Therapeutic effects of Nigella sativa on chronic HAART-induced hyperinsulinemia in ratsThis article is one of a selection of papers from the NATO Advanced Research Workshop on Translational Knowledge for Heart Health (published in part 2 of a 2-part Special Issue).
Bibliographic record
Abstract
Prolonged use of highly active antiretroviral therapy (HAART) is associated with insulin resistance in HIV-1-positive patients. Small animal models that recapitulate the long-term effects of HAART may facilitate the identification of therapeutic agents to suppress these side effects. We investigated the protective effects of black seed oil (BSO) from Nigella sativa in Sprague-Dawley rats treated with a daily HAART regimen for 7 months. The antiretroviral drugs, consisting of nelfinavir (200 mg/kg), zidovudine (50 mg/kg), and efavirenz (20 mg/kg), were mixed with diet with or without BSO (400 microL/kg) supplementation. Significant increases in insulin and C-peptide levels were observed in HAART-treated groups, and concomitant BSO treatment reduced this hyperinsulinemia. Interestingly, HAART-treated rats showed reduced size of pancreatic islets that was not seen in BSO-exposed rats. In vitro studies showed that nelfinavir, alone and in combination with HAART, induced oxidative stress and decreased glucose-induced insulin production in INS-1 cells. Suppressed insulin production was restored in cells coexposed to either BSO or thymoquinone. Our findings demonstrated that chronic HAART may increase serum insulin levels by dysregulating both insulin production by beta cells and insulin action at the periphery. These deleterious effects may be prevented by dietary supplementation with BSO.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| 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 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".