Metabolic profile and differentiation potential of extraembryonic endoderm-like cells
Bibliographic record
Abstract
Glucose metabolism has a crucial role for providing substrates required to generate ATP and regulate the epigenetic landscape. We reported that F9 embryonal carcinoma stem-like cells require cytosolic reactive oxygen species to differentiate into extraembryonic endoderm; however, mitochondrial sources were not examined. To extend these studies, we examined the metabolic profile of early and late-passage F9 cells, and show that their ability to differentiate is similar, even though each population has dramatically different metabolic profiles. Differentiated early-passage cells relied on glycolysis, while differentiated late-passage cells transitioned towards oxidative phosphorylation (OXPHOS). Unexpectedly, electron transport chain protein stoichiometry was disrupted in differentiated late-passage cells, whereas genes encoding mitofusion 1 and 2, which promote mitochondrial fusion and favor OXPHOS, were upregulated in differentiated early-passage cells. Despite this, early-passage cells cultured under conditions to promote glycolysis showed enhanced differentiation, whereas promoting OXPHOS in late-passage cells showed a similar trend. Further analysis revealed that the distinct metabolic profiles seen between the two populations is largely associated with changes in genomic integrity, linking metabolism to passage number. Together, these results indicate that passaging has no effect on the potential for F9 cells to differentiate into extraembryonic endoderm; however, it does impact their metabolic profile. Thus, it is imperative to determine the molecular and metabolic status of a stem cell population before considering its utility as a therapeutic tool for regenerative medicine.
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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 | 0.000 | 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".