Navegando por Autor "Tasic, Ljubica"
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Artigo Are phosphatidylcholine and lysophosphatidylcholine body levels potentially reliable biomarkers in obesity?: a review of human studies(Molecular Nutrition & Food Research, 2023-01) Reis, Bruna Zavarize; Bellot, Paula Emília Nunes Ribeiro; Moia, Melissa Nunes; Pedrosa, Lucia Fatima Campos; Tasic, Ljubica; Barbosa, Fernando; Evangelista, Karine Cavalcanti Maurício SenaPhosphatidylcholines (PCs) are the major components of biological membranes in animals and are a class of phospholipids that incorporate choline as a headgroup. Lysophosphatidylcholines (LPCs) are a class of lipid biomolecules derived from the cleavage of PCs, and are the main components of oxidized low-density lipoproteins (oxLDLs) that are involved in the pathogenesis of atherosclerosis. Since obesity is associated with a state of chronic low-grade inflammation, one can anticipate that the lipidomic profile changes in this context and both PCs and LPCs are gaining attention as hypothetically reliable biomarkers of obesity. Thus, a literature search is performed on PubMed, Latin American and Caribbean Health Science Literature (LILACS), and Excerpta Medica DataBASE (Embase) to obtain the findings of population studies to clarify this hypothesis. The search strategy resulted in a total of 2403 reports and 21 studies were included according to the eligibility criteria. Controversial data on the associations of PCs and LPCs with body mass index (BMI) and body fat parameters have been identified. There is an inverse relationship between BMI and most species of PCs, and a majority of studies exhibited negative associations between BMI and LPCs. Other findings regarding the differences between PCs and LPCs in obesity are presented, and the associated uncertainties are discussed in detailArtigo Plasma lipid metabolites as potential biomarkers for identifying individuals at risk of obesity-induced metabolic complications(Scientific Reports, 2023) Lima, Severina Carla Vieira Cunha; Bellot, Paula Emília Nunes Ribeiro; Braga, Erik Sobrinho; Omage, Folorunsho Bright; Nunes, Francisca Leide da; Lyra, Clélia Oliveira; Marchioni, Dirce Maria Lobo; Pedrosa, Lucia Fatima Campos; Barbosa Júnior, Fernando; Tasic, Ljubica; Evangelista, Karine Cavalcanti Maurício Sena; https://orcid.org/0000-0001-8268-1986Lipidomics studies have indicated an association between obesity and lipid metabolism dysfunction. This study aimed to evaluate and compare cardiometabolic risk factors, and the lipidomic profile in adults and older people. A cross-sectional study was conducted with 72 individuals, divided into two sex and age-matched groups: obese (body mass index—BMI ≥ 30 kg/m2; n = 36) and non-obese (BMI < 30 kg/m2; n = 36). The lipidomic profiles were evaluated in plasma using 1H nuclear magnetic resonance (1H-NMR) spectroscopy. Obese individuals had higher waist circumference (p < 0.001), visceral adiposity index (p = 0.029), homeostatic model assessment insulin resistance (HOMA-IR) (p = 0.010), and triacylglycerols (TAG) levels (p = 0.018). 1H-NMR analysis identified higher amounts of saturated lipid metabolite fragments, lower levels of unsaturated lipids, and some phosphatidylcholine species in the obese group. Two powerful machine learning (ML) models—k-nearest neighbors (kNN) and XGBoost (XGB) were employed to characterize the lipidomic profile of obese individuals. The results revealed metabolic alterations associated with obesity in the NMR signals. The models achieved high accuracy of 86% and 81%, respectively. The feature importance analysis identified signal at 1.50–1.60 ppm (–CO–CH2–CH2–, Cholesterol and fatty acid in TAG, Phospholipids) to have the highest importance in the two models.Artigo Plasma lipid metabolites as potential biomarkers for identifying individuals at risk of obesity-induced metabolic complications(Scientific Reports, 2023-07) Lyra, Clelia de Oliveira; Bellot, Paula Emília Nunes Ribeiro; Braga, Erik Sobrinho; Omage, Folorunsho Bright; Nunes, Francisca Leide da Silva; Lima, Severina Carla Vieira Cunha; Marchioni, Dirce Maria Lobo; Pedrosa, Lucia Fatima Campos; Barbosa, Fernando; Tasic, Ljubica; Evangelista, Karine Cavalcanti Maurício SenaLipidomics studies have indicated an association between obesity and lipid metabolism dysfunction. This study aimed to evaluate and compare cardiometabolic risk factors, and the lipidomic profle in adults and older people. A cross-sectional study was conducted with 72 individuals, divided into two sex and age-matched groups: obese (body mass index—BMI≥ 30 kg/m2 ; n= 36) and nonobese (BMI < 30 kg/m2 ; n= 36). The lipidomic profles were evaluated in plasma using 1 H nuclear magnetic resonance (1 H-NMR) spectroscopy. Obese individuals had higher waist circumference (p< 0.001), visceral adiposity index (p= 0.029), homeostatic model assessment insulin resistance (HOMA-IR) (p= 0.010), and triacylglycerols (TAG) levels (p= 0.018). 1 H-NMR analysis identifed higher amounts of saturated lipid metabolite fragments, lower levels of unsaturated lipids, and some phosphatidylcholine species in the obese group. Two powerful machine learning (ML) models—knearest neighbors (kNN) and XGBoost (XGB) were employed to characterize the lipidomic profle of obese individuals. The results revealed metabolic alterations associated with obesity in the NMR signals. The models achieved high accuracy of 86% and 81%, respectively. The feature importance analysis identifed signal at 1.50–1.60 ppm (–CO–CH2–CH2–, Cholesterol and fatty acid in TAG, Phospholipids) to have the highest importance in the two models