MRI tracking of transplanted iron‐labeled mesenchymal stromal cells in an immune‐compromised mouse model of critical limb ischemia
Bibliographic record
Abstract
Peripheral arterial disease is a clinical problem in which mesenchymal stromal cell (MSC) transplantation may offer substantial benefit by promoting the generation of new blood vessels and improving limb ischemia and wound healing via their potent paracrine activities. MRI allows for the noninvasive tracking of cells over time using iron oxide contrast agents to label cells before they are injected or transplanted. However, a major limitation of the tracking of iron oxide-labeled cells with MRI is the possibility that dead or dying cells will transfer the iron oxide label to local bystander macrophages, making it very difficult to distinguish between viable transplanted cells and endogenous macrophages in the images. In this study, a severely immune-compromised mouse, with limited macrophage activity, was investigated to examine cell tracking in a system in which bystander cell uptake of dead, iron-labeled cells or free iron particles was minimized. MRI was used to track the fate of MSCs over 21 days after their intramuscular transplantation in mice with a femoral artery ligation. In all mice, a region of signal loss was observed at the injection site and the volume of signal hypointensity diminished over time. Fluorescence and light microscopy showed that iron-positive MSCs persisted at the transplant site and often appeared to be integrated in perivascular niches. This was compared with MSC transplantation in immune-competent mice with femoral artery ligation. In these mice, the regions of signal loss caused by iron-labeled MSC cleared more slowly, and histology revealed iron particles trapped at the site of cell transplantation and associated with areas of inflammation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".