Publications by authors named "I Arenzana-Ramila"

Human immunodeficiency virus (HIV) is a retrovirus that weakens the immune system and permits opportunistic diseases such as hepatitis C (HCV) to enter the body. These diseases induce metabolic disorders in the patients and it is therefore logical to approach them from a holistic, functional perspective, studying the metabolome comprehensively to identify metabolic signatures associated with certain disease states. The metabolomics strategy here proposed involves metabolic fingerprinting using Fourier transform infrared spectroscopy and chemometric tools on 72 plasma samples (subdivided into 63 training and 9 test samples) to differentiate between healthy subjects and patients with different disease stages.

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Lipid profiling is a promising tool for the discovery and subsequent identification of biomarkers associated with various diseases. However, data quality is quite dependent on the pre-analytical methods employed. To date, potential confounding factors that may affect lipid metabolite levels after the thawing of plasma for biomarker exploration studies have not been thoroughly evaluated.

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Article Synopsis
  • The study evaluates how different factors (like oxygen levels, wood type, and maceration time) affect the aging of red wines, specifically their phenolic and color characteristics.
  • The findings show that adjusting these factors can change the levels of specific compounds, like anthocyanins and flavan-3-ols, which are directly related to the wine's color.
  • The research highlights a new approach to crafting wines with desired color traits, a subject that hasn't been extensively explored before using detailed experimental methods.
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Lipidomics is an emerging field in biomedical research that includes the analysis of all the lipids present in complex biological samples. To evaluate the chemical and biological diversity of lipids, lipid extraction is usually the first step toward lipidomics analysis. Nevertheless, sample preparation is still a time-consuming and error prone analytical step.

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