<i>n</i>-3 Polyunsaturated fatty acids throughout the cancer trajectory: influence on disease incidence, progression, response to therapy and cancer-associated cachexia
Bibliographic record
Abstract
Evidence from epidemiological studies suggests that diets rich in n-3 PUFA may be associated with reduced cancer risk. These observations have formed the rationale for exploring the mechanisms by which n-3 PUFA may be chemoprotective and have resulted in significant advances in our mechanistic understanding of n-3 PUFA action on tumour growth. Various interrelated and integrated mechanisms may be at work by which n-3 PUFA influence cancer at all stages of initiation, promotion, progression, and neoplastic transformation. More recently, experimental studies have reported enhanced tumour cell death with chemotherapy when fish oil is provided while toxic side effects to the host are reduced. Furthermore, cancer-associated wasting has been shown to be attenuated by fish oil supplementation. Clinical evidence suggests that the n-3 PUFA status of newly diagnosed cancer patients and individuals undergoing chemotherapy is low. Therefore, both the disease itself and therapeutic treatments may be contributing factors in the decline of n-3 PUFA status. Dietary supplementation to maintain and replenish n-3 PUFA status at key points in the cancer disease trajectory may provide additional health benefits and an enhanced quality of life. The present review will focus on and critically examine current research efforts related to the putative anti-cancer effects of n-3 PUFA and their suggested ability to palliate cancer-associated and treatment-associated symptoms.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".