A New Deep Learning Calibration Method Enhances Genome-Based Prediction of Continuous Crop Traits

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Bayesian multitrait kernel methods improve multienvironment genome-based prediction

When multitrait data are available, the preferred models are those that are able to account for correlations between phenotypic traits because when the degree of correlation is moderate or large, this increases the genomic prediction accuracy. For this reason, in this article, we explore Bayesian multitrait kernel methods for genomic prediction and we illustrate the power of these models with three-real datasets. The kernels under study were the linear, Gaussian, polynomial, and sigmoid kernels; they were compared with the conventional Ridge regression and GBLUP multitrait models. The results show that, in general, the Gaussian kernel method outperformed conventional Bayesian Ridge and GBLUP multitrait linear models by 2.2–17.45% (datasets 1–3) in terms of prediction performance based on the mean square error of prediction. This improvement in terms of prediction performance of the Bayesian multitrait kernel method can be attributed to the fact that the proposed model is able to capture nonlinear patterns more efficiently than linear multitrait models. However, not all kernels perform well in the datasets used for evaluation, which is why more than one kernel should be evaluated to be able to choose the best kernel

Sample Size under Inverse Negative Binomial Group Testing for Accuracy in Parameter Estimation

Background:The group testing method has been proposed for the detection and estimation of genetically modified plants (adventitious presence of unwanted transgenic plants, AP). For binary response variables (presence or absence), group testing is efficient when the prevalence is low, so that estimation, detection, and sample size methods have been developed under the binomial model. However, when the event is rare (low prevalence Methodology/Principal Findings: This research proposes three sample size procedures (two computational and one analytic) for estimating prevalence using group testing under inverse (negative) binomial sampling. These methods provide the required number of positive pools (rm), given a pool size (k), for estimating the proportion of AP plants using the Dorfman model and inverse (negative) binomial sampling. We give real and simulated examples to show how to apply these methods and the proposed sample-size formula. The Monte Carlo method was used to study the coverage and level of assurance achieved by the proposed sample sizes. An R program to create other scenarios is given in Appendix S2. Conclusions: The three methods ensure precision in the estimated proportion of AP because they guarantee that the width (W) of the confidence interval (CI) will be equal to, or narrower than, the desired width (v), with a probability of c. With the Monte Carlo study we found that the computational Wald procedure (method 2) produces the more precise sample size (with coverage and assurance levels very close to nominal values) and that the samples size based on the Clopper-Pearson CI (method 1) is conservative (overestimates the sample size); the analytic Wald sample size method we developed (method 3) sometimes underestimated the optimum number of pools

Stabilization of high-order solutions of the cubic Nonlinear Schrodinger Equation

In this paper we consider the stabilization of non-fundamental unstable stationary solutions of the cubic nonlinear Schrodinger equation. Specifically we study the stabilization of radially symmetric solutions with nodes and asymmetric complex stationary solutions. For the first ones we find partial stabilization similar to that recently found for vortex solutions while for the later ones stabilization does not seem possible

Genome and Environment Based Prediction Models and Methods of Complex Traits Incorporating Genotype × Environment Interaction

Genomic-enabled prediction models are of paramount importance for the successful implementation of genomic selection (GS) based on breeding values. As opposed to animal breeding, plant breeding includes extensive multienvironment and multiyear field trial data. Hence, genomic-enabled prediction models should include genotype × environment (G × E) interaction, which most of the time increases the prediction performance when the response of lines are different from environment to environment. In this chapter, we describe a historical timeline since 2012 related to advances of the GS models that take into account G × E interaction. We describe theoretical and practical aspects of those GS models, including the gains in prediction performance when including G × E structures for both complex continuous and categorical scale traits. Then, we detailed and explained the main G × E genomic prediction models for complex traits measured in continuous and noncontinuous (categorical) scale. Related to G × E interaction models this review also examine the analyses of the information generated with high-throughput phenotype data (phenomic) and the joint analyses of multitrait and multienvironment field trial data that is also employed in the general assessment of multitrait G × E interaction. The inclusion of nongenomic data in increasing the accuracy and biological reliability of the G × E approach is also outlined. We show the recent advances in large-scale envirotyping (enviromics), and how the use of mechanistic computational modeling can derive the crop growth and development aspects useful for predicting phenotypes and explaining G × E

