Garlic extracts prevent oxidative stress, hypertrophy and apoptosis in cardiomyocytes: a role for nitric oxide and hydrogen sulfide
Bibliographic record
Abstract
BACKGROUND: In ancient times, plants were recognized for their medicinal properties. Later, the arrival of synthetic drugs pushed it to the backstage. However, from being merely used for food, plants are now been widely explored for their therapeutic value. The current study explores the potential of skin and flesh extracts from a hard-necked Rocambole variety of purple garlic in preventing cardiomyocyte hypertrophy and cell death. METHODS: Norepinephrine (NE) was used to induce hypertrophy in adult rat cardiomyocytes pretreated with garlic skin and flesh extracts. Cell death was measured as ratio of rod to round shaped cardiomyocytes. Fluorescent probes were used to measure apoptosis and oxidative stress in cardiomyocytes treated with and without extracts and NE. Pharmacological blockade of nitric oxide (NO) and hydrogen sulfide (H₂S) were used to elucidate the mechanism of action of garlic extracts. Garlic extract samples were also tested for alliin and allicin concentrations. RESULTS: Exposure of cardiomyocytes to NE induced an increase in cell size and cell death; this increase was significantly prevented upon treatment with garlic skin and flesh extracts. Norepinephrine increased apoptosis and oxidative stress in cardiomyocytes which was prevented upon pretreatment with skin and flesh extracts; NO, and H₂S blockers significantly inhibited this beneficial effect. Allicin and alliin concentration were significantly higher in garlic flesh extract when compared to the skin extract. CONCLUSION: These results suggest that both skin and flesh garlic extracts are effective in preventing NE induced cardiomyocyte hypertrophy and cell death. Reduction in oxidative stress may also play an important role in the anti-hypertrophic and anti-apoptotic properties of garlic extracts. These beneficial effects may in part be mediated by NO and H₂S.
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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) | 0.000 | 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) | 0.001 | 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".