Review of the role of dietary fiber in the prevention of colorectal cancer
Bibliographic record
Abstract
Colorectal cancer (CRC) is one of the most prevalent types of cancers, whose etiology has been highly related to diet. High intake of dietary fiber has been found to favor the reduction of CRC risk, as deduced from a lot of studies. The aim of this review is to explore the role of fiber in CRC chemoprevention and to provide insight into the mechanisms underlying the reduced risk of this neoplasia associated with the consumption of fiber. In this work, the authors describe the state of the literature regarding the association between intake and CRC risk through presenting data from epidemiological investigations, clinical intervention studies, and molecular mechanisms. Data were assembled from studies like the European Prospective Investigation into Cancer and Nutrition (EPIC) and fiber supplementation studies to assess the role of dietary fiber on CRC. The analysis indicated that dietary fiber intake, particularly from fruit, vegetable, and whole grain sources, is inversely related to CRC risk. Most studies, such as meta-analyses and large cohort studies, presented the significantly reduced CRC incidence of the highest intake of fiber. The favorable benefits of fiber are attributed to various modes of mechanisms, including the modulation of gut microbiota, bile acid metabolism, and a reduction in oxidative stress. Dietary fiber might play a vital role in this regard and lower the risk of CRC through its effects on different biological pathways. Promotion of dietary fiber intake could be a key strategy for the prevention of CRC, especially via a balanced diet rich in fruits, vegetables, and whole grains. Public health initiatives that aim at increasing fiber intake should start early in life to prevent not only metabolic but also neoplastic diseases more influenced by dietary factors. However, fiber supplementation appears promising, although further large-scale studies will be required to establish its definite role in CRC chemoprevention.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".