Latent protein trees

Unbiased, label-free proteomics is becoming a powerful technique for measuring protein expression in almost any biological sample. The output of these measurements after preprocessing is a collection of features and their associated intensities for each sample. Subsets of features within the data are from the same peptide, subsets of peptides are from the same protein, and subsets of proteins are in the same biological pathways, therefore, there is the potential for very complex and informative correlational structure inherent in these data. Recent attempts to utilize this data often focus on the identification of single features that are associated with a particular phenotype that is relevant to the experiment. However, to date, there have been no published approaches that directly model what we know to be multiple different levels of correlation structure. Here we present a hierarchical Bayesian model which is specifically designed to model such correlation structure in unbiased, label-free proteomics. This model utilizes partial identification information from peptide sequencing and database lookup as well as the observed correlation in the data to appropriately compress features into latent proteins and to estimate their correlation structure. We demonstrate the effectiveness of the model using artificial/benchmark data and in the context of a series of proteomics measurements of blood plasma from a collection of volunteers who were infected with two different strains of viral influenza.Comment: Published in at http://dx.doi.org/10.1214/13-AOAS639 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

Effect of Al2O3 or MgO on liquidus line in the FeOX corner of FeOX-SiO2-CaO system at 1523 K under various oxygen partial pressures

The liquidus line in the FeO corner of FeO SiO - CaO system and the effect by adding Al O or MgO to this plain system on the liquidus line were experimentally investigated at 1523 K in a wide range of oxygen partial pressure between about 10 and about 10 atm and for given (mass% CaO/mass% SiO / ratios in the system between 0 and about 1. It was found for the plain system that the liquidus line remarkably shifted toward the low FeO -content region when the partial pressure of oxygen was increased from 10 to 10 atm. It was clarified that the addition of Al O made the homogeneous region wide only in a strongly reducing atmosphere while the addition of MgO made the homogeneous liquid region remarkably narrow at all the oxygen partial pressures and all the (mass% CaO/mass% SiO / ratios investigated in the study

The pathways of cell death in cardiomyocytes induced by vanadate

After 24 hours, cardiac myocytes exposure to 10 μM (LD50) vanadate (meta or decavanadate) an increased (30%) of caspase 3-activation was observed, although not significant. On contrary, a significant decrease (40%) of ATP content, characteristic of necrotic cell death was detected. Furthermore, vanadate treatment increased intracellular Ca2+ level from 60 nM to 240 nM, whereas it decreases mitochondria superoxide anion generation and induces mitochondria membrane depolarization (IC50=6.5 μM). In conclusion, micromolar vanadate exposure induces large chances in two major bioenergetic markers in cardiac myocytes: intracellular calcium concentration and superoxide anion mitochondrial production, suggesting a necrotic cell death through a mitochondrial toxic pathway

Vanadate induces necrotic cell death in neonatal rat cardiomyocytes through mitochondrial membrane depolarization

Besides the well-known inotropic effects of vanadium in cardiac muscle, previous studies have shown that vanadate can stimulate cell growth or induce cell death. In this work, we studied the toxicity to neonatal rat ventricular myocytes (cardiomyocytes) of two vanadate solutions containing different oligovanadates distribution, decavanadate (containing decameric vanadate, V10) and metavanadate (containing monomeric vanadate and also di-, tetra-, and pentavanadate). Incubation for 24 h with decavanadate or metavanadate induced necrotic cell death of cardiomyocytes, without significant caspase-3 activation. Only 10 μM total vanadium of either decavanadate (1 μMV10) or metavanadate (10 μM total vanadium) was needed to produce 50% loss of cell viability after 24 h (assessed with MTT and propidium iodide assays). Atomic absorption spectroscopy showed that vanadium accumulation in cardiomyocytes after 24 h was the same when incubation was done with decavanadate or metavanadate. A decrease of 75% of the rate of mitochondrial superoxide anion generation, monitored with dihydroethidium, and a sustained rise of cytosolic calcium (monitored with Fura-2-loaded cardiomyocytes) was observed after 24 h of incubation of cardiomyocytes with decavanadate or metavanadate concentrations close to those inducing 50% loss of cell viability produced. In addition, mitochondrial membrane depolarization within cardiomyocytes, monitored with tetramethylrhodamine ethyl esther or with 3,3′,6,6′-tetrachloro-1,1′,3,3′- tetraethylbenzimidazolcarbocyanine iodide, were observed after only 6 h of incubation with decavanadate or metavanadate. The concentration needed for 50% mitochondrial depolarization was 6.5 ( 1 μM total vanadium for both decavanadate (0.65 μMV10) and metavanadate. In conclusion, mitochondrial membrane depolarization was an early event in decavanadate- and monovanadate-induced necrotic cell death of cardiomyocytes

