Curcuma longa on the Metabolic Profile and Atherogenic Index of Rats Fed with a Hyper Caloric Diet
Bibliographic record
Abstract
The chronic diseases such as diabetes mellitus, metabolic syndrome and cardiovascular diseases have reached epidemic proportions in developed and developing countries. The high costs of the allopathic medicines represent a growing demand for non-allopathic alternatives. Curcuma longa is usually used as a spice in curries and as a dietary pigment and is considered a medicinal plant due important properties, with anti-inflammatory, anti-oxidant, anti-bacterial and anti-tumor action.The aim of this work was to evaluate the effects of Curcuma longa on the metabolic profile of Wistar rats treated with hyper caloric diet. Forty eight male rats were divided randomly into 4 groups (n=12) and treated for 40 days: G1 that received water (Control Group); G2 that received condensed milk solution ad libitum; G3 that received C. longa by gavage route and G4 that received condensed milk solution ad libitum and C. longa by gavage route. No significant differences for body weight and cholesterol were observed among the groups. Visceral fat, triglycerides and glycaemia were higher in the groups treated with condensed milk but did not differ when comparing G1 with G3 and G2 with G4. Analyzing our results it is possible to say that C. longa may not be efficient to promote benefits in lipid and glycemic profile as well as in the body weight and visceral fat of animals treated with hyper caloric diet.
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 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 | 0.000 | 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) | 0.000 | 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".