Phenamil enhances the adipogenic differentiation of hen preadipocytes
Bibliographic record
Abstract
A study was conducted to examine the effect of phenamil on adipogenic differentiation and expression of key adipogenic transcripts in hen preadipocytes. Preadipocytes were isolated from 20-week old Single Comb White Leghorn hens (Gallas gallus, Lohman strain). The experiment lasted for 48 h and had six treatments. Non-treated control (C) cells, cells treated with dexamethasone, 3-isobutyl-1-methylxanthine, insulin, and oleic acid (DMIOA) (T1), DMIOA + 15 μM phenamil (T2), DMIOA + 30 μM phenamil (T3), 15 μM phenamil alone (T4), and 30 μM phenamil alone (T5). Neutral lipid accumulation and the mRNA expression of key adipogenic transcripts were measured in all treatments and compared. Lipid accumulation was detected in T1, T2, and T3 only. Expression of peroxisome proliferator receptor-activator gamma 2 (PPARγ2), the core enhancer binding protein α (C/EBPα), C/EBPβ, fatty acid binding protein 4 (FABP4), and lipoprotein lipase (LPL) as well as ETS variant 4 (ETV4) and 5 was higher (P < 0.05) in T2, T3, T4, and T5 compared to C. Expression of these transcripts was higher (P < 0.05) in T2 and T3 compared to T4 and T5. The core enhancer binding protein α, C/EBPβ, and FABP4 were highly expressed (P < 0.05) in T1 compared to C. However, the expression of PPARγ2, LPL, and ETV4 and ETV5 was not significantly different. Expression of C/EBPα, C/EBPβ, and FABP4 was higher (P < 0.05) in T2 and T3 compared to T1. Expression of sterol regulatory element binding protein 1 (SREBP1) and leptin receptor (LEPR) was not significantly different among the treatments. In conclusion, phenamil enhances DMIOA-induced adipogenic differentiation of hen preadipocytes but does not induce adipogenesis by itself.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".