Antioxidant Capacity of Myrciaria Cauliflora Seeds Extracts By Spectrophotometric, Biochemical and Electrochemical Methods Preferred Presentation
Notice bibliographique
Résumé
It is well known that fruit processing industries lead to the generation of large amounts of by-products every year, such as seeds and peels, which are frequently considered as waste. However, it has already been proved that these by-products can consist in a rich source of bioactive compounds with valuable nutritional and biological effects (1). In this perspective, there is a growing interest in the discovery of natural antioxidants which can be used as an alternative to synthetic substances by pharmaceutical and food industries (2). Jabuticaba (Myrciaria cauliflora) is a typical fruit from Brazil that belongs to Myrtaceae family. Its seeds are usually discarded as waste by industries and studies have already proven that these by-products are rich in bioactive compounds with promising biological effects (3,4). In this study, it was evaluated the antioxidant activity of hydroalcoholic (EtOH), methanolic (MEtOH), aqueous (AQ) and propanone (AQAc) extracts from jabuticaba seeds. This effect was assessed by their ability to scavenge 2,2-diphenyl-1-picrylhydrazyl (DPPH•), 2,2’-azino-bis (ethylbenzothiazoline-6-sulfonic acid) (ABTS•+), hypochlorous acid (HOCl), and superoxide anion (O2 •−) radicals. The redox properties of jabuticaba seed extracts were studied by using differential pulse voltammetry (DPV). Their protective effect to prevent in vitro oxidative cellular damages induced by 2,2-azobis(2-aminopropanone) dihydrochloride (AAPH) in human erythrocytes was also investigated. The obtained results revealed that all extracts were able to scavenge free radicals used in this work, due to their lower IC50 (inhibitory concentration) values. A similarity between E pa values suggested that the extracts were constituted by analogous electroactive species and exhibited similar antioxidant effect in this assay. However, it was observed that the AQAc extract presented the lowest E pa value (115.1 ± 0.95 mV) indicating a higher antioxidant activity when compared to the other extracts (p < 0.05). Furthermore, it was showed a good positive correlation between the results obtained by using DPV and the synthetic and biological radicals (DPPH•: r = 0.8215; ABTS•+: r = 0.9123; HOCl: r = 0.8193, and O2 •-: r = 0.9916). The extracts protected human erythrocytes against oxidative cellular damage caused by AAPH, which was confirmed by using field-emission gun scanning electron microscopy (FESEM) analysis. Taken together, the results reported in this work evidence that jabuticaba seeds are a source of antioxidant compounds that present a remarkable potential to prevent damage related to oxidative stress in biological systems. In this way, our work suggests the use of this fruit byproduct in further biochemical studies aiming its use as a new nutraceutical and food additive. References Fierascu RC, Sieniawska E, Ortan A, Fierascu I, Xiao J. Fruits By-Products – A Source of Valuable Active Principles. A Short Review. Frontiers in Bioengineering and Biotechnology. 2020;8:1–8. Villacís-Chiriboga J, Elst K, Camp J van, Vera E, Ruales J. Valorization of byproducts from tropical fruits: Extraction methodologies, applications, environmental, and economic assessment: A review (Part 1: General overview of the byproducts, traditional biorefinery practices, and possible applications ). Comprehensive Reviews in Food Science and Food Safety. 2020;19:405–47. Hacke ACM, Granato D, Maciel LG, Weinert PL, do Prado-Silva L, Alvarenga VO, et al. Jabuticaba (Myrciaria cauliflora) Seeds: Chemical Characterization and Extraction of Antioxidant and Antimicrobial Compounds. Journal of food science. 2016;81(9). Fidelis M, do Carmo MA v, Azevedo L, Cruz TM, Marques MB, Myoda T, et al. Response surface optimization of phenolic compounds from jabuticaba (Myrciaria cauliflora [Mart.] O.Berg) seeds: Antioxidant, antimicrobial, antihyperglycemic, antihypertensive and cytotoxic assessments. Food and Chemical Toxicology. 2020;142.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».