ANTI-HYPERLIPIDEMIC ACTIVITY OF Hibiscus sabdariffa FLOWER BUDS IN TRITON-X100 INDUCED HYPERLIPIDEMIA IN RATS
Bibliographic record
Abstract
The purpose : The current study was planned to assess Anti-hyperlipidemic action of Hibiscus sabdariffa ehanolic flower buds extract in Triton X 100 induced Hyperlipidemia in Rats. Mehod: Here Triton X-100 (100 mg/kg,i.p)induced Hyperlipidemia model is used.In this model the animals were divided into 5groups, in which 6 rats were used in each group. First group considered as , normal, 2nd control, 3rd as standard, 4th and 5th are considered as tested groups.In this method, Triton x-100 (100mg/kg)is induced to 4 groups except normal group. Rats in 4th and 5th groups were treated with an ethanolic flower bud extract of Hibiscus sabdariffa (EEHS) 200 and 400(mg/kg/p.o) for 7 days. On 8th day blood was collected by retro orbital sinus puncture,under mild ether anaesthesia.The collected blood samples were centrifuged for 10mins at 2000 rpm and serum samples collected were used for various lipid profile tests. Results: It is found that treatment with ethanolic flower buds extract of Hibisus sabdariffa (EEHS)essentially diminished the hyperlipidemia i.e diminished degrees of serum Total Cholesterol, Triglycerides, Low Density Lipoprotein Cholesterol (LDL-C), Very Low Density Lipoprotein Cholesterol (VLDL-C) , and increment of serum High Density Lipoprotein Cholesterol (HDL-C) when contrasted with vehicle control and standard medication Atorvastatin (10 mg/kg). Conclusion The outcomes exhibited that ethanolic extract of Hibiscus sabdariffa buds had critical antihyperlipidemic action.
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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 | 0.000 |
| 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".