A study protocol to investigate the relationship between dietary fibre intake and fermentation, colon cell turnover, global protein acetylation and early carcinogenesis: the FACT study
Bibliographic record
Abstract
BACKGROUND: A number of studies, notably EPIC, have shown a descrease in colorectal cancer risk associated with increased fibre consumption. Whilst the underlying mechanisms are likely to be multifactorial, production of the short-chain fatty-acid butyrate fro butyratye is frequently cited as a major potential contributor to the effect. Butyrate inhibits histone deacetylases, which work on a wide range of proteins over and above histones. We therefore hypothesized that alterations in the acetylated proteome may be associated with a cancer risk phenotype in the colorectal mucosa, and that such alterations are candidate biomarkers for effectiveness of fibre interventions in cancer prevention. METHODS AN DESIGN: There are two principal arms to this study: (i) a cross-sectional study (FACT OBS) of 90 subjects recruited from gastroenterology clinics and; (ii) an intervention trial in 40 subjects with an 8 week high fibre intervention. In both studies the principal goal is to investigate a link between fibre intake, SCFA production and global protein acetylation. The primary measure is level of faecal butyrate, which it is hoped will be elevated by moving subjects to a high fibre diet. Fibre intakes will be estimated in the cross-sectional group using the EPIC Food Frequency Questionnaire. Subsidiary measures of the effect of butyrate on colon mucosal function and pre-cancerous phenotype will include measures of apoptosis, apoptotic regulators cell cycle and cell division. DISCUSSION: This study will provide a new level of mechanistic data on alterations in the functional proteome in response to the colon microenvironment which may underwrite the observed cancer preventive effect of fibre. The study may yield novel candidate biomarkers of fibre fermentation and colon mucosal function. TRIAL REGISTRATION NUMBER: ISRCTN90852168.
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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 | 0.021 | 0.014 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.079 | 0.026 |
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".