Garlic and cardioprotection: insights into the molecular mechanisms
Bibliographic record
Abstract
Garlic is widely recognized for its immense therapeutic potential. Garlic has been shown to exert its beneficial effects against a wide spectrum of diseases, including cancer, diabetes, and microbial infections, as well as immunological and cardiovascular disorders. Most of the research on garlic has indicated that garlic and its active compounds are effective in reducing cardiovascular and metabolic risk by normalizing abnormal plasma lipids, oxidized low density lipoproteins, abnormal platelet aggregation, high blood pressure, and cardiac injury. Some of the beneficial effects of dietary garlic against cardiovascular disorders are mediated via the generation of hydrogen sulfide and nitric oxide in cardiomyocytes and endothelial cells. Garlic has the potential to protect the heart against myocardial infarction, doxorubicin-induced cardiotoxicity, arrhythmia, hypertrophy, and ischemia-reperfusion injury. The induction of cardiac endogenous antioxidants and the reduction of lipid peroxidation by garlic has been reported by several different groups. Other mechanisms, such as regulating ion channels, modulating Akt signaling pathways, histone deacetylase inhibition, and cytochrome P450 inhibition, could be responsible for the cardioprotective effect of garlic. Although several mechanisms have been identified for the cardioprotective effect of garlic, there is a need for further research to identify the specific molecular mechanism of cardioprotection in different cardiac diseases.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".