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Record W4286213186 · doi:10.1155/2022/4421828

Artichoke Leaf Extract‐Mediated Neuroprotection against Effects of Aflatoxin in Male Rats

2022· article· en· W4286213186 on OpenAlexafffund
Enas A. Ibrahim, Mokhtar I. Yousef, Doaa A. Ghareeb, Maria Augustyniak, John P. Giesy, Mourad A. M. Aboul‐Soud, Abeer El Wakil

Bibliographic record

VenueBioMed Research International · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicCynara cardunculus studies
Canadian institutionsUniversity of Saskatchewan
FundersAlexandria UniversityKing Saud UniversityDeanship of Scientific Research, King Saud UniversityCanada Research ChairsBaylor University
KeywordsAflatoxinAntioxidantOxidative stressBiologyJerusalem artichokeFood scienceTraditional medicineChemistryBiochemistryMedicine

Abstract

fetched live from OpenAlex

Attenuation of adverse effects of aflatoxin (AFB 1 ) in brains of B 1 rats by extracts of leaves of artichoke was studied. The active ingredients in extracts of leaves of artichoke, Cynara scolymus L., were determined by HPLC analysis. In the 42‐day experiment, rats were exposed to either sterile water, 4% DMSO, 100 mg artichoke leaf extract/kg body mass, 72 μ g aflatoxin B 1 /kg body mass, or AFB 1 plus artichoke leaf extract. Neurotoxicity of AFB 1 was determined by an increase in profile of lipids, augmentation of plasmatic glucose and concentrations of insulin, oxidative stress, increased activities of cholinergic enzymes, and a decrease in activities of several antioxidant enzymes and pathological changes in brain tissue. Extracts of artichoke leaf significantly reduced adverse effects caused by AFB 1 , rescuing most of the parameters to values similar to unexposed controls, which demonstrated that adverse, neurotoxic effects caused by aflatoxin B 1 could be significantly reduced by simultaneous dietary supplementation with artichoke leaf extract, which itself is not toxic.

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 score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.043
GPT teacher head0.302
Teacher spread0.259 · 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

Citations32
Published2022
Admission routes2
Has abstractyes

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Same venueBioMed Research InternationalSame topicCynara cardunculus studiesFrench-language works237,207