Cardiac regenerative capacity is age- and disease-dependent in childhood heart disease
Bibliographic record
Abstract
OBJECTIVE: We sought to define the intrinsic stem cell capacity in pediatric heart lesions, and the effects of diagnosis and of age, in order to inform evidence-based use of potential autologous stem cell sources for regenerative medicine therapy. METHODS: Ventricular explants derived from patients with hypoplastic left heart syndrome (HLHS), tetralogy of Fallot (TF), dilated cardiomyopathy (DCM) and ventricular septal defect (VSD) were analyzed following standard in vitro culture conditions, which yielded cardiospheres (C-spheres), indicative of endogenous stem cell capacity. C-sphere counts generated per 5 mm3 tissue explant and the presence of cardiac progenitor cells were correlated to patient age, diagnosis and echocardiographic function. RESULTS: Cardiac explants from patients less than one year of age with TF and DCM robustly generated c-kit- and/or vimentin-positive cardiac mesenchymal cells (CMCs), populating spontaneously forming C-spheres. Beyond one year of age, there was a marked reduction or absence of cardiac explant-derivable cardiac stem cell content in patients with TF, VSD and DCM. Stem cell content in HLHS and DCM strongly correlated to the echocardiographic function in the corresponding ventricular chamber, with better echocardiographic function correlating to a more robust regenerative cellular content. CONCLUSIONS: We conclude that autologous cardiomyogenic potential in pediatric heart lesions is robust during the first year of life and uniformly declines thereafter. Depletion of stem cell content occurs at an earlier age in HLHS with the onset of ventricular failure in a chamber-specific pattern that correlates directly to ventricular dysfunction. These data suggest that regenerative therapies using autologous cellular sources should be implemented in the neonatal period before the potentially rapid onset of single ventricle failure in HLHS or the evolution of biventricular failure in DCM.
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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 | 0.001 |
| 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".