Rapamycin Inhibits Human Adipocyte Differentiation in Primary Culture
Bibliographic record
Abstract
OBJECTIVE: The immunosuppressant drug rapamycin, has been reported to inhibit 3T3-L1 adipocyte differentiation by interfering with critical postconfluent mitoses that are required early on for successful differentiation of this cell line (clonal expansion phase). In contrast to the murine 3T3-L1 preadipocyte cell line, human preadipocytes in primary culture do not undergo clonal expansion during differentiation. We investigated whether rapamycin could inhibit human adipocyte differentiation. RESEARCH METHODS AND PROCEDURES: The effect of rapamycin on the induction of differentiation of human preadipocytes in primary culture into adipocytes was measured using Oil Red O staining and glycerol phosphate dehydrogenase activity. RESULTS: We have observed that rapamycin severely curtails human adipocyte differentiation of both omental and abdominal subcutaneous preadipocytes (to 14% and 19% of standard differentiation, respectively). The rapamycin-mediated inhibition of human adipocyte differentiation could be reversed in the presence of excess amounts of FK-506, which displaces rapamycin from its intracellular receptor, FKPB12. Measurement of cytosolic protein and [3H]thymidine incorporation into DNA confirmed the absence of proliferation during differentiation of human preadipocytes in primary culture. DISCUSSION: Our data indicate that rapamycin exerts important negative regulatory effects on adipogenesis in human preadipocytes, through a mechanism that does not depend on interruption of clonal expansion.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.006 |
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".