Search results for "ARIA"

Shelf life evaluation of fresh-cut red chicory subjected to different minimal processes

2018

Abstract Microbiological, chemical and physical parameters of minimally processed red chicory (Cichorium intybus L.) subjected to two different transformation processes were investigated. A classic ready-to-eat (RTE) process (P1) and a production without cutting (P2) were monitored during refrigerated (4 °C) storage (15 d). Total mesophilic microorganisms, total psychrotrophic microorganisms and pseudomonads were detected at the highest cell densities in all samples. Presumptive Pseudomonas population dominated the cultivable microbial community of RTE red chicory and were characterized genetically. Twenty-two randomly amplified polymorphic DNA (RAPD) types were investigated by 16S rRNA gen…

Ancient European dog genomes reveal continuity since the Early Neolithic

2017

Europe has played a major role in dog evolution, harbouring the oldest uncontested Palaeolithic remains and having been the centre of modern dog breed creation. Here we sequence the genomes of an Early and End Neolithic dog from Germany, including a sample associated with an early European farming community. Both dogs demonstrate continuity with each other and predominantly share ancestry with modern European dogs, contradicting a previously suggested Late Neolithic population replacement. We find no genetic evidence to support the recent hypothesis proposing dual origins of dog domestication. By calibrating the mutation rate using our oldest dog, we narrow the timing of dog domestication t…

Assessing Human Genetic Variations in Glucose Transporter SLC2A10 and Their Role in Altering Structural and Functional Properties

2018

Purpose: Demand is increasing for clinical genomic sequencing to provide diagnoses for patients presenting phenotypes indicative of genetic diseases, but for whom routine genetic testing failed to yield a diagnosis. DNA-based testing using high-throughput technologies often identifies variants with insufficient evidence to determine whether they are disease-causal or benign, leading to categorization as variants of uncertain significance (VUS). Methods: We used molecular modeling and simulation to generate specific hypotheses for the molecular effects of variants in the human glucose transporter, GLUT10 (SLC2A10). Similar to many disease-relevant membrane proteins, no experimentally derived…

Toward a direct and scalable identification of reduced models for categorical processes.

2017

The applicability of many computational approaches is dwelling on the identification of reduced models defined on a small set of collective variables (colvars). A methodology for scalable probability-preserving identification of reduced models and colvars directly from the data is derived—not relying on the availability of the full relation matrices at any stage of the resulting algorithm, allowing for a robust quantification of reduced model uncertainty and allowing us to impose a priori available physical information. We show two applications of the methodology: (i) to obtain a reduced dynamical model for a polypeptide dynamics in water and (ii) to identify diagnostic rules from a standar…

A multicentric study to evaluate the use of relative retention times in targeted proteomics.

2016

Despite the maturity reached by targeted proteomic strategies, reliable and standardized protocols are urgently needed to enhance reproducibility among different laboratories and analytical platforms, facilitating a more widespread use in biomedical research. To achieve this goal, the use of dimensionless relative retention times (iRT), defined on the basis of peptide standard retention times (RT), has lately emerged as a powerful tool. The robustness, reproducibility and utility of this strategy were examined for the first time in a multicentric setting, involving 28 laboratories that included 24 of the Spanish network of proteomics laboratories (ProteoRed-ISCIII). According to the results…

Discovering hidden temporal patterns in behavior and interaction : t-pattern detection and analysis with THEME

2016

In our laboratories we use T-pattern analysis to study rat behavior in different and well-known experimental assays widely employed as rodent models of anxiety: the open field, the hole board and the elevated plus maze. By using Theme software and T-pattern analysis, we have observed that numerous events, characterizing rodent behavior in each experimental model, occurred sequentially and with significant constraints on the interval lengths separating them. In this chapter, for each test, we highlight some key aspects of our behavioral analyses, with a twofold attempt: first to provide the researcher with useful information concerning the application of T-pattern analysis in the study of ro…

DeepWAS: Multivariate genotype-phenotype associations by directly integrating regulatory information using deep learning

2020

Genome-wide association studies (GWAS) identify genetic variants associated with traits or diseases. GWAS never directly link variants to regulatory mechanisms. Instead, the functional annotation of variants is typically inferred by post hoc analyses. A specific class of deep learning-based methods allows for the prediction of regulatory effects per variant on several cell type-specific chromatin features. We here describe “DeepWAS”, a new approach that integrates these regulatory effect predictions of single variants into a multivariate GWAS setting. Thereby, single variants associated with a trait or disease are directly coupled to their impact on a chromatin feature in a cell type. Up to…

Identifying Prognostic SNPs in Clinical Cohorts: Complementing Univariate Analyses by Resampling and Multivariable Modeling

2016

Clinical cohorts with time-to-event endpoints are increasingly characterized by measurements of a number of single nucleotide polymorphisms that is by a magnitude larger than the number of measurements typically considered at the gene level. At the same time, the size of clinical cohorts often is still limited, calling for novel analysis strategies for identifying potentially prognostic SNPs that can help to better characterize disease processes. We propose such a strategy, drawing on univariate testing ideas from epidemiological case-controls studies on the one hand, and multivariable regression techniques as developed for gene expression data on the other hand. In particular, we focus on …

2020

Background Small sample sizes combined with multiple correlated endpoints pose a major challenge in the statistical analysis of preclinical neurotrauma studies. The standard approach of applying univariate tests on individual response variables has the advantage of simplicity of interpretation, but it fails to account for the covariance/correlation in the data. In contrast, multivariate statistical techniques might more adequately capture the multi-dimensional pathophysiological pattern of neurotrauma and therefore provide increased sensitivity to detect treatment effects. Results We systematically evaluated the performance of univariate ANOVA, Welch’s ANOVA and linear mixed effects models …

Lipid levels, atrial fibrillation and the impact of age:Results from the LIPIDOGRAM2015 study

2020

Background and aims: An inverse relationship between lipid levels and atrial fibrillation (AF) has been suggested, but whether the association is upheld for all age groups remains unclear. The aim of the study was to examine associations between lipid levels and AF by age groups in a nationwide study in Poland. Methods: Multivariate Poisson regression models were used to estimate prevalence ratios (PRs) for AF by lipid levels. Low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglycerides (TG), total cholesterol (TC), non-HDL-C and LDL-C/HDL-C ratios were grouped into quartiles. Results: Of the 13,724 participants, 5.2% (n = 708) had AF. People with…