Dynamic upregulation of CD24 in pre-adipocytes promotes adipogenesis
Bibliographic record
Abstract
The development of mature adipocytes from pre-adipocytes is a highly regulated process. CD24 is a glycophosphatidylinositol-linked cell surface receptor that has been identified as a critical cell surface marker for identifying pre-adipocytes that are able to reconstitute white adipose tissue (WAT) in vivo. Here, we examined the role and regulation of CD24 during adipogenesis in vitro. We found that CD24 mRNA and protein expression is upregulated early during adipogenesis in the 3T3-L1 pre-adipocytes and in murine primary pre-adipocytes isolated from subcutaneous and visceral WAT, followed by downregulation in mature adipocytes. CD24 mRNA expression was found to be dependent on increased transcription due to increased promoter activity in response to activation of a pre-existing transcriptional regulator. Furthermore, either intracellular cAMP or dexamethasone were sufficient to increase expression in pre-adipocytes, while both additively increased CD24 expression. Preventing the increase in CD24 expression, by siRNA-mediated knock-down, resulted in fewer mature lipid-laden adipocytes and decreased expression of mature adipogenic genes. Therefore, conditions experienced during adipogenesis in vitro are sufficient to increase CD24 expression, which is necessary for differentiation. Overall, we conclude that the dynamic upregulation of CD24 actively promotes adipogenesis in vitro.
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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 | 0.001 |
| 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".