Novel Genes of Visceral Adiposity: Identification of Mouse and Human Mesenteric Estrogen-Dependent Adipose (MEDA)-4 Gene and Its Adipogenic Function
Bibliographic record
Abstract
Visceral adiposity represents a high risk factor for type 2 diabetes, metabolic syndrome, and cardiovascular disease as well as various cancers. While studying sex hormone imbalance-induced early obesity and late onset of insulin resistance in FSH receptor knock out female mice, we identified a novel mesenteric estrogen-dependent adipose gene (MEDA-4) selectively up-regulated in a depot-specific manner in mesenteric adipose tissue. Meda-4 cloned from both mouse and human adipose tissue codes for a 34-kDa cytosolic protein with 91% homology. Mouse Meda-4 mRNA is expressed highest in visceral adipose tissue and localizes predominantly in the adipocyte fraction. Human MEDA-4 is also more abundant in omental fat than sc depot in obese patients. In 3T3-L1 cells endogenous Meda-4 expression increases early during differentiation, and its overexpression promotes differentiation of preadipocytes into adipocytes and enhances glucose uptake. Conversely, short hairpin RNA-mediated knockdown of Meda-4 reduces both adipogenic and glucose uptake potential. In promoting adipogenesis, Meda-4 up-regulates transcription factor peroxisome proliferator-activated receptor-γ2. Meda-4 promotes lipid accumulation in adipocytes, regulating adipocyte fatty acid-binding protein 2, CD36, lipoprotein lipase, hormone-sensitive lipase, acyl-Coenzyme A oxidase-1, perilipin-1, and fatty acid synthase expression. 17β-Estradiol reduced Meda-4 expression in mesenteric adipose tissue of ovariectomized mice and in 3T3-L1 adipocytes. Thus our study identifies Meda-4 as a novel adipogenic gene, capable of promoting differentiation of preadipocytes into adipocytes, increasing lipid content and glucose uptake in adipocytes. Therefore it might play an important role in adipose tissue expansion in normal and aberrant hormonal conditions and pathophysiological states.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".