Preconditioning of Stem Cells by Oxytocin to Improve Their Therapeutic Potential
Bibliographic record
Abstract
Principal limitation of cell therapy is cell loss after transplantation because of the interplay between ischemia, inflammation, and apoptosis. We investigated the mechanism of preconditioning of mesenchymal stem cells (MSCs) with oxytocin (OT), which has been proposed as a novel strategy for enhancing therapeutic potential of these cells in ischemic heart. In this study, we demonstrate that rat MSCs express binding sites for OT receptor and OT receptor transcript and protein as detected by RT-PCR and immunofluorescence, respectively. In response to OT (10(-10) to 10(-6) M) treatment, MSCs respond with rapid calcium mobilization and up-regulation of the protective protein kinase B (PKB or Akt) and phospho-ERK1/2 proteins. In OT-stimulated cells, phospho-Akt accumulates intracellularly close to the mitochondrial marker cytochrome c oxidase subunit 4. Functional analyses reveal the involvement of Akt/ERK1/2 pathways in cell proliferation, migration, and protection against the cytotoxic and apoptotic effects of hypoxia and serum deprivation. In addition, OT preconditioning increases MSC glucose uptake. Genes with angiogenic, antiapoptotic, and cardiac antiremodeling properties, such as heat shock proteins (hsps) HSP27, HSP32, HSP70, vascular endothelial growth factor, thrombospondin, tissue inhibitor of metalloproteinase (TIMP)-1, TIMP-2, TIMP-3, and matrix metalloproteinase-2, were also up-regulated upon OT exposure. Moreover, coculture with OT-preconditioned MSC reduces apoptosis, as measured using terminal transferase dUTP nick end labeling assay in newborn rat cardiomyocytes exposed to hypoxia and reoxygenation. In conclusion, these results indicate that OT treatment evokes MSC protection through both intrinsic pathways and secretion of cytoprotective factors. Ex vivo cellular treatment with OT represents an attractive strategy aimed to maximize the biological and functional properties of effector cells.
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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".