Insulin induced lipogenesis and enhanced mRNA level of sterol regulatory element binding protein-1c in primary porcine adipocyte
Bibliographic record
Abstract
Little is known about the development and metabolism of the pig adipocyte, and even less is known about regulation of lipogenesis in the pig adipocyte. The objective of this study was to test the effects of insulin on the morphology of cells, the content of triacylglycerols (TG), the activity of fatty acid synthase (FAS) and the mRNA level of sterol regulatory element binding protein-1c (SREBP-1c) in porcine adipocytes in vitro. Morphologically, larger lipid droplets appeared in the presence of insulin for 48 h. Insulin-induced lipogenesis of primary porcine adipocytes was correlated with the TG content and FAS activity. There was a significant difference in the TG content and FAS activity between the insulin-treated cells and the control cells (P < 0.05); insulin increased the content of TG and FAS activity in a dose-dependent manner and the maximum activity occurred at 150 nmol L-1. The TG content and FAS activity were increased in a dose-dependent manner and maximal values were obtained when adipocytes were incubated with 150 nmol L-1 insulin. The mRNA levels of SREBP-1c were also increased by insulin. In summary, lipogenesis of porcine adipocyte could be induced by insulin in a dose-dependent manner and the induced hypertrophy of porcine adipocytes partially due to the increase of TG content, FAS activity and SREBP-1c mRNA level. Key words: Lipogenesis, porcine, adipocyte, insulin, SREBP-1c
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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 | 0.001 |
| 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".