Improving Event Time Prediction by Learning to Partition the Event Time Space

Recently developed survival analysis methods improve upon existing approaches by predicting the probability of event occurrence in each of a number pre-specified (discrete) time intervals. By avoiding placing strong parametric assumptions on the event density, this approach tends to improve prediction performance, particularly when data are plentiful. However, in clinical settings with limited available data, it is often preferable to judiciously partition the event time space into a limited number of intervals well suited to the prediction task at hand. In this work, we develop a method to learn from data a set of cut points defining such a partition. We show that in two simulated datasets, we are able to recover intervals that match the underlying generative model. We then demonstrate improved prediction performance on three real-world observational datasets, including a large, newly harmonized stroke risk prediction dataset. Finally, we argue that our approach facilitates clinical decision-making by suggesting time intervals that are most appropriate for each task, in the sense that they facilitate more accurate risk prediction.Comment: 16 pages, 5 figures, 2 table

Increasing Collegiate Flight Training Fleet Utilization Through the Use of an Aircraft Assignment Algorithm

The operational efficiency of fleet aircraft employed for student flight training in collegiate aviation programs is strongly influenced by scheduling, among other factors. The average utilization rate for the fleet operated by the Purdue University School of Aviation and Transportation Systems was found to be 24% (Avery, 2014), and there is no data to suggest that that this rate is atypical in similar institutional programs. Mott and Bullock (2015) identified several means by which the utilization rate could be increased, and improvements in the dispatch and scheduling process were a key component of those recommendations. This article describes a scheduling algorithm that was implemented at Purdue University in the fall semester of 2015. The algorithm is a linear programming technique that incorporates optimization constraints unique to collegiate flight training operations. The resulting improvements in aircraft utilization will facilitate an increased matriculation rate of students into the flight program, thereby allowing the allocation of fixed costs over a wider user base and the reduction of overall program fees for all students. Those improvements are validated through measurement of the reduction of the cumulative turn times between aircraft operations

Quality model for software development pymes located in the valle de Aburrá metropolitan area

Modelo de calidad para pymes desarrolladoras de software ubicadas en el área metropolitana del valle de AburráMediante este artículo se desea mostrar el proyecto de investigación (Modelo de Calidad para PYMES Desarrolladoras de Software ubicadas en el Área Metropolitana del Valle de Aburra) se presenta un Modelo de Calidad que busca servir de apoyo a las Pymes desarrolladoras de software del Área Metropolitana del Valle de Aburra. Para su creación se realizó un análisis de modelos importantes como: MoProSoft, TST/PSP, Mosca, CMI, CMMI, de los cuales se toman como base las mejores prácticas. De igual manera se analiza conceptos importantes como Modelos de Calidad, Gestión de Procesos, Metodologías de Desarrollo, Gestión de proyectos. Este modelo de calidad busca servir de base a las pequeñas empresas, creando apoyo a los equipos desarrolladores de software mejorando su rendimiento y efectividad en la elaboración de los proyectos.AbstractThe purpose of this article is to showcase a research project (Quality Model for Software Development Pymes Located in the Aburrá Valley Metropolitan Area), and to present the resulting Quality Model, intended to support PYMES that develop software and are located in the Aburrá Valley Metropolitan Area. Many important models were analyzed for its development, such as MoProSoft, TST/PSP, Mosca, CMI, CMMI, from which the best practices were extracted. Additionally, important concepts were taken into account, such as Quality Models, Process Management, Development Processes, and Project Management. This quality model aims serve as a basis for small companies by supporting their software development teams, improving their performance and effectiveness in project elaboration.Keywords: Software, Software Development Process, Quality Models, Software Qualit

Local invertibility in Sobolev spaces with applications to nematic elastomers and magnetoelasticity

We define a class of deformations in W^1,p(\u3a9,R^n), p>n 121, with positive Jacobian that do not exhibit cavitation. We characterize that class in terms of the non-negativity of the topological degree and the equality between the distributional determinant and the pointwise determinant of the gradient. Maps in this class are shown to satisfy a property of weak monotonicity, and, as a consequence, they enjoy an extra degree of regularity. We also prove that these deformations are locally invertible; moreover, the neighbourhood of invertibility is stable along a weak convergent sequence in W^1,p, and the sequence of local inverses converges to the local inverse. We use those features to show weak lower semicontinuity of functionals defined in the deformed configuration and functionals involving composition of maps. We apply those results to prove existence of minimizers in some models for nematic elastomers and magnetoelasticity