Attenuation of hepatic steatosis by purple sweet potato colour is associated with blocking Src/ERK/C/EBPβ signalling in high-fat-diet–treated mice
Bibliographic record
Abstract
Our previous work showed that purple sweet potato colour (PSPC), a class of naturally occurring anthocyanins, effectively improved hepatic glucose metabolic dysfunction in high-fat-diet (HFD)–treated mice. This study investigated the effects of PSPC on HFD-induced hepatic steatosis and the signalling events associated with these effects. Mice were divided into 4 groups: control group, HFD group, HFD+PSPC group, and PSPC group. PSPC was administered daily for 20 weeks at oral doses of 700 mg/(kg·day)−1). Our results showed that PSPC significantly improved obesity and related metabolic parameters, as well as liver injury in HFD-treated mice. Moreover, PSPC dramatically attenuated hepatic steatosis in HFD-treated mice. PSPC markedly prevented oxidative stress-mediated Src activation in HFD-treated mouse livers. Furthermore, PSPC feeding remarkably suppressed mitogen-activated protein kinase kinase/extracellular-signal-regulated kinase (MEK/ERK) signalling and consequent CCAAT/enhancer binding protein β (C/EBPβ) activation and restored AMPK activation in HFD-treated mouse livers, which was confirmed by U0126 treatment. Ultimately, PSPC feeding dramatically reduced protein expression of FAS and CD36 and the activation of ACC, and increased the protein expression of CPT1A in the livers of HFD-treated mice, indicating decreased lipogenesis and fatty acid uptake and enhanced fatty acid oxidation. In conclusion, PSPC exhibited beneficial effects on hepatic steatosis, which were associated with blocking Src and C/EBPβ activation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".