Nonesterified Fatty Acids and Depression in Cancer Patients and Caregivers
Bibliographic record
Abstract
BACKGROUND: Nonesterified fatty acids (NEFAs) are known to have inflammatory effects. The inflammatory hypothesis of depression suggests that omega-3 (ω-3) and omega-6 (ω-6) fatty acids might be negatively and positively correlated with depression, respectively. OBJECTIVE: An exploratory study was conducted to determine the association between dietary free fatty acids and depressive symptoms in cancer patients and caregivers. METHODS: Associations between depression and the NEFA pool were investigated in 56 cancer patients and 23 caregivers using a combination of nonparametric tests and regularized regression. Plasma NEFAs were measured using thin layer and gas chromatography with flame ionization detection. Depression was characterized both as a continuous severity score using the GRID-Hamilton Depression Rating Scale (GRID Ham-D), and as a categorical diagnosis of major depression by structured clinical interview. RESULTS: -unsaturated fatty acid found in hydrogenated vegetable oils, was found to be negatively correlated with continuous depression scores in cancer patients. No significant associations were found in caregivers. CONCLUSIONS: An unexpected negative association between elaidic acid and depression was identified, supporting recent literature on the role of G protein-coupled receptors in depression. Further research is needed to confirm this result and to evaluate the potential role of G protein agonists as therapeutic agents for depression in cancer patients.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".