Mitochondrial Biogenesis and Energy Production in Differentiating Murine Stem Cells: A Functional Metabolic Study
Bibliographic record
Abstract
The significance of metabolic networks in guiding the fate of the stem cell differentiation is only beginning to emerge. Oxidative metabolism has been suggested to play a major role during this process. Therefore, it is critical to understand the underlying mechanisms of metabolic alterations occurring in stem cells to manipulate the ultimate outcome of these pluripotent cells. Here, using P19 murine embryonal carcinoma cells as a model system, the role of mitochondrial biogenesis and the modulation of metabolic networks during dimethyl sulfoxide (DMSO)-induced differentiation are revealed. Blue native polyacrylamide gel electrophoresis (BN-PAGE) technology aided in profiling key enzymes, such as hexokinase (HK) [EC 2.7.1.1], glucose-6-phosphate isomerase (GPI) [EC 5.3.1.9], pyruvate kinase (PK) [EC 2.7.1.40], Complex I [EC 1.6.5.3], and Complex IV [EC 1.9.3.1], that are involved in the energy budget of the differentiated cells. Mitochondrial adenosine triphosphate (ATP) production was shown to be increased in DMSO-treated cells upon exposure to the tricarboxylic acid (TCA) cycle substrates, such as succinate and malate. The increased mitochondrial activity and biogenesis were further confirmed by immunofluorescence microscopy. Collectively, the results indicate that oxidative energy metabolism and mitochondrial biogenesis were sharply upregulated in DMSO-differentiated P19 cells. This functional metabolic and proteomic study provides further evidence that modulation of mitochondrial energy metabolism is a pivotal component of the cellular differentiation process and may dictate the final destiny of stem cells.
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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) | 0.000 | 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 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".