Using diffusion tensor imaging to depict myocardial changes after matured pluripotent stem cell-derived cardiomyocyte transplantation
Bibliographic record
Abstract
BACKGROUND: Novel treatment strategies are needed to improve the structure and function of the myocardium post-infarction. In vitro-matured pluripotent stem cell-derived cardiomyocytes (PSC-CMs) have been shown to be a promising regenerative strategy. We hypothesized that mature PSC-CMs will have anisotropic structure and improved cell alignment when compared to immature PSC-CMs using cardiovascular magnetic resonance (CMR) in a guinea pig model of cardiac injury. METHODS: immature tissue culture plastic (TCP)-generated PSC-CMs (n = 6) on day 0. Vehicle (sham-treated) subjects were injected with a pro-survival cocktail devoid of cells (n = 4), while healthy controls (n = 4) did not undergo cryoinjury or treatment. Animals were sacrificed on either day +14 or day +28 post-transplantation. Animals were imaged ex vivo on a 7T Bruker MRI. A 3D diffusion tensor imaging (DTI) sequence was used to quantify structure via fractional anisotropy (FA), mean diffusivity (MD), and myocyte alignment measured by the standard deviation of the transverse angle (TA). RESULTS: /s, p < 0.05) and significantly lower FA than the control (0.12 ± 0.02, p < 0.05) but were not different from mature PDMS grafts in this small cohort. TA of healthy controls showed low variability and was not significantly different than mature PDMS grafts (p = 0.4) while immature TCP grafts were significantly different (p < 0.001). DTI parameters of mature graft tissue trended toward that of the healthy myocardium, indicating the grafted cardiomyocytes may have a similar phenotype to healthy tissue. Contrast-enhanced magnetic resonance images corresponded well to histological staining, demonstrating a non-invasive method of localizing the repopulated cardiomyocytes within the scar. CONCLUSIONS: The DTI measures within graft tissue were indicative of anisotropic structure and showed greater myocyte organization compared to the scarred territory. These findings show that MRI is a valuable tool to assess the structural impacts of regenerative therapies.
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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 | 0.001 | 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".