The differential<i>in vitro</i>and<i>in vivo</i>responses of bone marrow stromal cells on novel porous gelatinâalginate scaffolds
Bibliographic record
Abstract
Tissue engineering and stem cell therapy hold great potential of being able to fully restore, repair and replace damaged, diseased or lost tissues in the body. Biocompatible porous scaffolds are used for the delivery of cells to the regeneration sites. Marrow stromal cells (MSCs), also referred to as mesenchymal stem cells, are an attractive cell source for tissue engineering, due to the relative ease of isolation and the ability of in vitro expanded MSCs to generate multiple cell types, including osteoblasts, chondrocytes and adipocytes. This study utilized a novel technique called microwave vacuum drying to fabricate porous gelatin-alginate scaffolds for the delivery of MSCs and investigated the differential in vitro and in vivo responses of MSCs seeded on these scaffolds. Scaffold total porosity was found to decrease with increased cross-link density but the pore size and pore size distribution were not affected. Although highly porous, the scaffold had relatively small pores and limited interconnectivity. The porous gelatin-alginate scaffold demonstrated excellent biocompatibility with neovascularization on the surfaces and was bioresorbed completely in vivo, depending upon the cross-link density. MSCs were able to attach and proliferate at the same rate on the scaffolds, and the self-renewal potential of MSC cultures was similar during both in vitro culture and in vivo implantation. However, the subcutaneous microenvironment was found to suppress MSC differentiation along the osteogenic, chondrogenic and adipogenic lineages compared to in vitro conditions, highlighting the differential responses of MSCs cultured in vitro compared to implantation in vivo.
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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".