Conjugated Fatty Acids in Muscle Food Products and Their Potential Health Benefits: A Review
Bibliographic record
Abstract
Conjugated fatty acids (CFAs) are a group of positional and geometric isomers of polyunsaturated fatty acids (PUFAs) with conjugated double bonds. There are several subgroups of CFAs including conjugated linoleic acids (CLAs), conjugated linolenic acids (CLNAs), conjugated eicosapentaenoic acids (CEPAs), and conjugated docosahexaenoic acids (CDHAs). CFAs, especially CLAs, have been studied in recent years both for their health benefits and factors that affect their level in muscle food products. CFAs have been reported in numerous studies as having antitumor, antiobesity, antidiabetes, anticardiovascular disease, and modulating immune system effects. These biological activies are involved in changes of lipid peroxidation and energy expenditure, as well as inhibitory effects on the hormone receptor, lipid metabolism, lipoprotein lipase activity, and adiponectin production. A large body of studies has revealed that the diet, processing, storage conditions, slaughter season, and age are common factors that affect CFA content in muscle food products, as detailed in this review. Recommendations are made regarding animal farming and meat product processing to obtain high CFA content meat products and to optimize the benefits of CFA for health promotion.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".