Crown-like structures in breast adipose tissue of breast cancer patients: associations with CD68 expression, obesity, metabolic factors and prognosis
Bibliographic record
Abstract
Abstract Crown-like structures of the breast (CLS-B), defined by the clustering of macrophages (identified using CD68 immunohistochemical staining) to surround a dying adipocyte, are a sign of adipose-tissue inflammation. In human cohorts, CLS-B positively correlates with older age, obesity, dyslipidemia and higher levels of glucose, insulin, C-reactive protein and IL-6. In an existing cohort of early-stage breast cancer patients, CLS-B were identified using H&E stained histologic sections (hCLS-B), and by CD68 immunohistochemistry (CD68 + CLS-B). We examined associations of H&E and CD68-detected CLS-B with clinicopathologic features using χ2 tests, with metabolic factors using Wilcoxon rank sum tests and with disease free and overall survival using Cox regression models. hCLS-B were detected in 59 of 163 patients with slides (36.2%) and CD68 + CLS-B in 37 of 119 patients with paraffin blocks (31.1%). hCLS-B were positively correlated with higher weight (p = 0.003), BMI (p = 0.0008) and C-reactive protein (p = 0.045). CD68 + CLS-B were positively correlated with higher weight (p = 0.006), BMI p = 0.001), leptin (p = 0.034), insulin (p = 0.008) and Homeostasis Model Assessment (p = 0.027). CD68 + CLS-B were associated with poor distant disease-free with a hazard ratio (HR) of 2.81, 95% confidence interval (CI) 1.20–6.57, and overall survival with HR 3.97 (1.66–9.48), while hCLS-B were not associated with either: HR for distant recurrence 0.59 (0.26–1.30); HR for death 1.04 (0.50–2.16). The presence of hCLS-B and of CD68 + CLS-B were associated with obesity; CD68 + CLS-B were associated with insulin resistance and adverse prognosis. Similar patterns were not seen for hCLS-B. Research is needed to understand the biologic basis for these differences.
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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 | 0.000 | 0.001 |
| 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) | 0.002 | 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 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".