Aged Osteoporotic Bone Marrow Stromal Cells Demonstrate Defective Recruitment, Mechanosensitivity, and Matrix Deposition
Bibliographic record
Abstract
Bone formation requires the replenishment of the osteoblast from a progenitor or stem cell population, which must be recruited, expanded, and differentiated to ensure continued anabolism. How this occurs and whether it is altered in the osteoporotic environment is poorly understood. Furthermore, given that emerging treatments for osteoporosis are targeting this progenitor population, it is critical to determine the regenerative capacity of this cell type in the setting of osteoporosis. Human bone marrow stromal cells (hMSCs) from a cohort of aged osteoporotic patients were compared to MSCs isolated from healthy donors in terms of the ability to undergo recruitment and proliferation, and also respond to both the biophysical and biochemical cues that drive osteogenic matrix deposition. hMSCs isolated from healthy donors demonstrate good recruitment, mechanosensitivity, proliferation, and differentiation capacity. Contrastingly, hMSCs isolated from aged osteoporotic patients had significantly diminished regenerative potential. Interestingly, we demonstrated that osteoporotic hMSCs no longer responded to chemokine-directing recruitment and became desensitised to mechanical stimulation. The osteoporotic MSCs had a reduced proliferative potential and, importantly, they demonstrated an attenuated differentiation capability with reduced mineral and lipid formation. Moreover, during osteogenesis, despite minimal differences in the quantity of deposited collagen, the distribution of collagen was dramatically altered in osteoporosis, suggesting a potential defect in matrix quality. Taken together, this study has demonstrated that hMSCs isolated from aged osteoporotic patients demonstrate defective cell behaviour on multiple fronts, resulting in a significantly reduced regenerative potential, which must be considered during the development of new anabolic therapies that target this cell population.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".