60 research outputs found
Lagrangian dynamical geography of the Gulf of Mexico
We construct a Markov-chain representation of the surface-ocean Lagrangian
dynamics in a region occupied by the Gulf of Mexico (GoM) and adjacent portions
of the Caribbean Sea and North Atlantic using satellite-tracked drifter
trajectory data, the largest collection so far considered. From the analysis of
the eigenvectors of the transition matrix associated with the chain, we
identify almost-invariant attracting sets and their basins of attraction. With
this information we decompose the GoM's geography into weakly dynamically
interacting provinces, which constrain the connectivity between distant
locations within the GoM. Offshore oil exploration, oil spill contingency
planning, and fish larval connectivity assessment are among the many activities
that can benefit from the dynamical information carried in the geography
constructed here.Comment: Submitted to Scientific Report
Nutrimetabolomics: An Integrative Action for Metabolomic Analyses in Human Nutritional Studies
The life sciences are currently being transformed by an unprecedented wave of developments in molecular analysis, which include important advances in instrumental analysis as well as biocomputing. In light of the central role played by metabolism in nutrition, metabolomics is rapidly being established as a key analytical tool in human nutritional studies. Consequently, an increasing number of nutritionists integrate metabolomics into their study designs. Within this dynamic landscape, the potential of nutritional metabolomics (nutrimetabolomics) to be translated into a science, which can impact on health policies, still needs to be realized. A key element to reach this goal is the ability of the research community to join, to collectively make the best use of the potential offered by nutritional metabolomics. This article, therefore, provides a methodological description of nutritional metabolomics that reflects on the stateâofâtheâart techniques used in the laboratories of the Food Biomarker Alliance (funded by the European Joint Programming Initiative "A Healthy Diet for a Healthy Life" (JPI HDHL)) as well as points of reflections to harmonize this field. It is not intended to be exhaustive but rather to present a pragmatic guidance on metabolomic methodologies, providing readers with useful "tips and tricks" along the analytical workflow
State-of-the-art methods for exposure-health studies: Results from the exposome data challenge event
The exposome recognizes that individuals are exposed simultaneously to a multitude of different environmental factors and takes a holistic approach to the discovery of etiological factors for disease. However, challenges arise when trying to quantify the health effects of complex exposure mixtures. Analytical challenges include dealing with high dimensionality, studying the combined effects of these exposures and their interactions, integrating causal pathways, and integrating high-throughput omics layers. To tackle these challenges, the Barcelona Institute for Global Health (ISGlobal) held a data challenge event open to researchers from all over the world and from all expertises. Analysts had a chance to compete and apply state-of-the-art methods on a common partially simulated exposome dataset (based on real case data from the HELIX project) with multiple correlated exposure variables (P > 100 exposure variables) arising from general and personal environments at different time points, biological molecular data (multi-omics: DNA methylation, gene expression, proteins, metabolomics) and multiple clinical phenotypes in 1301 motherâchild pairs. Most of the methods presented included feature selection or feature reduction to deal with the high dimensionality of the exposome dataset. Several approaches explicitly searched for combined effects of exposures and/or their interactions using linear index models or response surface methods, including Bayesian methods. Other methods dealt with the multi-omics dataset in mediation analyses using multiple-step approaches. Here we discuss features of the statistical models used and provide the data and codes used, so that analysts have examples of implementation and can learn how to use these methods. Overall, the exposome data challenge presented a unique opportunity for researchers from different disciplines to create and share state-of-the-art analytical methods, setting a new standard for open science in the exposome and environmental health field
MĂ©todo fluorescente (diacetato de fluoresceĂna e brometo de etĂdeo) para o estudo da viabilidade de Cryptococcus neoformans em lĂquor
Plasma metabolites associated with type 2 diabetes in a Swedish population: a caseâcontrol study nested in a prospective cohort
LongITools: Dynamic longitudinal exposome trajectories in cardiovascular and metabolic noncommunicable diseases
The current epidemics of cardiovascular and metabolic noncommunicable diseases have emerged alongside dramatic modifications in lifestyle and living environments. These correspond to changes in our âmodernâ postwar societies globally characterized by rural-to-urban migration, modernization of agricultural practices, and transportation, climate change, and aging. Evidence suggests that these changes are related to each other, although the social and biological mechanisms as well as their interactions have yet to be uncovered. LongITools, as one of the 9 projects included in the European Human Exposome Network, will tackle this environmental health equation linking multidimensional environmental exposures to the occurrence of cardiovascular and metabolic noncommunicable diseases
Försök Till förklaringar öfver hÀllristningar med femton plancher.
Mode of access: Internet
- âŠ