Data Analysis Tool (data + analysis_tool)

Distribution by Scientific Domains

Selected Abstracts

Inflammation reduces HDL protection against primary cardiac risk

James P. Corsetti
Eur J Clin Invest 2010; 40 (6): 483,489 Abstract Background, We recently reported high high-density lipoprotein (HDL) cholesterol as a predictor of recurrent risk in a subgroup of postinfarction patients defined by hypercholesterolemia and high C-reactive protein (CRP) levels. We investigated whether a similar high-risk subgroup might exist for incident cardiovascular disease. Material and Methods, A graphical exploratory data analysis tool was used to identify high-risk subgroups in a male population-based cohort (n = 3405) from the prevention of renal and vascular end-stage disease study by generating 3-dimensional mappings of risk over the HDL-cholesterol/CRP domain with subsequent use of Kaplan,Meier analysis to verify high-risk. Within-subgroup risk was assessed using Cox proportional hazards regression and Kaplan,Meier analysis. Results, Mappings revealed two high-risk subgroups: a low HDL-cholesterol/high CRP subgroup and a high HDL-cholesterol/high CRP subgroup. The low HDL-cholesterol subgroup demonstrated a pattern of metabolic syndrome dyslipidemia contrasted with a predominantly unremarkable biomarker pattern for the high HDL-cholesterol subgroup. However, in the high HDL-cholesterol subgroup, CRP levels were higher than the low HDL-cholesterol subgroup; and within the high HDL-cholesterol subgroup, CRP predicted risk. Moreover, in the high HDL-cholesterol subgroup, risk was associated with lower triglyceride levels in conjunction with presumptively larger HDL particles. Conclusions, High HDL-cholesterol and high CRP levels define a subgroup of men at high-risk for incident cardiovascular disease. High HDL cholesterol-associated risk likely relates to impaired HDL particle remodelling in the setting of inflammation. This approach may facilitate identification of additional inflammation-related mechanisms underlying high HDL cholesterol-associated risk; and potentially influence management of such patients. [source]

An ecologist's guide to ecogenomics

Summary 1Currently, plant ecologists are increasingly adopting approaches and techniques from molecular biology. The new field of ecogenomics aims at understanding the mechanistic basis for adaptation and phenotypic variation by using genomic techniques to investigate the mechanistic and evolutionary basis of species interactions, and focuses on identifying the genes affected by evolution. 2While the entire toolbox of genomics is only available for model species such as Arabidopsis thaliana, we describe the options open to ecologists interested in pursuing an ecogenomics research program on ecologically relevant traits or phenomena in non-model species, for which part of the genomic toolbox may be currently unavailable. In these non-model species, a viable ecogenomics research program is possible with relatively modest effort. 3Four challenges to further development of ecogenomics are described and discussed: (i) the ecogenomic study of non-model species; (ii) reconciliation of experimental languages of ecology and evolutionary biology with molecular biology; (iii) development of specific ecogenomic data analysis tool; and (iv) adoption of a multidisciplinary cooperative research culture. 4An important task for ecologists is to provide the necessary ecological input (the ,eco' part) to ecogenomics. [source]

A chromatic explosion: the development and future of multiparameter flow cytometry

IMMUNOLOGY, Issue 4 2008
Pratip K. Chattopadhyay
Summary Multiparameter flow cytometry has matured tremendously since the 1990s, giving rise to a technology that allows us to study the immune system in unprecedented detail. In this article, we review the development of hardware, reagents, and data analysis tools for multiparameter flow cytometry and discuss future advances in the field. Finally, we highlight new applications that use this technology to reveal previously unappreciated aspects of cell biology and immunity. [source]

Mass spectrometry-based metabolomics

Katja Dettmer
Abstract This review presents an overview of the dynamically developing field of mass spectrometry-based metabolomics. Metabolomics aims at the comprehensive and quantitative analysis of wide arrays of metabolites in biological samples. These numerous analytes have very diverse physico-chemical properties and occur at different abundance levels. Consequently, comprehensive metabolomics investigations are primarily a challenge for analytical chemistry and specifically mass spectrometry has vast potential as a tool for this type of investigation. Metabolomics require special approaches for sample preparation, separation, and mass spectrometric analysis. Current examples of those approaches are described in this review. It primarily focuses on metabolic fingerprinting, a technique that analyzes all detectable analytes in a given sample with subsequent classification of samples and identification of differentially expressed metabolites, which define the sample classes. To perform this complex task, data analysis tools, metabolite libraries, and databases are required. Therefore, recent advances in metabolomics bioinformatics are also discussed. 2006 Wiley Periodicals, Inc., Mass Spec Rev 26:51,78, 2007 [source]