Bibliographic record
Abstract
PURPOSE OF REVIEW: n-3 polyunsaturated fatty acids, eicosapentaenoic acid and docosahexaenoic acid have been implicated as potential mediators in pathways involved in cancer cachexia. This review summarizes recent findings on the n-3 fatty acid status of patients with cancer, the effects of n-3 fatty acid supplementation on weight and lean body mass and the potential role of supplementation during antineoplastic therapy. RECENT FINDINGS: Due to suboptimal intakes and possible metabolic disturbances, physiological concentrations of n-3 fatty acids are low in patients with cancer. Low n-3 fatty acids are associated with loss of skeletal muscle, suggesting a need for supplementation. Recent trials have shown an effect of n-3 supplementation throughout antineoplastic therapy on weight, lean body mass and treatment outcomes. Attenuation or gain of weight and lean body mass was reported and the first clinical trials of n-3 fatty acids as an adjuvant to chemotherapy treatment suggest improved efficacy and milder treatment toxicity with n-3 fatty acid supplementation. SUMMARY: Recent evidence appears to favour providing n-3 fatty acids early in the disease trajectory, during antineoplastic therapy for preservation of muscle and also to improve treatment tolerance. Additional, larger trials are needed to define these relationships further but it appears that fish oil has broad therapeutic potential in patients with cancer.
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) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| 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) | 0.009 | 0.004 |
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".