Visfatin expression is hormonally regulated by metabolic and sex hormones in 3T3‐L1 pre‐adipocytes and adipocytes
Bibliographic record
Abstract
AIM: The novel adipokine visfatin has 'insulin-mimicking' effects and is increased in models of diet-induced obesity, but factors that regulate visfatin have not been fully elucidated. METHODS: In order to determine visfatin regulation in adipocyte development and metabolism, as well as in pathophysiological conditions related to metabolic syndrome, endogenous visfatin expression was measured in 3T3-L1 pre-adipocytes and adipocytes using real-time reverse transcriptase polymerase chain reaction (real-time RT-PCR). RESULTS: A marked increase in visfatin expression was observed during differentiation, with a 2.2-fold increase between preconfluent and 2-day confluent cells even before differentiation was initiated. A further 4.1-fold increase was induced from day 0 to day 9 of differentiation (overall ninefold). Overnight incubation with dexamethasone (10(-8) to 10(-2) M) increased visfatin expression in both pre-adipocytes (1.5- to 3.3-fold, p < 0.05) and adipocytes (1.9-fold, p < 0.01). All other treatments decreased visfatin expression. In pre-adipocytes, visfatin expression decreased by 23% at a concentration of 1 microM insulin, 15% at 1-15 nM T3, 15% at 10 nM-1 microM progesterone, 33-44% at 10 nM-1 microM testosterone, 50% with palmitate and 30% with oleate (p < 0.05 for all). In adipocytes, insulin had a much greater effect, decreasing visfatin by 77% at 100 nM (p < 0.01), whereas oleate and sex hormones did not affect visfatin expression. However, tumor necrosis factor alpha, which had no effect on pre-adipocytes, significantly decreased visfatin in adipocytes by 26% at 10 ng/ml (p < 0.05). Interestingly, the thiazolidinedione (TZD) rosiglitizone also decreased visfatin by 28% at a concentration of 1 microM (p < 0.01). CONCLUSION: In summary, while the mechanism of visfatin action remains to be elucidated, the clear effects of multiple hormones on visfatin expression support a physiological role.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".