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Vibration's frequency and intensity for optimal setup for enhancement bone response in small rodents: A systematic review and Bayesian network meta-analysis
Low-intensity vibration (LIV) is a non-invasive mechanical stimulus capable of regulating skeletal adaptation and cellular signaling pathways involved in bone remodeling. Despite
- Published: 09 Jul 2026, 12:00 pm (UTC)
- Updated: 09 Jul 2026, 12:00 pm (UTC)
- Specialty: Research Highlights
- Source: bioRxiv (Biomedical Preprints)
GIST
Low-intensity vibration (LIV) is a non-invasive mechanical stimulus capable of regulating skeletal adaptation and cellular signaling pathways involved in bone remodeling. Despite growing interest in LIV, substantial methodological heterogeneity persists in the selection of experimental vibration parameters such as frequency, expressed in Hertz (Hz) and intensity, defined as earth's gravitational field (g) (9.81 m/s2). Focusing on micro-computed tomography (CT) derived trabecular bone volume fraction (BV/TV) as the main outcome measure, this study sought to synthesize the effects of different LIV frequency and intensity on BV/TV in small rodents (mice and rats) as they remain as the most studied pre-clinical model. To accomplish this, we performed a systematic review searching for publications in English on PubMed, Web of Science, CINAHL, and Embase databases. Two independent investigators followed inclusion criteria to select only peer-reviewed studies with mature mice, using whole-body vibration experiments without other co-variables. We further restricted to include studies that analyzed non-fractured bones and compared pre- and post-intervention or control values. In addition to these core criteria, a detailed hierarchical screening framework was applied during full-text review.
Clinical Editorial
bioRxiv (Biomedical Preprints) published a clinical update in Research Highlights on 09 Jul 2026. The item focuses on Vibration's frequency and intensity for optimal setup for enhancement bone response in small rodents: A systematic review and Bayesian network meta-analysis. Review the original article for the full source wording and details.
Original source: https://www.biorxiv.org/content/10.64898/2026.07.08.737040v1?rss=1