DHCR24-Knockout Embryonic Fibroblasts Are Susceptible to Serum Withdrawal-Induced Apoptosis Because of Dysfunction of Caveolae and Insulin-Akt-Bad Signaling
Bibliographic record
Abstract
The DHCR24 gene encodes an enzyme catalyzing the last step of cholesterol biosynthesis, the conversion of desmosterol to cholesterol. To elucidate the physiological significance of cholesterol biosynthesis in mammalian cells, we investigated proliferation of mouse embryonic fibroblasts (MEFs) prepared from DHCR24(-/-) mice. Both DHCR24(-/-) and wild-type MEFs proliferated in the presence of serum in culture media. However, the inhibition of external cholesterol supply by serum withdrawal induced apoptosis of DHCR24(-/-) MEFs, which was associated with a marked decrease in the intracellular and plasma membrane cholesterol levels, Akt inactivation, and Bad dephosphorylation. Insulin is an antiapoptotic factor capable of stimulating the Akt-Bad cascade, and its receptor (IR) is enriched in caveolae, cholesterol-rich microdomains of plasma membrane. We thus analyzed the association of IR and caveolae in the cholesterol-depleted MEFs. Subcellular fractionation and immunocytochemical analyses revealed that the IR and caveolin-1 contents were markedly reduced in the caveolae fraction of the MEFs, suggesting the disruption of caveolae, and that large amounts of IR were present apart from caveolin-1 on plasma membrane, indicating the uncoupling of IR with caveolae. Consistent with these findings, insulin-dependent phosphorylations of insulin receptor substrate-1, Akt, and Bad were impaired in the cholesterol-depleted MEFs. However, this impairment was partial because treatment of the MEFs with insulin restored Akt activation and prevented apoptosis. Cholesterol supply also prevented apoptosis. These results demonstrate that the cellular cholesterol biosynthesis is critical for the activation and maintenance of the Akt-Bad cell survival cascade in response to growth factors such as insulin.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".