Attenuation of the development of hypercholesterolemic atherosclerosis by thymoquinone
Bibliographic record
Abstract
Thymoquinone (TQ), derived from Nigella sativa seed, is an antioxidant. The present study investigated whether TQ attenuates the development of atherosclerosis, and/or reduces the serum lipid levels and oxidative stress in rabbits. New Zealand white female rabbits were assigned to four groups of six animals each: group I, control; group II, 1% cholesterol diet; group III, 1% cholesterol plus TQ (10 mg/kg/day; through a nasogastric tube) diet; and group IV, 1% cholesterol plus TQ (20 mg/kg/day; through a nasogastric tube) diet. Blood samples were collected at baseline and after four and eight weeks on the experimental diets for measurement of serum lipids, total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), TC/HDL-C ratio and oxidative stress biomarkers (malondialdehyde [MDA] and protein carbonyls). At the end of the eight weeks, the aorta was removed for the assessment of atherosclerotic changes, MDA and protein carbonyls. Group II animals developed atherosclerosis (45%±11% of the intimal surface of aorta was covered with atherosclerotic plaques), which was associated with an increase in the serum TC, TG, LDL-C, HDL-C, TC/HDL-C, MDA and protein carbonyls. In group III, TQ decreased serum TC, LDL-C, MDA and protein carbonyls by 26%, 29%, 85% and 62%, respectively, and aortic MDA by 73%, which was associated with a 40% reduction of the development of aortic atherosclerosis. The higher dose of TQ in group IV had effects similar to the lower dose (group III), except that this dose further decreased serum TG. It is concluded that TQ attenuates hypercholesterolemic atherosclerosis and this effect is associated with a decrease in serum lipids and oxidative stress.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".