Erythropoietin Gene-enhanced Marrow Mesenchymal Stromal Cells Decrease Cisplatin-induced Kidney Injury and Improve Survival of Allogeneic Mice
Bibliographic record
Abstract
Bone marrow-derived mesenchymal stromal cells (MSCs) are promising for regenerative medicine applications, such as for renoprotection and repair in acute kidney injury (AKI). Erythropoietin (Epo) can also exert cytoprotective effects on various tissues including the kidney. We hypothesized that MSCs gene-enhanced to secrete Epo may produce a significant beneficial effect in AKI. Mouse Epo-secreting MSCs were generated, tested in vitro, and then implanted by intraperitoneal injection in allogeneic mice previously administered cisplatin to induce AKI. Epo-MSCs significantly improved survival of implanted mice as compared to controls (67% survival versus 33% with Vehicle only). Also, Epo-MSCs led to significantly better kidney function as shown by lower levels of blood urea nitrogen (72 ± 9.5 mg/dl versus 131 ± 9.20 mg/dl) and creatinine (74 ± 17 µmol/l versus 148±19.4 µmol/l). Recipient mice also showed significantly decreased amylase and alanine aminotransferase blood concentrations. Kidney sections revealed significantly less apoptotic cells and more proliferating cells. Furthermore, PCR revealed the presence of implanted cells in recipient kidneys, with Epo-MSCs leading to significantly increased expression of Epo and of phosphorylated-Akt (Ser473) (P-Akt) in these kidneys. In conclusion, our study demonstrates that Epo gene-enhanced MSCs exert significant tissue protective effects in allogeneic mice with AKI, and supports the potential use of gene-enhanced cells as universal donors in acute injury.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".