Experimental and clinical research findings on the cardiovascular benefits of consuming flaxseed
Bibliographic record
Abstract
Functional foods and nutraceuticals are becoming popular alternatives to pharmacological treatments by providing health benefits and (or) reducing the risk of chronic diseases. Flaxseed is a rich source of 3 components with demonstrated cardioprotective effects: the omega-3 fatty acid alpha-linolenic acid (ALA), dietary fibre, and phytoestrogen lignans. Multiple clinical dietary intervention trials report that consuming flaxseed daily can modestly reduce circulating total cholesterol (TC) by 6%-11% and low-density lipoprotein (LDL) cholesterol by 9%-18% in normolipemic humans and by 5%-17% for TC and 4%-10% for LDL cholesterol in hypercholesterolemic patients, as well as lower various markers associated with atherosclerotic cardiovascular disease in humans. Evidence to date suggests that the dietary fibre and (or) lignan content of flaxseed provides the hypocholesterolemic action. The omega-3 ALA found in the flaxseed oil fraction also contributes to the antiatherogenic effects of flaxseed via anti-inflammatory and antiproliferative mechanisms. Dietary flaxseed may also protect against ischemic heart disease by improving vascular relaxation responses and by inhibiting the incidence of ventricular fibrillation.
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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".