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Record W4402282518 · doi:10.26599/fmh.2025.9420029

Protective benefits and mechanisms of <i>Phyllanthus emblica</i> Linn. on aging induced by oxidative stress: a system review

2024· review· en· W4402282518 on OpenAlexaff
Na Wu, Yao Pan, Qi Liu, Fereidoon Shahidi, Hongyan Li, Fang Chen, Zeyuan Deng, Zhihong Zhang

Bibliographic record

VenueFood & medicine homology. · 2024
Typereview
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPhytochemistry and Bioactivity Studies
Canadian institutionsMemorial University of Newfoundland
FundersYouth Science Foundation of Jiangxi ProvinceHealth Commission of Jiangxi Province
KeywordsPhyllanthus emblicaOxidative stressChemistryTraditional medicineMedicinePharmacologyBiochemistry

Abstract

fetched live from OpenAlex

This review clarified the nutritional value of Phyllanthus emblica Linn. (PE) and summarized its application prospect as a health food which show anti-aging effects. This review highlighted the latest researches of PE to describe its anti-aging mechanism and related diseases induced by oxidative stress, as well as existing problems and future application directions. In general, PE is a fruit widely consumed in south of Asia, as well as one of the three medicinal plants been selected by the World Health Organization (WHO) for widespread cultivation. Polyphenols (including phenolics, flavonoid, tannins, etc.) are the main bioactive components in PE. Those bioactive compounds show anti-aging effects through scavenging free radicals, preventing mitochondrial damage, anti-triggering lipid peroxidation, and protecting protein structures. The development and research of nutritional foods derived from PE are limited, with most efforts focused on edible fruits and juice beverages. However, there is still significant potential for further high-value utilization of its nutritional properties focus on PE.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.179
GPT teacher head0.449
Teacher spread0.271 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreReview

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

Citations20
Published2024
Admission routes1
Has abstractyes

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