Induction of differentiation and metabolic reprogramming in human hepatoma cells by adult human serum
Bibliographic record
Abstract
Abstract Tissue culture medium routinely contains fetal bovine serum (FBS). Here we show that culturing human hepatoma cells in their native, adult serum (human serum, HS) results in the restoration of key morphological and metabolic features of normal liver cells. When moved to HS, these cells show differential transcription of 22-32% of the genes, stop proliferating, and assume a hepatocyte-like morphology. Metabolic analysis shows that the Warburg-like metabolic profile, typical for FBS-cultured cells, is replaced by a diverse metabolic profile consistent with in vivo hepatocytes. We demonstrate the formation of large lipid and glycogen stores, increased glycogenesis, increased β-oxidation, increased ketogenesis, and decreased glycolysis. Finally, organ-specific functions are restored, including xenobiotics degradation and secretion of bile, very low density lipoprotein, and albumin. Thus, organ-specific functions are not necessarily lost in cell cultures, but might be merely suppressed in FBS. Together, we showed that cells that are representative of normal physiology can be produced from cancer cells simply by replacing FBS by HS in culture media. The effect of serum is often overseen in cell culture and we provide a detailed study in the changes that occur, provide insight in some of the serum components that may play a role in the establishment of the different phenotypes, and discuss how these finding might be beneficial to a variety of research fields.
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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".