Polyphenol-Microbiota Interactions in Atherosclerosis: The Role of Hydroxytyrosol and Tyrosol in Modulating Inflammation and Oxidative Stress
Bibliographic record
Abstract
Atherosclerosis is a chronic inflammatory cardiovascular disease that may result from the interaction between oxidative stress, immune dysregulation, and metabolic disorders. Recent studies indicate that the well-known phenolic compounds, hydroxytyrosol (HTyr) and tyrosol (Tyr) present in extra virgin olive oil, confer cardioprotection through various mechanisms of action that include antioxidant, anti-inflammatory, and metabolic regulatory properties. The gut microbiota modulates the structure, bioavailability, and bioactivity of these phenolic compounds, thereby influencing their therapeutic potential. This review explores the intricate interactions between Tyr, HTyr, and gut microbiota within the context of atherosclerosis prevention and management. We explore how gut microbial metabolism can magnify or alter the biological effects of the Tyr and HTyr, and how interindividual differences in microbiota composition may influence their efficacy. A deeper understanding of these mechanisms could support the development of precision nutrition strategies aimed at reducing the risk of atherosclerosis.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".