Silencing ANGPTL8 reduces mouse preadipocyte differentiation and insulin signaling
Bibliographic record
Abstract
ANGPTL8, expressed mainly in the liver and adipose tissue, regulates the activity of lipoprotein lipase (LPL) present in the extracellular space and triglyceride (TG) metabolism through its interaction with ANGPTL3 and ANGPTL4. Whether intracellular ANGPTL8 can also exert effects in tissues where it is expressed is uncertain. ANGPTL8 expression was low in preadipocytes and much increased during differentiation. To better understand the role of intracellular ANGPTL8 in adipocytes and assess whether it may play a role in adipocyte differentiation, we knocked down its expression in normal mouse subcutaneous preadipocytes. ANGPTL8 knockdown reduced adipocyte differentiation, cellular TG accumulation and also isoproterenol-stimulated lipolysis at day 7 of differentiation. RNA-Seq analysis of ANGPTL8 siRNA or control siRNA transfected SC preadipocytes on days 0, 2, 4 and 7 of differentiation showed that ANGPTL8 knockdown impeded the early (day 2) expression of adipogenic and insulin signaling genes, PPARγ, as well as genes related to extracellular matrix and NF-κB signaling. Insulin mediated Akt phosphorylation was reduced at an early stage during adipocyte differentiation. This study based on normal primary cells shows that ANGPTL8 has intracellular actions in addition to effects in the extracellular space, like modulating LPL activity. Preadipocyte ANGPTL8 expression modulates their differentiation possibly via changes in insulin signaling gene expression.
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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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".