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1.
J Sci Food Agric ; 102(10): 4151-4161, 2022 Aug 15.
Artigo em Inglês | MEDLINE | ID: mdl-35000197

RESUMO

BACKGROUND: Citrus fruits are a rich source of valuable molecules, and their industrial processing produces bagasses, little explored to generate important by-products. These Citrus residues, including seeds and peels, also contain numerous pharmacologically important substances. To reduce the impact of these Citrus by-products, young, harvested fruits could be used as a functional supplemental food while another part is grown until maturity for industrial production. This study therefore aims to valorize rangpur (Citrus limonia) in the first 3 months of its growth by investigating and comparing its monthly chemical profiles using ultra-performance liquid chromatography-electrospray mass spectrometry (UPLC-ESI-MS) and its anti-inflammatory and antiplatelet activity. RESULTS: Extracts obtained from the fruits harvested in November, December, and January, 2017 and 2018 (L221117, L161217, and L160118) showed different UPLC-ESI-MS profiles. Twenty-five of the 26 detected metabolites were identified as cyclitol, pyrrolidine betaine, aryl propanoyl esters, chlorogenic acids, flavonoids, coumarins, and limonoids. Quantification studies indicated an increased concentration of hesperidin from the younger fruits to the older fruits of the series. L160118 reduced nitrogen oxide (NOx), tumor necrosis factor alpha (TNF-α), and interleukin 6 (IL-6) levels more than other extracts. Their activity followed the same trends as the hesperidin concentration in each fruit. In contrast, the most promising antiplatelet activity was observed with the extracts from the two youngest fruits. This suggests combined effects of the chemical components found in these fruits' extracts. CONCLUSION: The extracts obtained from these young fruits showed considerable anti-inflammatory and antiplatelet activity. Overall, young rangpur could be used as raw material to produce functional foods without producing any waste. © 2022 Society of Chemical Industry.


Assuntos
Citrus , Hesperidina , Anti-Inflamatórios/análise , Anti-Inflamatórios/farmacologia , Cromatografia Líquida de Alta Pressão/métodos , Cromatografia Líquida , Citrus/química , Frutas/química , Hesperidina/farmacologia , Extratos Vegetais/química , Espectrometria de Massas por Ionização por Electrospray/métodos
2.
Environ Res ; 191: 110106, 2020 12.
Artigo em Inglês | MEDLINE | ID: mdl-32882238

RESUMO

Studies in air pollution epidemiology are of paramount importance in diagnosing and improve life quality. To explore new methods or modify existing ones is critical to obtain better results. Most air pollution epidemiology studies use the Generalized Linear Model, especially the default version of R, Splus, SAS, and Stata softwares, which use maximum likelihood estimators in parameter optimization. Also, a smooth time function (usually spline) is generally used as a pre-processing step to consider seasonal and long-term tendencies. This investigation introduces a new approach to GLM, proposing the estimation of the free coefficients through bio-inspired metaheuristics - Particle Swarm Optimization (PSO), Genetic Algorithms, and Differential Evolution, as well as the replacement of the spline function by a simple normalization procedure. The considered case studies comprise three important cities of São Paulo state, Brazil with distinct characteristics: São Paulo, Campinas, and Cubatão. We considered the impact of particles with an aerodynamic diameter less than 10 µm (PM10), ambient temperature, and relative humidity in the number of hospital admissions for respiratory diseases (ICD-10, J00 to J99). The results showed that the new approach (especially PSO) brings performance gains compared to the default version of statistical software like R.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Transtornos Respiratórios , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Brasil/epidemiologia , Humanos , Modelos Lineares
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