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Record W3194919879 · doi:10.1002/fsn3.2534

Effect of pinolenic acid on oxidative stress injury in HepG2 cells induced by H<sub>2</sub>O<sub>2</sub>

2021· article· en· W3194919879 on OpenAlexaff
Yang Zhao, Sainan Liu, Zhili Sheng, Xue Li, Yanan Chang, Weichang Dai, Sui Kiat Chang, Junmei Liu, Yuchun Yang

Bibliographic record

VenueFood Science & Nutrition · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomics, phytochemicals, and oxidative stress
Canadian institutionsMinistry of Agriculture
FundersNational Key Research and Development Program of China
KeywordsOxidative stressSuperoxide dismutaseIntracellularCatalaseMalondialdehydeReactive oxygen speciesAntioxidantChemistryGlutathione peroxidaseMolecular biologyGlutathioneBiochemistryGene expressionEnzymeGeneBiology

Abstract

fetched live from OpenAlex

Abstract To investigate the effect and mechanism of pinolenic acid (PNA) on H2O2‐induced oxidative stress injury in HepG2 cells. Methods: PNA was used to regulate oxidative stress injury of HepG2 cells induced by H2O2. Quantification of cell survival rate, accumulation of intracellular reactive oxygen species (ROS), and expression levels of anti‐oxidation‐related genes were determined using MTT, fluorescent probe technology (DCFH‐DA), and real‐time quantitative reverse transcription polymerase chain technology (qRT‐PCR) method, respectively. Meanwhile, the activity of intracellular antioxidant enzymes was determined by biochemical methods. The results showed that PNA improved the survival rate of HepG2 cells induced by H2O2 (29.59%, high‐dose group), reduced the accumulation of intracellular ROS (65.52%, high‐dose group), and reduced the level of intracellular malondialdehyde (MDA; 65.52%, high‐dose group). All these results were dose‐dependent, which indicated that PNA can improve oxidative stress damage of cells. Furthermore, the mechanism of PNA regulating oxidative stress was investigated from the gene level. Results showed that under supplementation of PNA, the activity of superoxide dismutase (SOD), catalase (CAT), and glutathione peroxidase (GSH‐Px) had been improved (39.74%, 17.58%, and 23.83%, high‐dose group). Further studies on gene expression which controls the activity of antioxidant enzymes showed that under the regulation of PNA, the expression level of Keap1 gene was decreased, while Nrf2 gene was increased. The expression levels of HO‐1 and NQO1 in the downstream of Nrf2 were increased. Results indicated that under the regulation of PNA, Nrf2 was separated from Keap1, entered the nucleus, bound to ARE, and up‐regulated the expression levels of HO‐1 and NQO1 genes. Conclusion: PNA has a conspicuous improvement effect on oxidative stress damage induced by H2O2 in HepG2 cells. We also found the antioxidant mechanisms of PNA where it protected cells from oxidative stress damage by causing nuclear translocation of Nrf2 gene and up‐regulated the expression levels of antioxidant enzymes in the downstream. This shows that PNA prevented oxidative stress by mediating the Keap1/Nrf2 transcriptional pathway and down‐regulating enzyme activities.

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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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

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 head0.007
GPT teacher head0.242
Teacher spread0.235 · 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

Citations23
Published2021
Admission routes1
Has abstractyes

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