Early Beneficial Effects of Bone Marrow-Derived Mesenchymal Stem Cells Overexpressing Akt on Cardiac Metabolism After Myocardial Infarction
Bibliographic record
Abstract
Administration of mesenchymal stem cells (MSCs) is an effective therapy to repair cardiac damage after myocardial infarction (MI) in experimental models. However, the mechanisms of action still need to be elucidated. Our group has recently suggested that MSCs mediate their therapeutic effects primarily via paracrine cytoprotective action. Furthermore, we have shown that MSCs overexpressing Akt1 (Akt-MSCs) exert even greater cytoprotection than unmodified MSCs. So far, little has been reported on the metabolic characteristics of infarcted hearts treated with stem cells. Here, we hypothesize that Akt-MSC administration may influence the metabolic processes involved in cardiac adaptation and repair after MI. MI was performed in rats randomized in four groups: sham group and animals treated with control MSCs, Akt-MSCs, or phosphate-buffered saline (PBS). High energy metabolism and basal 2-deoxy-glucose (2-DG) uptake were evaluated on isolated hearts using phosphorus-31 nuclear magnetic resonance spectroscopy at 72 hours and 2 weeks after MI. Treatment with Akt-MSCs spared phosphocreatine stores and significantly limited the increase in 2-DG uptake in the residual intact myocardium compared with the PBS- or the MSC-treated animals. Furthermore, Akt-MSC-treated hearts had normal pH, whereas low pH was measured in the PBS and MSC groups. Correlative analysis indicated that functional recovery after MI was inversely related to the rate of 2-DG uptake. We conclude that administration of MSCs overexpressing Akt at the time of infarction results in preservation of normal metabolism and pH in the surviving myocardium.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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) | 0.001 | 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".