Purple sweet potato anthocyanin extract regulates redox state related to gut microbiota homeostasis in obese mice
Bibliographic record
Abstract
This study explored the advantageous effects of purple sweet potato anthocyanin extract (PSPAE) on redox state in obese mice. The normal chow diet (NCD) group, high-fat/cholesterol diet (HCD) group, and three groups based on HCD and added with low, middle, and high dose of PSPAE (PAL, PAM, and PAH) were raised for 12 weeks. High dose of PSPAE treatment decreased the elevations of the body weight by 24.7%, serum total cholesterol by 48.3%, serum triglyceride by 42.4%, and elevated serum activities of glutathione peroxidase by 53.3%, superoxide dismutase by 57.8%, catalase by 75.4%, decreased serum contents of malondialdehyde by 27.1% and lipopolysaccharides by 40.5%, as well as increased caecal total short-chain fatty acid by 2.05-fold. Additionally, PSPAE depressed toll-like receptor 4 (TLR-4), nuclear factor kappa-B (NF-κB), interleukin 6, tumor necrosis factor α, and preserved nuclear factor erythroid-2-related factor 2 (Nrf2) gene expression. Similarly, the protein expression of Nrf2 was enhanced, while TLR-4 and p-NF-κB/NF-κB were depressed by PSPAE treatment. Moreover, PSPAE administration promoted the protection of intestinal barrier function and rebuilt gut microbiota homeostasis by blooming g_Akkermansia, g_Bifidobacterium, and g_Lactobacillus. Furthermore, antibiotic interference experiments showed that the gut microbiota was indispensable for preserving the redox state of PSPAE. These results suggested that PSPAE administration could be an opportunity for improving HCD-induced obesity and the redox state related to gut dysbiosis. PRACTICAL APPLICATION: Purple sweet potato anthocyanin has diverse pharmacological properties. It is applicable for individuals to consume extracts (as pills or other forms) from raw purple sweet potato if they want to improve obesity or redox state.
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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) | 0.000 | 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 | 0.001 |
| 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".