Influence of the Mediterranean diet on the production of short-chain fatty acids in women at risk for breast cancer (LIBRE)
Bibliographic record
Abstract
Abstract Background: A number of small intervention studies suggested that a Mediterranean diet (MedD) and physical activity can lower the risk for breast cancer. LIBRE is the first large multicenter RCT to test the effect of these lifestyle factors on the incidence of breast cancer in women at risk because of BRCA mutations (1) . LIBRE also offers to unravel underlying mechanisms such as the role of short-chain fatty acids (SCFA) for beneficial effects of such lifestyle interventions. Methods: We examined the effect of the lifestyle intervention on the production of SCFA measured in feces by gas chromatography. From the ongoing LIBRE trial we included all complete datasets (171 women; mean age 44 ± 11 years). Both women with and without previous breast cancer diagnosis were recruited (diseased; non-diseased). The participants were randomized into an intervention group (IG) trained for MedD and physical activity, and a usual care control group (CG). Adherence to the MedD was assessed at baseline and after 3 months (V1) using the validated Mediterranean Diet Adherence Screener (MEDAS) and the EPIC food frequency questionnaire (FFQ). Results: At baseline there was no difference in SCFA levels between the groups. In the IG the MEDAS score increased substantially by 2.5 points (p < 0.001), in the CG only mildly by 0.4 points (p < 0.05). Correspondingly, the intake of fibers increased solely in the IG. In the course of the study the amount of caproic acid decreased in the control group (p < 0.001). At V1 non-diseased women showed higher amounts of acetic acid (p = 0.042), n-butyric acid (p = 0.023), n-valeric acid (p = 0.018) and iso-valeric acid (p = 0.031). There were several correlations between the intake of different fibers and fecal SCFA. For example, the sum of poly- and oligosaccharides correlated with acetic acid (p = 0.001; r = 0.316), propionic acid (p = 0.034; r = 0,251), n-butyric acid (p = 0.010; r = 0.316) and iso-valeric acid (p = 0.012; r = 0.306). There was no correlation between the MEDAS and SCFA. Discussion: A lifestyle change towards a MedD and increased physical activity did not change the levels of SCFA in feces, although an increase of fiber intake was documented in the IG. To further analyze SCFA metabolism in this target population, gut microbiota composition and function (metabolites) are currently analyzed.
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".