Reprogramming bone progenitor identity and potency through control of collagen density and oxygen tension
Bibliographic record
Abstract
The biophysical microenvironment of the cell is being increasingly used to control cell signaling and to direct cell function. Herein, engineered 3D tuneable biomimetic scaffolds are used to control the cell microenvironment of Adipose-derived Mesenchymal Stromal Cells (AMSC), which exhibit a collagen density-specific profile for early and late stage bone cell lineage status. Cell potency was enhanced when AMSCs were cultured within low collagen density environments in hypoxic conditions. A transitional culture containing varied collagen densities in hypoxic conditions directed differential cell fate responses. The early skeletal progenitor identity (PDPN + CD146 − CD73 + CD164 + ) was rescued in the cells which migrated into low collagen density gels, with cells continuously exposed to the high collagen density gels displaying a transitioned bone-cartilage-stromal phenotype (PDPN + CD146 + CD73 − CD164 - ). This study uncovers the significant contributions of the physical and physiological cell environment and highlights a chemically independent methodology for reprogramming and isolating skeletal progenitor cells from an adipose-derived 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 | 0.001 | 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".