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Record W2979721448 · doi:10.3390/foods8100471

Phenolic Profile and Antioxidant Activity of the Edible Tree Peony Flower and Underlying Mechanisms of Preventive Effect on H2O2-Induced Oxidative Damage in Caco-2 Cells

2019· article· en· W2979721448 on OpenAlexafffund
Jinle Xiang, Chengbo Yang, Trust Beta, Shangxi Liu, Runqiang Yang

Bibliographic record

VenueFoods · 2019
Typearticle
Languageen
FieldMedicine
TopicPhytochemicals and Antioxidant Activities
Canadian institutionsUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship CouncilUniversity of Manitoba
KeywordsAntioxidantSuperoxide dismutaseFlavonoidBiochemistryOxidative stressCalyxKaempferolBiologyGlutathioneChemistryGlutathione peroxidaseBotanyFood scienceEnzyme

Abstract

fetched live from OpenAlex

The entire phenolic profiles and antioxidant activities of different organs of the edible tree peony flowers (Fengdan Bai (FDB)) were analyzed. HPLC-quadrupole time-of-flight mass spectrometer (Q-TOF-MS/MS) analyses of individual phenolic compounds revealed that the petal and stamen contained higher levels of flavonoid glycosides than other organs (p < 0.05). Kaempferol-3,7-di-O-glucoside was the dominant flavonoid in these two organs, however, the calyx and ovary contained higher contents of gallic acid derivatives than other organs (p < 0.05). Hexa-O-galloyl-glucose was the dominant species in the calyx and ovary. At the same concentration of total phenolic extract (TPE), the stamen had the highest protection effect on Caco-2 cell oxidative damage induced by H2O2. The antioxidant effect was attributed to potent antioxidant capability; restored redox state due to the increased expression of glutathione peroxidase (GSH-Px) and superoxide dismutase (SOD); and improved barrier function of Caco-2 cell owing to increased zonula occludens-1 (ZO-1), CLDN3 (Claudin 3), and occludin mRNA expression. As a new resource food, the edible tree peony flower is a potential functional food material and natural antioxidants resource.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.127
Threshold uncertainty score0.462

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 head0.016
GPT teacher head0.270
Teacher spread0.255 · 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

Citations59
Published2019
Admission routes2
Has abstractyes

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