iPS Cell–Derived Cardiogenicity is Hindered by Sustained Integration of Reprogramming Transgenes
Bibliographic record
Abstract
BACKGROUND: Nuclear reprogramming inculcates pluripotent capacity by which de novo tissue differentiation is enabled. Yet, introduction of ectopic reprogramming factors may desynchronize natural developmental schedules. This study aims to evaluate the effect of imposed transgene load on the cardiogenic competency of induced pluripotent stem (iPS) cells. METHODS AND RESULTS: Targeted inclusion and exclusion of reprogramming transgenes (c-MYC, KLF4, OCT4, and SOX2) was achieved using a drug-inducible and removable cassette according to the piggyBac transposon/transposase system. Pulsed transgene overexpression, before iPS cell differentiation, hindered cardiogenic outcomes. Delayed in counterparts with maintained integrated transgenes, transgene removal enabled proficient differentiation of iPS cells into functional cardiac tissue. Transgene-free iPS cells generated reproducible beating activity with robust expression of cardiac α-actinin, connexin 43, myosin light chain 2a, α/β-myosin heavy chain, and troponin I. Although operational excitation-contraction coupling was demonstrable in the presence or absence of transgenes, factor-free derivatives exhibited an expedited maturing phenotype with canonical responsiveness to adrenergic stimulation. CONCLUSIONS: A disproportionate stemness load, caused by integrated transgenes, affects the cardiogenic competency of iPS cells. Offload of transgenes in engineered iPS cells ensures integrity of cardiac developmental programs, underscoring the value of nonintegrative nuclear reprogramming for derivation of competent cardiogenic regenerative biologics.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".