The Mixed-Lineage Kinase DLK Is a Key Regulator of 3T3-L1 Adipocyte Differentiation
Bibliographic record
Abstract
BACKGROUND: The mixed-lineage kinase (MLK) family member DLK has been proposed to serve as a regulator of differentiation in various cell types; however, its role in adipogenesis has not been investigated. In this study, we used the 3T3-L1 preadipocyte cell line as a model to examine the function of DLK in adipocyte differentiation. METHODS AND FINDINGS: Immunoblot analyses and kinase assays performed on 3T3-L1 cells showed that the expression and activity of DLK substantially increase as differentiation occurs. Interestingly, DLK appears crucial for differentiation since its depletion by RNA interference impairs lipid accumulation as well as expression of the master regulators of adipogenesis C/EBPalpha and PPARgamma2 at both the mRNA and protein levels. In contrast, neither the expression nor the DNA binding activity of C/EBPbeta, an activator for C/EBPalpha and PPARgamma, is affected by DLK loss. CONCLUSIONS: Taken together, these results suggest that DLK is important for expression of mature adipocyte markers and that its action most likely takes place via regulation of C/EBPbeta transcriptional activity and/or initiation of C/EBPalpha and PPARgamma2 gene transcription.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".