RESUMO

BACKGROUND: Cocoa quality plays a pivotal role in establishing denominations of origin, with genotypes, geography, climate and soil conditions being key variables. However, these factors have not been comprehensively explored in defining cacao denominations of origin. The present study addresses this gap by laying the foundation for cacao denomination of origin, focusing on the Buenaventura region on Colombia's Pacific coast. Our goal is to provide a holistic understanding of the elements underpinning cacao denomination of origin, emphasizing Buenaventura's unique cocoa quality and geographical significance. RESULTS: Through the Buenaventura case, we propose a robust framework applicable to other cacao-producing regions, elevating the recognition and value of cacao denomination of origin. Our framework encompasses geography, agronomy, genetics, microbial diversity, pests and diseases and cocoa quality. In a pioneering move, we propose a cacao denomination of origin in Colombia, specifically examining Bajo Calima, Sabaletas and Cisneros within Buenaventura region. Buenaventura stands out for its cocoa quality, characterized by fruity flavors attributed to the rich biodiversity of the lowland rainforest. CONCLUSION: Our analysis indicates specific geographical indicators for each of the study zones, with Buenaventura identified as a region with natural characteristics to produce fine flavour cocoa products. Each zone exhibited a high differentiation and diversity of cacao cultivars. Buenaventura has the potential to be designated as a future denomination of origin for cacao from the Pacific region of Colombia, characterized by its unique fruity-aroma chocolates. Our framework is adaptable to other cacao-producing regions, facilitating the establishment of denominations of origin within the cocoa industry and agriculture. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Assuntos

RESUMO

The association between neurodegenerative diseases (NDs) and obesity has been well studied in recent years. Obesity is a syndrome of multifactorial etiology characterized by an excessive accumulation and release of fatty acids (FA) in adipose and non-adipose tissue. An excess of FA generates a metabolic condition known as lipotoxicity, which triggers pathological cellular and molecular responses, causing dysregulation of homeostasis and a decrease in cell viability. This condition is a hallmark of NDs, and astrocytes are particularly sensitive to it, given their crucial role in energy production and oxidative stress management in the brain. However, analyzing cellular mechanisms associated with these conditions represents a challenge. In this regard, metabolomics is an approach that allows biochemical analysis from the comprehensive perspective of cell physiology. This technique allows cellular metabolic profiles to be determined in different biological contexts, such as those of NDs and specific metabolic insults, including lipotoxicity. Since data provided by metabolomics can be complex and difficult to interpret, alternative data analysis techniques such as machine learning (ML) have grown exponentially in areas related to omics data. Here, we developed an ML model yielding a 93% area under the receiving operating characteristic (ROC) curve, with sensibility and specificity values of 80% and 93%, respectively. This study aimed to analyze the metabolomic profiles of human astrocytes under lipotoxic conditions to provide powerful insights, such as potential biomarkers for scenarios of lipotoxicity induced by palmitic acid (PA). In this work, we propose that dysregulation in seleno-amino acid metabolism, urea cycle, and glutamate metabolism pathways are major triggers in astrocyte lipotoxic scenarios, while increased metabolites such as alanine, adenosine, and glutamate are suggested as potential biomarkers, which, to our knowledge, have not been identified in human astrocytes and are proposed as candidates for further research and validation.

Assuntos

RESUMO

Lipotoxicity is a metabolic condition resulting from the accumulation of free fatty acids in non-adipose tissues which involves a series of pathological responses triggered after chronic exposure to high levels of fatty acids, severely detrimental to cellular homeostasis and viability. In brain, lipotoxicity affects both neurons and other cell types, notably astrocytes, leading to neurodegenerative processes, such as Alzheimer (AD) and Parkinson diseases (PD). In this study, we performed for the first time, a whole lipidomic characterization of Normal Human Astrocytes cultures exposed to toxic concentrations of palmitic acid and the protective compound tibolone, to establish and identify the set of potential metabolites that are modulated under these experimental treatments. The study covered 3843 features involved in the exo- and endo-metabolome extracts obtained from astrocytes with the mentioned treatments. Through multivariate statistical analysis such as PCA (principal component analysis), partial least squares (PLS-DA), clustering analysis, and machine learning enrichment analysis, it was possible to determine the specific metabolites that were affected by palmitic acid insult, such as phosphoethanolamines, phosphoserines phosphocholines and glycerophosphocholines, with their respective metabolic pathways impact. Moreover, our results suggest the importance of tibolone in the generation of neuroprotective metabolites by astrocytes and may be relevant to the development of neurodegenerative processes.