SÍNDROMES EMPÍRICOS EN UNA POBLACIÓN ADOLESCENTE, EVALUADOS MEDIANTE EL YSR

The study of adolescent populations, considered from an empirical and epidemiologic perspective, responds to the need for psychopathological profiles and for prosocial aspects, which may be useful in the policy formulation process in every field, especially when the country’s resources are scarce and the sector’s demands are increasing. This work focuses on the study of the psychopathological and sociodemographic characteristics, as well as on the study of competencies, in an adolescent population of high school students in an educational institution of the city of Montevideo, Uruguay. The specific objective developed on this paper, refers to the adjustment of Youth Self-Report (Achenbach et al, 1978) to a uruguayan youth population, analyzing the scale’s factorial structure and contrasting these findings with those found in other countries. Thus, our findings are compared with those originated by Lopez Soler in Spain (1998) as well as with those described by the scale’s original author. The taxonomic structure obtained comprises the following Syndromes: Depression-Anxiety, Somatic Complaints; Dissocial; Opposition-Impulsivity; Alteration in Thought Processes; Withdrawal-Avoidance, Immaturity; Fear; Social Problems and also, the Prosocial Syndrome. The results show significant coincidences with the studies of reference.El estudio de poblaciones adolescentes desde un encare empírico y de corte epidemiológico, responde a la necesidad de contar con perfiles psicopatológicos y también de aspectos prosociales, que puedan ser útiles para la formulación de políticas en todos los ámbitos, máxime cuando los recursos de los países son escasos y las demandas en el sector van en aumento. Este trabajo se centra en el estudio de las características psicopatológicas, sociodemográficas y competencias, en una población adolescente de una institución educativa de nivel secundario de la ciudad de Montevideo, Uruguay. El objetivo específico desarrollado en esta comunicación, refiere al ajuste del Autoinforme para Jóvenes (Achenbach y colaboradores, 1978 y ss.) a población juvenil uruguaya; analizando la estructura factorial del mismo y contrastando estos hallazgos con los encontrados en otros países. Asi se comparan los hallazgos con los encontrados en estudios de López Soler en España (1998) y los del propio autor. La estructura taxonómica obtenida contiene a los Síndromes de: Depresión-Ansiedad, Quejas Somáticas; Disocial; Oposición-Impulsividad; Alteración del Pensamiento; Retraimiento-Evitación, Inmadurez; Temor; Problemas Sociales y también al Síndrome Prosocial. Los resultados muestran coincidencias importantes con los trabajos de referencia.

2007 : el año del Sol

Sumario : La estrella imprescindible.-- Pero, ¿cómo medimos el campo magnético?.-- El interior de las manchas solares.-- CIENCIA: PILARES E INCERTIDUMBRES.-- DECONSTRUCCIÓN Y otros ENSAYOS : El satélite que indagará en el campo magnético solar.-- ACTUALIDAD.-- ENTRE BASTIDORES.-- HISTORIAS DE ASTRONOMÍA : Una predicción, un cristal, un derrumbe y un incendio.-- HOMENAJE A LUCAS LARA.-- ACTIVIDADES IAA.-- El increíble y asombroso viaje de Fotón.Esta revista se publica con la ayuda de la Acción Complementaria CCT005-06-00178 del Programa Nacional de Fomento de la Cultura Científica y Tecnológica.N

Revisión bioestratigráfica de las pizarras del Ordovícico Medio en el noroeste de España (zonas Cantábrica, Asturoccidental-leonesa y Centroibérica septentrional)

