Oxylipin regulation by phenolic compounds from coffee beverage: Positive outcomes from a randomized controlled trial in healthy adults and macrophage derived foam cells
Bibliographic record
Abstract
Oxylipins are considered biomarkers related to cardiovascular diseases (CVDs). They are generated in vivo via the oxygenation of polyunsaturated fatty acids as a result of oxidative stress and inflammation. Oxylipins are involved in vascular functions and are produced during foam cell formation in atherogenesis. Additionally, the consumption coffee is associated with the regulation on a particular oxylipin group, the F2t-isoprostanes (F2t-IsoPs). This function has been attributed to the chlorogenic acids (CGAs) from the coffee beverage. Considering the anti-inflammatory and antioxidant properties of CGAs, we evaluated the effects of two types of coffee that provided 787 mg CGAs/day (Coffee A) and 407 mg CGAs/day (Coffee B) by reducing 35 selected oxylipins in healthy subjects. Furthermore, we assessed the effect of CGAs on the cellular proatherogenic response in foam cells by using an oxidized LDL (oxLDL)-macrophage interaction model. After eight weeks of coffee consumption, the contents of 12 urine oxylipins were reduced. However, the effect of Coffee A showed a stronger decrease in IsoPs, dihomo-IsoPs, prostaglandins (PGs) and PG metabolites, probably due to its higher content of CGAs. Neither of the two coffees reduced the levels of oxLDL. Moreover, the in vitro oxylipin induction by oxLDL on foam cells was ameliorated by phenolic acids and CGAs, including the inhibition of IsoPs and PGs by caffeoylquinic and dicaffeoylquinic acids, respectively, while the phenolic acids maintained both antioxidant and anti-inflammatory activities. These findings suggest that coffee antioxidants are strong regulators of oxylipins related to CVDs. The clinical trial was registered on the International Clinical Trials Registry Platform, WHO primary registry (RPCEC00000168).
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".