Cardiovascular protective effects of cinnamic acid as a natural phenolic acid: a review
Bibliographic record
Abstract
Phenolic acids derived from plants have beneficial effects on cardiovascular diseases (CVD). Cinnamic acid (CA) is a crucial phenolic acid that can form numerous hydroxycinnamic derivate found in many food groups. We review current data on the cardiovascular pharmacology of CA with a focus on CVD and their risk factors including hyperlipidaemia, obesity, hyperglycaemia, cardiomyopathy and myocardial ischaemia, vascular dysfunction, oxidative stress and inflammation. Both in vivo and in vitro laboratory studies demonstrate the lipid-lowering, anti-obesity, anti-hyperglycemic, cardio-protective and vasorelaxant activities of CA. The protective impacts of CA against CVD occur by inhibiting inflammatory, oxidative, and apoptotic pathways, regulating the genes and enzymes involved in glucose and lipid metabolisms, and promoting vasodilation. This review showed that the most studied and prominent effects of CA are anti-hyperlipidemic and anti-diabetic properties. In conclusion, intake of plant foods rich in CA may reduce CVD risk especially through regulating blood glucose and lipids levels.
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 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".