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Record W4229367676 · doi:10.1111/jfbc.14222

Antioxidant capacity of<i>Myrciaria cauliflora</i>seed extracts by spectrophotometric, biochemical, and electrochemical methods and its protective effect against oxidative damage in erythrocytes

2022· article· en· W4229367676 on OpenAlexaff
Ana Carolina Mendes Hacke, Taynara Pacheco Valério, Mateus Flórido Cubo, Dhésmon Lima, Christiana Andrade Pessôa, José Carlos Rebuglio Vellosa, Romaiana Picada Pereira

Bibliographic record

VenueJournal of Food Biochemistry · 2022
Typearticle
Languageen
FieldMedicine
TopicPhytochemicals and Antioxidant Activities
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsAntioxidantChemistryABTSOxidative stressDPPHLipid peroxidationFood scienceReactive oxygen speciesFunctional foodOxidative phosphorylationBiochemistryAntioxidant capacity

Abstract

fetched live from OpenAlex

This study aimed to investigate the antioxidant activity of extracts obtained from jabuticaba (Myrciaria cauliflora) seeds. Ethanolic (ETJS), methanolic (MEJS), aqueous (AQJS), and propanone (PRJS) extracts was assessed by measuring spectrophotometrically their ability to scavenge DPPH·, ABTS·+, HOCl, and O2·− radicals. Electrochemical methods were employed, and the obtained data presented a good correlation with the radical scavenging results. The extracts were also able to attenuate lipid peroxidation induced by Fe2+ ions in phospholipids due to their chelation ability. The extracts protected human erythrocytes against oxidative cellular damage caused by AAPH, which was confirmed by using FESEM analysis. PRJS extract demonstrated the highest effect in all assays used in this work. Our findings prove that jabuticaba seeds are an important source of antioxidants which act by different mechanisms. This study opens new frontiers regarding the use of this fruit byproduct as a food additive. Practical applications Jabuticaba seeds are usually discarded as waste by food industries, but they are rich in bioactive products and present interesting biological properties. Herein, we demonstrated that their extracts show remarkable antioxidant power against different reactive oxygen species, which are involved in several human pathologies. In this way, this by-product can be further used in the development of products to protect the human body against diseases related to oxidative stress.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.279
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2022
Admission routes1
Has abstractyes

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