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Record W3135027073 · doi:10.1002/fsn3.2176

Hypoglycemic effect of <i>Taraxacum officinale</i> root extract and its synergism with <i>Radix Astragali</i> extract

2021· article· en· W3135027073 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 Science & Nutrition · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMetabolism, Diabetes, and Cancer
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsDandelionTaraxacum officinaleTraditional medicineRadix (gastropod)FlavonoidChemistryAmylaseFood scienceBiologyBotanyMedicineBiochemistryEnzymeAntioxidantTraditional Chinese medicine

Abstract

fetched live from OpenAlex

Abstract Taraxacum officinale (dandelion) and Radix Astragali are traditional medicinal and edible plants with high nutritional value. In this study, the synergistic hypoglycemic effect of DRE and Radix Astragali extract (RAE) was evaluated. Our results showed that water extract of dandelion (DRE‐w), mainly containing polysaccharides (63.92 ± 1.82 mg/g), total flavonoid (2.57 ± 0.06 mg/g), total phenolic compounds (8.93 ± 0.34 mg/g), and saponins (0.54 ± 0.05 mg/g), exhibited significantly inhibitory effect on α‐glucosidase and α‐amylase. DRE‐w and RAE had synergistic hypoglycemic effect; we found that DRE‐w and its combination with RAE could relieve the state of insulin resistance in IR‐HepG2 cells. The combination could more significantly increase the glucose consumption and intracellular glycogen content, and improve the activity of hexokinase and pyruvate kinase in IR‐HepG2 cells. In summary, DRE and its combination with RAE can be developed as the drugs or functional foods for diabetes prevention and treatment.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.121
Threshold uncertainty score0.655

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 head0.007
GPT teacher head0.232
Teacher spread0.226 · 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