Anti-Obesity Effects of <i>Abeliophyllum distichum</i> Extracts via the AMPK Signaling Pathway in 3T3-L1 Adipocytes
Bibliographic record
Abstract
Obesity is a major public health concern because of its association with metabolic disorders (e.g., type 2 diabetes mellitus) and cardiovascular diseases.Natural compounds are increasingly being explored as safer alternatives to synthetic antiobesity drugs.In this study, the antiobesity effects of Abeliophyllum distichum extracts in 3T3-L1 adipocytes and their underlying mechanisms were investigated.Oil Red O staining was employed to assess the effects of A. distichum extracts on adipogenesis and lipid accumulation, and Western blot analysis and quantitative polymerase chain reaction were used to analyze the key molecular pathways were.Treatment with A. distichum extracts significantly inhibited lipid accumulation and suppressed the expression of adipogenic transcription factors, including peroxisome proliferator-activated receptor gamma, CCAAT/enhancer-binding protein alpha, and sterol regulatory element-binding protein 1c, at the protein and mRNA levels.Furthermore, treatment with A. distichum extracts activated AMP-activated protein kinase (AMPK) and enhanced the phosphorylation of acetyl-CoA carboxylase (ACC), which are key regulators of cellular energy metabolism, while reducing the total ACC expression.These findings indicate that A. distichum extracts exert antiobesity effects by modulating the AMPK signaling pathway and inhibiting adipogenesis.Given these significant bioactive properties, A. distichum extracts have promising application potential as a natural therapeutic agent for treating obesity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".