Region‐specific alterations in adipose tissue function: cardiometabolic risk goes belly‐up
Bibliographic record
Abstract
Human body fat distribution patterns are heterogeneous and result from extrinsic influences (e.g. hormonal effects) and regional differences in intrinsic properties of adipose cells. The capacity of preadipocytes to differentiate and then store or mobilize lipids in each fat compartment is a major determinant of body fat distribution patterns. It also reflects the metabolic role of the cells of each region and directly relates to the high cardiometabolic risk closely associated with abdominal, visceral obesity. Visceral adipocytes (e.g. omental cells) are efficient for hypertrophy through lipid storage and show high lipolytic responsiveness, whereas subcutaneous cells have a high capacity for hyperplasia. We examined the potential of omental and subcutaneous adipose tissues as stem cell sources using the ceiling culture approach of adipocyte dedifferentiation. This cellular process generates multipotent mesenchymal stem cells through rapid downregulation of lipogenic/adipogenic transcripts and activation of matrix remodelling programs. Dedifferentiation is slightly more effective in subcutaneous than omental cells. Thus, adipose cell characteristics and origin closely relate to metabolic status and stem cell properties.
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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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".