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Record W4224940327 · doi:10.18280/ijdne.170220

Antioxidant Activity of Flavonoid Glycoside Extract of Solanum Betaceum on the Kidney of Wistar Rats

2022· article· en· W4224940327 on OpenAlexvenueno aff
Ida Ayu Raka Astiti Asih, Wiwik Susanah Rita, Wayan Suirta, Ahmad Fudholi

Bibliographic record

VenueInternational Journal of Design & Nature and Ecodynamics · 2022
Typearticle
Languageen
FieldMedicine
TopicPhytochemicals and Antioxidant Activities
Canadian institutionsnot available
FundersUniversitas Udayana
KeywordsFlavonoidGlycosideDPPHAntioxidantMalondialdehydeChemistryOxidative stressPharmacologySuperoxide dismutaseFood scienceBiochemistryTraditional medicineBiologyMedicineStereochemistry

Abstract

fetched live from OpenAlex

Flavonoid glycosides are a type of secondary metabolite that is one of the active chemicals in plants. The antioxidant efficacy of solanum betaceum flavonoid glycosides extract on malondialdehyde levels and superoxide dismutase activity in Wistar rat kidneys with maximum physical activity is the focus of this investigation. The DPPH technique was used to conduct an in vitro activity test. The in vivo test includes four treatment groups: control, stress, ethanol extract, and flavonoid glycoside extract group. Swimming almost one and a half hours every day for five days and being fed and drinking ad libitum is the treatment for stress conditions. Ethanol and flavonoids glycosides extract were given at doses of 50 mg/kg/BW/day respectively. In vitro test result with DPPH technique glycoside flavonoid extract was categorized as a strong antioxidant with an IC50 of 69.89 ppm. The intake of ethanol extract and flavonoid glycoside extract at a dose of 50 mg / Kg BW significantly lower MDA levels (p < 0.05), and can prevent oxidative stress through SOD in Wistar rat kidneys.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.267
Teacher spread0.253 · 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 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

Explore more

Same venueInternational Journal of Design & Nature and EcodynamicsSame topicPhytochemicals and Antioxidant ActivitiesFrench-language works237,207