Pharmacological Preconditioning Improves the Viability and Proangiogenic Paracrine Function of Hydrogel-Encapsulated Mesenchymal Stromal Cells
Bibliographic record
Abstract
The efficacy of cell therapy is limited by low retention and survival of transplanted cells in the target tissues. In this work, we hypothesize that pharmacological preconditioning with celastrol, a natural potent antioxidant, could improve the viability and functions of mesenchymal stromal cells (MSC) encapsulated within an injectable scaffold. Bone marrow MSCs from rat (rMSC) and human (hMSC) origin were preconditioned for 1 hour with celastrol 1 μM or vehicle (DMSO 0.1% v / v), then encapsulated within a chitosan-based thermosensitive hydrogel. Cell viability was compared by alamarBlue and live/dead assay. Paracrine function was studied first by quantifying the proangiogenic growth factors released, followed by assessing scratched HUVEC culture wound closure velocity and proliferation of HUVEC when cocultured with encapsulated hMSC. In vivo, the proangiogenic activity was studied by evaluating the neovessel density around the subcutaneously injected hydrogel after one week in rats. Preconditioning strongly enhanced the viability of rMSC and hMSC compared to vehicle-treated cells, with 90% and 75% survival versus 36% and 58% survival, respectively, after 7 days in complete media and 80% versus 64% survival for hMSC after 4 days in low serum media ( p < 0.05 ). Celastrol-treated cells increased quantities of proangiogenic cytokines compared to vehicle-pretreated cells, with a significant 3.0-fold and 1.8-fold increase of VEGFa and SDF-1α, respectively ( p < 0.05 ). The enhanced paracrine function of preconditioned MSC was demonstrated by accelerated growth and wound closure velocity of injured HUVEC monolayer ( p < 0.05 ) in vitro. Moreover, celastrol-treated cells, but not vehicle-treated cells, led to a significant increase of neovessel density in the peri-implant region after one week in vivo compared to the control (blank hydrogel). These results suggest that combining cell pretreatment with celastrol and encapsulation in hydrogel could potentiate MSC therapy for many diseases, benefiting particularly ischemic diseases.
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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".