Effects of oleic acid and chicken serum on the expression of adipogenic transcription factors and adipogenic differentiation in hen preadipocytes
Bibliographic record
Abstract
We have examined the effect of oleic acid (OA) concentrations and incubation time, along with chicken serum (CS), on adipogenic differentiation and expression of adipogenic transcripts in hen preadipocytes. Preadipocytes were treated with (i) an adipogenic cocktail (DMI) containing 500 nM dexamethasone, 0.5 mM 3-isobutyl-1-methylxanthine and 20 µg/mL insulin alone and DMI + 75, 150, 300 or 600 µM OA for 48 h; (ii) DMI + 300 µM OA (DMIOA) for 6, 12, 24 or 48 h; and (iii) foetal bovine serum (FBS), CS, DMI + FBS, DMI + CS, DMIOA + FBS and DMIOA + CS. While FABP4 was significantly expressed with increasing concentrations of OA, the expression of C/EBPβ, LEPR and FAS were unchanged compared with the control. PPARγ2 expression was unchanged across all time-points. A significantly higher level of C/EBPα was measured at 48 h, but the levels of C/EBPβ increased after 12 h. Levels of FABP4 significantly increased with the time of incubation after 12 h, but that of LPL was reduced (P < 0.05) at 6, 24 and 48 h. FABP4 was highly expressed in cells treated with CS, DMI + CS and DMIOA + CS compared to cells treated with FBS, DMI + FBS and DMIOA + FBS. In conclusion, increased concentrations of OA and incubation time increases lipid accumulation; FABP4 and C/EBPβ are potential transcription factors regulating OA induced adipogenesis of fat cells obtained from laying hen. CS is a potent inducer of adipogenic differentiation in hen preadipocytes.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".