Dietary Fatty Acid Composition Modulates Obesity and Interacts with Obesity‐Related Genes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The prevalence of obesity is skyrocketing worldwide. The scientific evidence has associated obesity risk with many independent factors including the quality of dietary fat and genetics. Dietary fat exists as the main focus of dietary guidelines targeting obesity reduction. To prevent/minimize the adipogenic effect of dietary fatty acids (FA), intakes of long-chain saturated- and trans-FA should be reduced and substituted with unsaturated FA. The optimal proportions of dietary unsaturated FA are yet to be defined, along with a particular emphasis on the need to achieve a balanced ratio of n-3:n-6 polyunsaturated FA and to increase monounsaturated FA consumption at the expense of saturated FA. However, inter-individual variability in weight loss in response to a dietary intervention is evident, which highlights the importance of exploring gene-nutrient interactions that can further modulate the risk for obesity development. The quality of dietary fat was found to modulate obesity development by interacting with genes involved in fatty acid metabolism, adipogenesis, and the endocannabinoid system. This review summarizes the current knowledge on the effect of the quality of dietary fat on obesity phenotype and obesity-related genes. The evidence is not only supporting the modulatory effect of fat quality on obesity development but also presenting a number of interactions between obesity-related genes and the quality of dietary fat. The identified gene-FA interaction may have a clinical importance and holds a promise for the possibility of using genetically targeted dietary interventions to reduce obesity risk in the future.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it