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Record W2890398105 · doi:10.3390/molecules23092328

Antioxidant Activity and Neuroprotective Activity of Stilbenoids in Rat Primary Cortex Neurons via the PI3K/Akt Signalling Pathway

2018· article· en· W2890398105 on OpenAlexaff
Haichao Wen, Zheng Qing Fu, Yangji Wei, Xiaoxu Zhang, Liyan Ma, Liwei Gu, Jingming Li

Bibliographic record

VenueMolecules · 2018
Typearticle
Languageen
FieldMedicine
TopicSirtuins and Resveratrol in Medicine
Canadian institutionsMcGill University Health Centre
FundersSpecial Fund for Agro-scientific Research in the Public InterestNational Natural Science Foundation of China
KeywordsNeuroprotectionChemistryNeurotoxicityProtein kinase BAntioxidantPI3K/AKT/mTOR pathwayReactive oxygen speciesResveratrolBiochemistryPharmacologyStereochemistryPhosphorylationSignal transductionBiologyOrganic chemistryToxicity

Abstract

fetched live from OpenAlex

-3',4',3,5-tetrahydroxy-stilbene (piceatannol, PIC), against β-amyloid (Aβ)-induced neurotoxicity in rat primary cortex neurons were evaluated. THS, RES, and PIC significantly scavenged DPPH• and •OH radicals. All three stilbenoids were able to inhibit Aβ neurotoxicity by decreasing intracellular reactive oxygen species (ROS) via the PI3K/Akt signalling pathway. Specifically, stilbenoids significantly promoted Akt phosphorylation; suppressed Bcl-2/Bax expression; and inhibited caspase-9, caspase-3, and PARP cleavage. Molecular docking between stilbenoids with Akt indicated that stilbenoids could form hydrogen bond interactions with the COOH-terminal region of Akt. Additionally, the neuroprotective activity of stilbenoids correlated with the number and position of hydroxyl groups. The lack of meta-dihydroxyl groups on THS did not affect its neuroprotective activity in comparison with RES, whereas the ortho-dihydroxyl moiety on PIC significantly enhanced neuroprotective activity. These results provide new insights into the correlation between the biological activity and chemical structure of stilbenoids.

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 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 score0.557
Threshold uncertainty score0.511

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 studies0.0000.001
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 head0.011
GPT teacher head0.243
Teacher spread0.232 · 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 teacher head, 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

Citations38
Published2018
Admission routes1
Has abstractyes

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