Low abdominal subcutaneous preadipocyte adipogenesis is associated with visceral obesity, visceral adipocyte hypertrophy, and a dysmetabolic state
Bibliographic record
Abstract
Subcutaneous adipose tissue expansion through adipogenesis is increasingly recognized as a major determinant of body fat distribution and obesity-related cardiometabolic alterations. Our objective was to assess whether adipogenic rates of cultured human primary preadipocytes from the visceral and subcutaneous compartments relate to visceral obesity and cardiometabolic alterations. We recruited 35 women undergoing gynecological surgery and assessed body fat distribution by CT as well as fasting plasma lipids and glycemia. Fat samples from the greater omentum and abdominal subcutaneous (SC) compartments were used to assess mature adipocyte cell size and establish primary preadipocyte cultures. Differentiation was induced using adipogenic media and adipogenic rates were assessed using Oil Red O (ORO) absorbance/DNA content ratio and glyceraldehyde 3-phosphate dehydrogenase (G3PDH) activity/DNA of differentiated cells. We found a lower adipogenic capacity of omental (OM) preadipocytes than SC preadipocytes originating from the same women (P < 0.05). Whereas only OM cell size was different among groups of low vs high OM adipogenic rate, SC adipogenic rates were clearly related to increased OM cell size and dyslipidemia when women were separated on median value of either ORO/DNA or G3PDH activity/DNA ratios. When matched for BMI, women with low SC preadipocyte adipogenic rates had a higher visceral adipose tissue area (P < 0.01), omental adipocyte hypertrophy (P < 0.05), higher VLDL-lipid content (P < 0.01) and higher fasting glycemia (P < 0.05) than those with low SC adipogenic rates. In conclusion, low abdominal subcutaneous preadipocyte differentiation capacity in vitro is associated with visceral obesity, visceral adipocyte hypertrophy, and a dysmetabolic state.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".