Curcumin supplementation ameliorated vascular dysfunction and improved antioxidant status in rats fed a high-sucrose, high-fat diet
Bibliographic record
Abstract
Vascular endothelial dysfunction is a potential risk factor for cardiovascular disease. This study evaluated the effect of curcumin on factors associated with vascular dysfunction using rats fed a high-sucrose, high-fat (HSF) diet. The experiment included 2 animal feeding phases. In the first feeding phase, male Sprague-Dawley rats were randomly divided into 2 groups: the control group (n = 8) was fed a standard diet (AIN-93G) and the HSF group (n = 24) was fed an HSF diet for 8 weeks to induce obesity. In the second feeding phase, lasting 4 weeks, the HSF group was randomly divided into 3 subgroups: the O group (n = 8) continued feeding on the HSF diet, the OA group (n = 8) had the HSF diet replaced with AIN-93G, and the OC group (n = 8) was fed the HSF diet supplemented with curcumin (300 mg/kg body weight daily). After 8 weeks, the HSF diet significantly elevated levels of aspartate aminotransferase (AST), alanine aminotransferase (ALT), insulin, homeostatic model assessment insulin resistance (HOMA-IR), low-density lipoprotein cholesterol (LDL-C), homocysteine (Hcy), C-reactive protein (CRP), vascular cell adhesion molecule 1 (VCAM-1), and intercellular adhesion molecule 1 (ICAM-1) but significantly reduced levels of nitric oxide (NO) and high-density lipoprotein cholesterol (HDL-C). After dietary intervention, the OA and OC groups exhibited significantly lower levels of AST, ALT, HOMA-IR, cholesterol, LDL-C, Hcy, CRP, VCAM-1, and ICAM-1 and higher levels of NO and catalase (CAT) activity compared with the O group. Superoxide dismutase, CAT, and glutathione peroxidase activities were increased in the OA group, while CAT levels were enhanced in the OC group. In conclusion, this study showed that curcumin supplementation and diet modification can inhibit HSF diet-induced vascular dysfunction potentially by enhancing NO production and antioxidant enzyme activities, thereby suppressing inflammation and oxidative damage in the vascular endothelium.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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".