Abstract 8096: Transplantation of Mesenchymal Stem Cells Alters Ion Channel Gene Expression and Mitigates Cardiac Electrophysiological Remodelling in a Rat Model of Myocardial Infarction
Bibliographic record
Abstract
The aim of this study was to evaluate the impacts of mesenchymal stem cell (MSC) transplantation on electrophysiological remodelling following myocardial infarction (MI). Methods: Three weeks after coronary ligation, 3×10 6 MSCs, or culture medium alone, were directly injected into infarcted Lewis rat hearts. Hearts were excised one to two weeks later, Langendorff-perfused, optically mapped using the potentiometric dye di-4-ANEPPS, and then fixed and sectioned for morphometric and histological analyses. Gene expression was assessed by qRT-PCR. Results: Optical mapping showed that MSC transplantation attenuated the reduction in conduction velocity (CV) and the prolongation of effective refractory period (ERP) in infarcted hearts. These electrophysiological changes correlated with higher vascular density and better-preserved ventricular wall thickness in MSC-treated hearts. A number of ion channel genes showed post-MI changes in expression. In particular, the expression of Kir2.1, which mediates the inward rectifier K + current I K1 , was reduced in MI and partially restored with MSC transplantation. Conclusion: Apart from well-documented benefits such as promoting angiogenesis and limiting adverse structural remodelling, MSC transplantation improves conduction and reduces refractoriness in infarcted hearts. MSCs also partially restore Kir2.1 expression, which would enhance I K1 and contribute to a more negative resting membrane potential, allowing for more Na + channels to open during depolarization and improving CV. As I K1 contributes to repolarization, restoring Kir2.1 expression would also attenuate ERP prolongation. Our experiments showed that MSCs have the capacity to alter cardiac ion channel expression and mitigate adverse electrophysiological remodelling following MI. Thus MSC transplantation may be a potential strategy to prevent post-MI arrhythmias.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".