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Record W3092629941 · doi:10.1039/d0fo00949k

Apigenin induced autophagy and stimulated autophagic lipid degradation

2020· article· en· W3092629941 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFood & Function · 2020
Typearticle
Languageen
FieldMedicine
TopicAutophagy in Disease and Therapy
Canadian institutionsNutrasource
FundersJilin University
KeywordsAutophagyApigeninDegradation (telecommunications)Cell biologyChemistryFlux (metallurgy)Lipid dropletBiochemistryBiologyFlavonoidApoptosisTelecommunications

Abstract

fetched live from OpenAlex

Apigenin, as a natural flavonoid, has been proved to have many biological effects. Our previous research has found the antiadipogenic effects of apigenin on HepG2 cells. Autophagy is intimately associated with the metabolism of lipid droplets (LDs) and is considered to be one of the lipid breakdown pathways. However, there is no study to elucidate the lipid-lowering mechanism of apigenin from the perspective of autophagy. Here, we investigated the possible role of apigenin in autophagy and lipid accumulation in palmitic acid (PA)-induced HepG2 cells. Our results showed that apigenin increased autophagosome formation and the LC3-II/I ratio, but decreased the p-mTOR/mTOR ratio and P62 protein expression. The effects of apigenin were blocked by chloroquine (CQ). Likewise, apigenin significantly stimulated autophagic flux in the cytoplasm. This effect also could be blocked by CQ. Moreover, apigenin decreased the lipid content and co-localization of LDs with LC3, and CQ could block these effects. Thus, we proposed that apigenin induced autophagy and stimulated autophagic lipid degradation in PA-treated HepG2 cells.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.628
Threshold uncertainty score0.603

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.039
GPT teacher head0.255
Teacher spread0.216 · 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