Localized SDF‐1alpha gene release mediated by collagen substrate induces CD117<sup>+</sup> stem cells homing
Bibliographic record
Abstract
Stromal cell-derived factor-1alpha (SDF-1alpha) mediated mobilization and homing of stem cells showed promising potential in stem cell based tissue engineering and regenerative medicine. However local and sustained release of SDF-1alpha is indispensable for stem cell mediated regenerative process due to its short half-life under inflammatory conditions. In this study, a gene activated collagen substrate (GAC) was formed via assembly of plasmid encoding SDF-1alpha into a collagen substrate to create a microenvironment favoring stem cell homing. Local release of SDF-1alpha from the transfected cells on GAC and its effect on CD117(+) stem cell homing were investigated. Non-viral poly-ethyleneimine (25kDa PEI)/DNA complexes were mixed with rat tail collagen solution to form the GAC. Optimization of GAC was carried out based on collagen effects on the PEI/DNA complexes, viability and luciferase expression of COS7 cells on GAC. CD117(+) stem cells homing in response to SDF-1alpha local expression from transfected cells on GAC were investigated in a flow chamber in vitro and in a mouse hind limb model in vivo. The gene expression, migration of CD117(+) stem cells and the induced inflammation were investigated with immunostaining, reverse transcription polymerase chain reaction (RT-PCR) and H&E staining. The optimized parameters for GAC were DNA dosage 10 microg/cm(2), molar ratio of PEI nitrogen in primary amine to DNA phosphate (N/P ratio) 4 and mass ratio of collagen to DNA (C/D ratio) 1.0. It kept cell viability above 75% and transfection efficiency around 5.8 x 10(5) RLU/mg protein. GAC allowed the sustained gene release up to 60 days. GAC mediated SDF-1alpha gene release induced migration and homing of CD117(+) stem cells in vitro and in vivo significantly, and the inflammation of GAC reduced significantly two weeks after transplantation. GAC is a promising stem cell based therapeutic strategy for regenerative medicine.
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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".