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Ursolic acid, a promising dietary bioactive compound of anti‐obesity (1045.40)

2014· article· en· W1543650637 on OpenAlexafffund
Yanwen Wang, Yonghan He

Bibliographic record

VenueThe FASEB Journal · 2014
Typearticle
Languageen
FieldMedicine
TopicAntioxidant Activity and Oxidative Stress
Canadian institutionsNational Research Council Canada
FundersCanadian Institutes of Health Research
KeywordsUrsolic acidAMPKAdipogenesisChemistryBeta oxidationProtein kinase AAdipose tissueBiochemistryPhosphorylationLipolysisEndocrinologyThermogenesisFatty acidInternal medicineBiologyMedicine

Abstract

fetched live from OpenAlex

Ursolic acid has recently been reported to possess a promising anti‐obesity effect. A number of studies have been conducted to elucidate the underlying mechanisms, which include the inhibition of pancreatic lipase activity, promotion of muscle hypertrophy, increase of brown fat, thermogenesis, energy expenditure, and lipolysis. Our recent study in 3T3‐L1 preadipocytes has demonstrated that ursolic acid inhibits cell differentiation and adipogenesis. This compound modulates the expression or activity of many proteins or enzymes involved in fat cell differentiation, fatty acid synthesis and oxidation. Further studies have shown that ursolic acid increases the phosphorylation and activity of AMPK and the protein expression of Sirt1. The anti‐adipogenic effect of UA can be reversed by AMPK siRNA but not Sirt1 inhibitor. Moreover, when LKB1 is silenced or inhibited, the effect of UA on AMPK activation diminishes. These results demonstrate that ursolic acid inhibits preadipocyte differentiation and adipogenesis through LKB1/AMPK pathway. While focusing on our recent report on the effect and mechanism of action of ursolic acid on fat cell differentiation and adipogenesis, other mechanisms related to energy and fat metabolism and body weight will be briefly discussed. Grant Funding Source : CIHR

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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.029
GPT teacher head0.279
Teacher spread0.249 · 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

Citations1
Published2014
Admission routes2
Has abstractyes

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