Migration, Proliferation, and Differentiation of Cord Blood Mesenchymal Stromal Cells Treated with Histone Deacetylase Inhibitor Valproic Acid
Bibliographic record
Abstract
Mesenchymal stromal cells (MSC) have great potential for cellular therapies as they can be directed to differentiate into certain lineages or to exert paracrine effects at sites of injury. The interactions between stromal cell-derived factor (SDF)-1 and its receptors CXCR4 and CXCR7 play pivotal roles in the migration of MSC to injured tissues. We evaluated whether a histone deacetylase inhibitor valproic acid (VPA) modulates the migration of cord blood (CB-) derived MSC towards SDF-1 and their proliferation and differentiation. We found that in MSC, VPA increased (i) the gene and total protein expression of CXCR4 and CXCR7 and primed migration towards a low gradient of SDF-1, (ii) the gene expression of MMP-2 and secretion and activation of proMMP-2, (iii) the proliferation and gene expression of pluripotency markers SOX2 and Oct-4, and exposure to lower concentrations of VPA (≤5 mM) had no effect on their differentiation to osteocytes and chondrocytes. Thus, our study indicates that VPA enhances the migration of CB MSC towards SDF-1 by increasing the expression of CXCR4, CXCR7, and MMP-2. VPA at low concentrations may be used for ex vivo treatment of MSC to increase their recruitment to sites of injury without compromising their ability to proliferate or differentiate.
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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".