Roselle supplementation prevents nicotine-induced vascular endothelial dysfunction and remodelling in rats
Bibliographic record
Abstract
Vascular endothelial dysfunction (VED) plays an important role in the initiation of cardiovascular diseases. Roselle, enriched with antioxidants, demonstrates high potential in alleviating hypertension. This study was undertaken to investigate the effects of roselle supplementation of VED and remodelling in a rodent model with prolonged nicotine administration. Male Sprague–Dawley rats (n = 6 per group) were administered with 0.6 mg/kg nicotine for 28 days to induce VED. The rats were given either aqueous roselle (100 mg/kg) or normal saline orally 30 min prior to nicotine injection daily. One additional group of rats served as control. Thoracic aorta was isolated from rats to measure vascular reactivity, vascular remodelling and oxidative stress. Roselle significantly lowered aortic sensitivity to phenylephrine-induced vasoconstriction (Endo-(+) Cmax = 234.5 ± 3.9%, Endo-(–) Cmax = 247.6 ± 5.2%) compared with untreated nicotine group (Endo-(+) Cmax = 264.5 ± 6.9%, Endo-(–) Cmax = 276.5 ± 6.8%). Roselle also improved aortic response to endothelium-dependent vasodilator, acetylcholine (Endo-(+) Rmax = 73.2 ± 2.1%, Endo-(–) Rmax = 26.2 ± 0.8%) compared to nicotine group (Endo-(+) Rmax = 57.8 ± 1.7%, Endo-(–) Rmax = 20.9 ± 0.8%). In addition, roselle prevented an increase in intimal media thickness and elastic lamellae proliferation to preserve vascular architecture. Moreover, we also observed a significantly lowered degree of oxidative stress in parallel with increased antioxidant enzymes in aortic tissues of the roselle-treated group. This study demonstrated that roselle prevents VED and remodelling, and as such it has high nutraceutical value as supplement to prevent cardiovascular diseases.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".