Mechanical loading of ex vivo bovine trabecular bone in 3D printed bioreactor chambers
Bibliographic record
Abstract
Previous ex vivo bone culture methods have successfully implemented polycarbonate (PC) bioreactors to investigate bone adaptation to mechanical load; however, they are difficult to fabricate and have been limited to a 5 mm maximum specimen height. The objective of this study was to validate a custom-made 3D printed MED610TM bioreactor system that addresses the limitations of the PC bioreactor and assess its efficacy in ex vivo bone culture. Twenty-three viable trabecular bone cores (10 mm height by 10 mm diameter) from an 18-month-old bovine sternum were cultured in MED610TM bioreactors with culture medium at 37 °C and 5% CO2 for 21-days. Bone cores were ranked based on their day 0 apparent elastic modulus (Eapp) and evenly separated into a “Load” group (n = 12) and a control group (n = 11). The Load group was loaded five times per week with a sinusoidal strain waveform between −1000 and −5000 με for 120 cycles at 2 Hz. Eapp was assessed on day 0, 8, and 21 using quasi-static tests with a −4000 με applied strain. Over 21-days, the Eapp of Load group samples tended to increase by more than double the control group (53.4% versus 20.9%) and no visual culture contamination was observed. This study demonstrated that bone organ culture in 3D printed MED610TM bioreactors replicated Eapp trends found in previous studies with PC bioreactors. However, further studies are warranted with a larger sample size to increase statistical power and histology to assess cell viability and bone mineral apposition rate.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".