Mitochondrial regulation in human pluripotent stem cells during reprogramming and β cell differentiation
Bibliographic record
Abstract
Mitochondria are the powerhouse of the cell and dynamically control fundamental biological processes including cell reprogramming, pluripotency, and lineage specification. Although remarkable progress in induced pluripotent stem cell (iPSC)-derived cell therapies has been made, very little is known about the role of mitochondria and the mechanisms involved in somatic cell reprogramming into iPSC and directed reprogramming of iPSCs in terminally differentiated cells. Reprogramming requires changes in cellular characteristics, genomic and epigenetic regulation, as well as major mitochondrial metabolic changes to sustain iPSC self-renewal, pluripotency, and proliferation. Differentiation of autologous iPSC into terminally differentiated β-like cells requires further metabolic adaptation. Many studies have characterized these alterations in signaling pathways required for the generation and differentiation of iPSC; however, very little is known regarding the metabolic shifts that govern pluripotency transition to tissue-specific lineage differentiation. Understanding such metabolic transitions and how to modulate them is essential for the optimization of differentiation processes to ensure safe iPSC-derived cell therapies. In this review, we summarize the current understanding of mitochondrial metabolism during somatic cell reprogramming to iPSCs and the metabolic shift that occurs during directed differentiation into pancreatic β-like cells.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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) | 0.000 | 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".