Co-delivery of human adipose-derived stromal cells and endothelial colony-forming cells in cell-assembled decellularized adipose tissue scaffolds for applications in soft tissue regeneration
Bibliographic record
Abstract
Abstract Cellular therapies involving the co-delivery of cells with complementary pro-regenerative functionality hold promise as a strategy to promote soft tissue regeneration. In particular, the co-delivery of adipose-derived stromal cells (ASCs) and endothelial colony-forming cells (ECFCs) has shown promise for regenerating stable blood vessels in vivo. The current study developed novel “cell-assembled” scaffolds for co-delivering human ASCs and ECFCs within a supportive decellularized adipose tissue (DAT) matrix, with the objective of enhancing their localized retention and augmenting their capacity to stimulate adipose tissue regeneration. Human ASCs and ECFCs were seeded separately onto human-derived DAT microcarriers under cell-type specific conditions. The cell-seeded microcarriers were then combined and cultured for 8 days under conditions that promoted matrix remodeling to fuse the microcarriers into 3D engineered tissues containing ASCs+ECFCs, ASCs alone, or ECFCs alone. Co-culture with ECFCs within the scaffolds was shown to modulate ASC pro-angiogenic gene expression, with some ECFCs forming tubule-like structures in vitro in both the ASC+ECFC and ECFC alone groups. In vivo bioluminescence imaging using a dual luciferase reporter system showed that co-delivery with ASCs enhanced ECFC retention following subcutaneous implantation in athymic nu/nu mice, but co-delivery did not alter the localized retention of viable ASCs. Interestingly, while immunofluorescence staining for CD31 and microcomputed tomography angiography indicated that vascular regeneration was similar in the cell-assembled scaffolds containing ASC+ECFCs, ASCs alone, and ECFCs alone, histological staining revealed that extensive regions of the ECFC alone scaffolds had remodelled into adipose tissue at 29 days post-implantation.
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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".