Probing the effects of matrix‐derived microcarrier composition on human adipose‐derived stromal cells cultured dynamically within spinner flask bioreactors
Bibliographic record
Abstract
Recognizing the cell-instructive capacity of the extracellular matrix (ECM), this study investigated the effects of expanding human adipose-derived stromal cells (hASCs) on ECM-derived microcarriers fabricated from decellularized adipose tissue (DAT) or decellularized cartilage tissue (DCT) within spinner flask bioreactors. Protocols were established for decellularizing porcine auricular cartilage and electrospraying methods were used to generate microcarriers comprised exclusively of DAT or DCT, which were compositionally distinct, but had matching Young's moduli. Both microcarrier types supported hASC attachment and growth over 14 days within a low-shear spinner culture system, with a significantly higher cell density observed on the DCT microcarriers at 7 and 14 days. Irrespective of the ECM source, dynamic culture on the microcarriers altered the expression of genes and proteins associated with cell adhesion and ECM remodeling. Label-free mass spectrometry analysis showed upregulation of proteins associated with cartilage development and ECM in the hASCs expanded on the DCT microcarriers. Based on Luminex analysis, the hASCs expanded on the DCT microcarriers secreted significantly higher levels of IL-8 and PDGFAA, supporting that the ECM source can modulate hASC paracrine factor secretion. Finally, the hASCs expanded on the microcarriers were extracted for analysis of adipogenic and chondrogenic differentiation relative to baseline controls. The microcarrier-cultured hASCs showed enhanced intracellular lipid accumulation at 7 days post-induction of adipogenic differentiation. In the chondrogenic studies, a low level of differentiation was observed in all groups. Future studies are warranted using alternative cell sources with greater chondrogenic potential to further assess the chondro-inductive properties of the DCT microcarriers.
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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) | 0.000 | 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".