Extracts from Salvia-Nelumbinis naturalis alleviate hepatosteatosis via improving hepatic insulin sensitivity
Bibliographic record
Abstract
BACKGROUND: Salvia-Nelumbinis naturalis (SNN), initially called Jiangzhi Granula as a formulae of Chinese medicinal decoction, has been used clinically to treat non-alcoholic fatty liver disease (NAFLD) and related syndromes. The mechanism of SNN action is unknown. METHODS: HepG2 cells were cultured in lipid-rich media supplemented with chemical components of SNN. Male Wistar rats (6 weeks of age) were fed a high calorie diet (15% fat, 15% sucrose, and 2% cholesterol) for eight weeks, and then treated with SNN for four weeks. Body and liver weight, lipids profiles, insulin and glucose levels, glucose and insulin tolerance were evaluated, the mRNA and protein expression of insulin receptor (InsR), insulin receptor substrate (IRS) 1/2, protein kinase B (PKB/Akt), protein expression of suppressor of cytokine signaling 3 (SOCS3), protein kinase C epsilon (PKC ε) in liver tissue were analysed. RESULTS: Treatment with SNN components in lipid-laden HepG2 cells decreased lipid accumulation. Rats fed with a HC diet developed hepatosteatosis and accompanied hyperglycemia, hyperinsulinemia, hyperleptinemia, and diabetic dyslipidemia. Prolonged HC diet feeding resulted in parabolic response in plasma triglyceride (TG) concentrations, indicative of compromised hepatic production of TG-rich lipoproteins. HC diet feeding also resulted in impaired insulin sensitivity and hepatic insulin signalling. Administration of SNN extracts alleviated hepatosteatosis and conferred to a normolipoproteinemia profile in the HC diet-fed rats. The efficacy of SNN extract in improving liver function and insulin sensitivity was comparable to that of simvastatin or pioglitazone. The improved insulin signaling by SNN treatment was associated with increased IRS and Akt phosphorylation and decreased SOCS3 expression. However, SNN failed to inhibit the PKC ε expression in the liver. CONCLUSIONS: SNN is effective in reducing lipid accumulation in HepG2 cells and attenuating hepatosteatosis in HC diet-fed rats. Reduced hepatic lipid content in the rat liver was associated with improved insulin signalling.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 |
| 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".