Assuntos

RESUMO

The systematic literature review presented here is designed to illustrate the role of metabonomics and metabolomics in pesticide exposure studies. The search was conducted in Thomson Reuters Web of Science (ISI Web of Knowledge) database. The references and citations for each article were downloaded for analysis. Graph theory was used to determine relevant articles and distinct relationships between classic and current research in this field through its structural characteristics. The initial network included 4423 nodes and 4978 links, from which indegree, outdegree and betweenness indicators were extracted. After preprocessing the data, the network was reduced to 415 nodes and 974 links. From this network, 80 articles with the highest score between the three indicators were extracted for review. This methodology allowed for the identification of different perspectives of metabolomic and metabonomic pesticide studies that included the mode and mechanism of action, toxicological and biological monitoring, environmental metab-olomics, metabolism, dose response and biomarkers and its role in pesticide exposure.

La revisión sistemática de literatura presentada a continuación tiene como objetivo dar a conocer el rol que han tenido la metabolómica en el estudio de la exposición a plaguicidas. La búsqueda se llevó a cabo en la base de datos Thomson Reuters Web of Science (ISI Web of Knowledge). Posteriormente, se descargaron todos los registros producto de resultado de la búsqueda y cada citación dentro de cada artículo. Estas referencias fueron analizadas mediante la teoría de grafos con el fin de identificar los artículos más relevantes, los artículos clásicos y recientes y los que presentan mayor intermediación en el tema de investigación. La red de citaciones fue construida con inicialmente con 4423 nodos (artículos) y 4978 enlaces (citaciones) a los cuales se les determinó los indicadores de grado de entrada, grado de salida y centralidad en el grafo. Posteriormente, esta red de citaciones fue procesada eliminando los artículos desconectados, reduciendo la red a 415 nodos y 974 enlaces. De esta red ya procesada se extrajeron 80 artículos que presentaron mayores indicadores de grado y centralidad. Finalmente, esta metodología permitió la identificación de diferentes perspectivas de los estudios metabolómicos y metabonómicos en la exposición a plaguicidas que incluyen estudios de modo de acción, mecanismos de acción, monitoreo biológico y toxicológico, metabolómica ambiental, metabolismo, dosis respuesta e identificación de biomarcadores.

Assuntos

RESUMO

Objetivo: describir las características clínicas, epidemiolópgicas y microbiológicas en una cohorte de pacientes con bacteremia significativa en un hospital universitario. Diseño: estudio observacional no analítico en una cohorte histórica (retrospectiva). Sitio del estudio: Hospital Universitario Sam Vicente de Paul, Medellín, Colombia. Pacientes: mayores de 12 años hospitalizados entre julio de 2993 y nuio de 1995, con crecimiento en al menos un hemocultivo de gérmenes habituales en piel. Variables: edad, sexo, servicio, hemocultivos verdaderos positivos, hemocultivos falsos postivos, origen de la infección, foco primario, factores predisponentes, criterios clínicos de severidad, terapia antibiótica y resultado final. Análisis estadístico: presentación de datos en promedios y proporciones. Diferencia de proporciones con prueba de Chi cuadrado o prueba exacta de Fisher. Intervalos de confianza del 95 por ciento y error alfa de 0.05. Resultados: Durante el período del estudio se informó crecimiento bacteriano en 605 hemocultivos, 356 (58.8 por ciento) de los cuales se consideraron verdaderos positivos y 249 (41.2 por ciento) falsos positivos. Entre los primeros, los gérmenes más frecuentes fueron S. aureus (n=110, 30.9 por ciento), E. coli (n=52, 14.6 por ciento), K. pneumoniae (n=44, 12.4 por ciento), Estreptococo alfa hemolítico (n=18, 5.1 por ciento) y S. pneumoniae (n=17, 4.8 por ciento). El promedio de edad de los pacientes fue de 41,8 años, y de ellos 212 (59.6 por ciento) fueron hombres y 144 mujeres (40.4 por ciento). La infección se consideró extrahospitalaria en 229 casos (64.7 por ciento)

Assuntos