genetic basis of human diseases, and conservation of biological resources.

Journal Article RP-HPLC—TSP—MS of Epoxy Resins Bisphenol A Diglycidyl Ether Type Get access J. Simal Gándara, J. Simal Gándara Universidad de Santiago de Compostela, Facultad de Farmacia, Departamento de Química Analítica, Nutrición y Bromatología, Area de Nutrición y Bromatología, 15706, Santiago de Compostela (La Coruña), Spain Search for other works by this author on: Oxford Academic PubMed Google Scholar P. Pasiero Losada, P. Pasiero Losada Universidad de Santiago de Compostela, Facultad de Farmacia, Departamento de Química Analítica, Nutrición y Bromatología, Area de Nutrición y Bromatología, 15706, Santiago de Compostela (La Coruña), Spain Search for other works by this author on: Oxford Academic PubMed Google Scholar P. López Mahía, P. López Mahía Universidad de Santiago de Compostela, Facultad de Farmacia, Departamento de Química Analítica, Nutrición y Bromatología, Area de Nutrición y Bromatología, 15706, Santiago de Compostela (La Coruña), Spain Search for other works by this author on: Oxford Academic PubMed Google Scholar J. Simal Lozano, J. Simal Lozano Universidad de Santiago de Compostela, Facultad de Farmacia, Departamento de Química Analítica, Nutrición y Bromatología, Area de Nutrición y Bromatología, 15706, Santiago de Compostela (La Coruña), Spain Search for other works by this author on: Oxford Academic PubMed Google Scholar S. Paz Abuín S. Paz Abuín Gairesa, Departmento de Investigación, Lago-Valdoviño (La Coruña), Spain Search for other works by this author on: Oxford Academic PubMed Google Scholar Journal of Chromatographic Science, Volume 30, Issue 1, January 1992, Pages 11–16, https://doi.org/10.1093/chromsci/30.1.11 Published: 01 January 1992 Article history Received: 07 June 1991 Revision received: 12 November 1991 Published: 01 January 1992

Abstract Nested clade analysis (NCA) is a flexible and powerful method to study the phylogeography of species and populations, implemented in the software geodis . Despite the popularity of this method, an explicit description of the exact equations used to compute the NCA statistics has never been published. Given the importance of the methodology and increased interest in exactly how it works, here we describe the exact equations implemented in the program geodis for the calculation of these statistics.

Particle shape plays an important role in controlling the optical, magnetic, and mechanical properties of nanoparticle suspensions as well as nanocomposites. However, characterizing the size, shape, and the associated polydispersity of nanoparticles is not straightforward. Electron microscopy provides an accurate measurement of the geometric properties, but sample preparation can be laborious, and to obtain statistically relevant data many particles need to be analyzed separately. Moreover, when the particles are suspended in a fluid, it is important to measure their hydrodynamic properties, as they determine aspects such as diffusion and the rheological behavior of suspensions. Methods that evaluate the dynamics of nanoparticles such as light scattering and rheo-optical methods accurately provide these hydrodynamic properties, but do necessitate a sufficient optical response. In the present work, three different methods for characterizing nonspherical gold nanoparticles are critically compared, especially taking into account the complex optical response of these particles. The different methods are evaluated in terms of their versatility to asses size, shape, and polydispersity. Among these, the rheo-optical technique is shown to be the most reliable method to obtain hydrodynamic aspect ratio and polydispersity for nonspherical gold nanoparticles for two reasons. First, the use of the evolution of the orientation angle makes effects of polydispersity less important. Second, the use of an external flow field gives a mathematically more robust relation between particle motion and aspect ratio, especially for particles with relatively small aspect ratios.