Berberine Inhibits Breast Cancer Stem Cell Development and Decreases Inflammation: Involvement of miRNAs and IL-6
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
Background: Breast cancer (BC) is a health concern worldwide and is often accompanied by depressive symptoms in patients. In BC, elevated interleukin-6 (IL-6) levels contribute to an inflammatory signature linked to cancer stem cell (CSC) stemness and depressive behaviors. Bioactive food components, such as berberine (BBR), have preventative effects against BC by targeting CSCs. Objectives: This study aimed to investigate the effects of BBR on breast CSC proliferation, on levels of specific micro (mi)RNAs and IL-6 in vitro and in vivo, and in alleviating depressive-like behaviors in mice with BC. Methods: Mammosphere formation assays were conducted by treating murine 4T1 and human MDA-MB-231 BC cell lines with BBR. qPCR analysis of miRNAs miR-let-7c and miR-34a-5p was performed on 4T1 CSCs exposed to BBR. BBR was administered orally to female BALB/c, followed by injection with mammary carcinoma cells to induce BC. Behavioral tests were conducted to assess depressive-like behaviors. Tumor tissues were collected for ex vivo mammosphere assays, miRNA expression analysis, and IL-6 detection by ELISA. Serum was also collected for IL-6 analysis. Results: > 0.05). However, no significant differences were observed in depressive-like behaviors between control and treatment groups. Conclusions: BBR may have the potential to be used as an "Epi-Natural Compound" to prevent cancer by reducing inflammation and affecting epigenetics.
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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