Change in Inflammatory Biomarkers and Adipose Tissue in <i>BRCA1/2</i>+ Breast Cancer Survivors Following a Yearlong Lifestyle Modification Program
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Breast cancer survivors who carry a genetic mutation for one of the BRCA genes often undergo surgically induced menopause a decade or more before the usual age of natural menopause. These women are at elevated risk for multiple negative health outcomes, including metabolic diseases, heart disease, and cancer recurrence. Effects of a 12-month commercially available web-based lifestyle program (Precision Nutrition) were tested on body composition and markers of inflammation in a randomized controlled trial. Participants (N = 35) were BRCA1/2+, breast cancer survivors, and had completed surgically induced menopause at age &lt;45 years. Dual-energy X-ray absorptiometry was used to quantify body composition. Fasting blood samples were used to assay insulin, IL1β, IL6, IL8, and TNFα. At baseline, we observed relationships between insulin, TNFα, and IL6, and between biomarkers and adiposity. Insulin and subcutaneous adipose tissue levels significantly decreased following the intervention compared with the change in the control group. Compared with baseline, TNFα and total adipose tissue levels decreased significantly in the intervention group. The percent change in insulin levels was moderately correlated with the percent change in subcutaneous adipose tissue (r = 0.33). Change in adiposity was not related to change in TNFα or IL6. Women in the intervention group decreased levels of subcutaneous, but not visceral, adipose tissue. The change in subcutaneous adipose tissue was the main driver of change in insulin levels for the women in the intervention group. However, the change in body composition achieved by the Precision Nutrition program was not sufficient to alter biomarker levels of inflammation. Cancer Prev Res; 11(9); 545–50. ©2018 AACR.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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