Probiotics and mediterranean diet for breast cancer management and prevention?
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The human gut microbiota, a diverse community of beneficial normal flora microorganisms, significantly influences physiological function and the immune response. Various microbiota strains have shown promise in supporting clinical treatment of chronic diseases, including cancer, by potentially providing antioxidative and anti-tumorigenic effects in both in vivo and in vitro studies. Breast cancer, which ranks amongst the top five cancer types common worldwide and particularly in Mediterranean countries, has been showing high incidence and prevalence. In breast cancer, microbiota composition, hormonal dynamics, and dietary choices are believed to play significant roles. Hence, the Mediterranean diet, known for its microbiota-friendly features, emerges as a potential protective factor against breast cancer development, highlighting the potential for personalized dietary strategies in cancer prevention. This comprehensive review highlights the emerging mechanisms by which probiotics support our immune system during different physiological activities. It also discusses their potential role, along with nutrition intervention, in improving essential clinical treatment outcomes in breast cancer patients and survivors, suggesting potential supportive strategies that go hand in hand with clinical strategies. Unfortunately, very little research addresses the possible clinical implications of probiotics and dietary habits on breast cancer, despite the promising results, calling for further studies and actions.
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.
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 it