Investigating the Effects of Tissue-Specific Extracellular Matrix on the Adipogenic and Osteogenic Differentiation of Human Adipose-Derived Stromal Cells Within Composite Hydrogel Scaffolds
Bibliographic record
Abstract
While it has been postulated that tissue-specific bioscaffolds derived from the extracellular matrix (ECM) can direct stem cell differentiation, systematic comparisons of multiple ECM sources are needed to more fully assess the benefits of incorporating tissue-specific ECM in stem cell culture and delivery platforms. To probe the effects of ECM sourced from decellularized adipose tissue (DAT) or decellularized trabecular bone (DTB) on the adipogenic and osteogenic differentiation of human adipose-derived stem/stromal cells (ASCs), a novel detergent-free decellularization protocol was developed for bovine trabecular bone that complemented our established detergent-free decellularization protocol for human adipose tissue and did not require specialized equipment or prolonged incubation times. Immunohistochemical and biochemical characterization revealed enhanced sulphated glycosaminoglycan content in the DTB, while the DAT contained higher levels of collagen IV, collagen VI and laminin. To generate platforms with similar structural and biomechanical properties to enable assessment of the compositional effects of the ECM on ASC differentiation, micronized DAT and DTB were encapsulated with human ASCs within methacrylated chondroitin sulfate (MCS) hydrogels through UV-initiated crosslinking. High ASC viability (>90%) was observed over 14 days in culture. Adipogenic differentiation was enhanced in the MCS+DAT composites relative to the MCS+DTB composites and MCS controls after 14 days of culture in adipogenic medium. Osteogenic differentiation studies revealed a peak in alkaline phosphatase (ALP) enzyme activity at 7 days in the MCS+DTB group cultured in osteogenic medium, suggesting that the DTB had bioactive effects on osteogenic protein expression. Overall, the current study suggests that tissue-specific ECM sourced from DAT or DTB can act synergistically with soluble differentiation factors to enhance the lineage-specific differentiation of human ASCs within 3-D hydrogel systems.
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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".