Vibration Therapy for Cancer-Related Bone Diseases
Bibliographic record
Abstract
Patients undergoing cancer treatments and/or suffering from metastatic bone lesions experience various skeletal-related events (SREs), substantially reducing functional independence and quality of life. Therefore, researchers are working towards developing new interventions by harnessing the bone’s innate anabolic response to mechanical stimulations. Whole body vibration (WBV) has recently gained interest due to its nature of being safe, effective, and easy to perform. In this review, we will summarize the most cutting-edge vibration studies of cancer models and bone-cancer cell interactions. We will also discuss various parameters, including age, vibration settings, and differences between bone sites, which may affect vibration efficacy. Studies have shown that WBV improves bone mineral density (BMD) and bone volume in patients and mice with cancer. WBV also reduces tumor burden and normalizes bone vasculature in mice. At the cellular level, vibration promotes interactions between bone cells and cancer cells, which reduce osteoclastogenesis and inhibit cancer metastatic potential. Hence, WBV could potentially serve as a new intervention or adjuvant treatment to attenuate cancer progression while preserving bone health.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".