A complete review of more than one hundred Middle Ordovician fossil localities, distributed within the north western part of the Hesperian Massif, shows that the sedimentation of the dark shales (Luarca Fo rmation and equivalents) that overlie Arenig quartzites with Cruziana (the 'Armorican Quartzite' facies) was not as uniform as it has been supposed for the whole NW Spain. These shales were mainly deposited during the Oretanian in the West Asturian-Leonese Zone and in nort h e rn Central-Iberian Zone (Domain of the Ollo de Sapo Antiform). In these zones, the top of the unit is close to the Oretanian/Dobrotivian boundary, without any fossils with proved Dobrotivian age. In the Cantabrian Zone, clay sedimentation started in the latest Oretanian and continued during the Dobrotivian. Several local or regional stratigraphic gaps are proposed and characterized for the whole study area. In addition, the most recent paleog e ographical reconstructions proposed are discussed, in accordance with new paleoecological and paleobiog e ographical data. These data indicate that sedimentation took place in open shelf areas, relative ly deeper than in the southern Central Iberian shelf, and with trough areas where some mesopelagic elements are recorded. We identified a total of 97 different fossil taxa (67 from Oretanian rocks and 45 from Dobrotivian rocks), remarkable among which are the first known appearance of certain trilobites and ostracodes, the latest record of other taxa, and also the presence of some taxa in common with Avalonia and Baltica, that were previously unknown from any area of SW Europe

CGIAR modeling approaches for resource-constrained scenarios: I. Accelerating crop breeding for a changing climate.

Crop improvement efforts aiming at increasing crop production (quantity, quality) and adapting to climate change have been subject of active research over the past years. But, the question remains 'to what extent can breeding gains be achieved under a changing climate, at a pace sufficient to usefully contribute to climate adaptation, mitigation and food security?'. Here, we address this question by critically reviewing how model-based approaches can be used to assist breeding activities, with particular focus on all CGIAR (formerly the Consultative Group on International Agricultural Research but now known simply as CGIAR) breeding programs. Crop modeling can underpin breeding efforts in many different ways, including assessing genotypic adaptability and stability, characterizing and identifying target breeding environments, identifying tradeoffs among traits for such environments, and making predictions of the likely breeding value of the genotypes. Crop modeling science within the CGIAR has contributed to all of these. However, much progress remains to be done if modeling is to effectively contribute to more targeted and impactful breeding programs under changing climates. In a period in which CGIAR breeding programs are undergoing a major modernization process, crop modelers will need to be part of crop improvement teams, with a common understanding of breeding pipelines and model capabilities and limitations, and common data standards and protocols, to ensure they follow and deliver according to clearly defined breeding products. This will, in turn, enable more rapid and better-targeted crop modeling activities, thus directly contributing to accelerated and more impactful breeding efforts.Online Version of Record before inclusion in an issue

Cost-effectiveness of midostaurin in the treatment of acute myeloid leukemia with the FLT3 mutation in Spain

The addition of midostaurin to standard chemotherapy (cytarabine and daunorubicin) has shown significant improvements in the survival of patients with acute myeloid leukemia with the FLT3 mutation (FLT3-AML). The objective of this study was to determine whether this intervention would be cost-effective in Spain. A partitioned survival model with five health states was developed (diagnosis and induction, complete remission, no complete remission, transplantation and death). A lifetime time horizon and the Spanish National Health System perspective were adopted. During the first three years, permanence in the different health states was determined according to the results of the RATIFY study. In successive years, the death rates of the Spanish population adjusted by a factor to reflect long-term disease-related mortality were used. Utilities were obtained from the literature. Pharmacological costs (first and second line) and the costs of other health resources (hospitalizations, visits and tests) were included. The robustness of the model was evaluated by deterministic and probabilistic sensitivity analyses. The addition of midostaurin resulted in 1.46 life years gained (LYG) and 1.23 quality-adjusted life years (QALY) gained and implied an additional cost of € 47,955, resulting in an incremental cost-effectiveness ratio (ICER) of € 32,854/LYG and an incremental cost-utility ratio of € 38,985/QALY. In the univariate sensitivity analysis, the threshold of € 50,000/QALY was not exceeded in any case; taking into consideration potential discounts of 20-40% in the PVL of midostaurin the ICER would be below € 30,000/QALY, a commonly accepted threshold in Spain. In the probabilistic analysis, when the threshold was € 50,000/QALY, midostaurin was cost-effective in 82.3% of simulations. According to our modeling, midostaurin, in combination with standard chemotherapy, could be an efficient alternative for the treatment of FLT3-AML in Spain. © 2019 Arenaza et al