Breast Cancer and Microcalcifications: An Osteoimmunological Disorder?
Bibliographic record
Abstract
The presence of microcalcifications in the breast microenvironment, combined with the growing evidences of the possible presence of osteoblast-like or osteoclast-like cells in the breast, suggest the existence of active processes of calcification in the breast tissue during a woman's life. Furthermore, much evidence that osteoimmunological disorders, such as osteoarthritis, rheumatoid arthritis, or periodontitis influence the risk of developing breast cancer in women exists and vice versa. Antiresorptive drugs benefits on breast cancer incidence and progression have been reported in the past decades. More recently, biological agents targeting pro-inflammatory cytokines used against rheumatoid arthritis also demonstrated benefits against breast cancer cell lines proliferation, viability, and migratory abilities, both in vitro and in vivo in xenografted mice. Hence, it is tempting to hypothesize that breast carcinogenesis should be considered as a potential osteoimmunological disorder. In this review, we compare microenvironments and molecular characteristics in the most frequent osteoimmunological disorders with major events occurring in a woman's breast during her lifetime. We also highlight what the use of bone anabolic drugs, antiresorptive, and biological agents targeting pro-inflammatory cytokines against breast cancer can teach us.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".