A Survey of Genes Differentially Expressed in Subcutaneous and Visceral Adipose Tissue in Men*
Bibliographic record
Abstract
Adipose tissue located within the abdominal cavity has been suggested to be functionally and metabolically distinct from that of the subcutaneous compartment. These differences could play a role in obesity-related complications. The aim of this study was to compare gene expression profiles of subcutaneous and visceral adipose tissues of 10 nondiabetic, normolipidemic obese men. Affymetrix human U133A arrays (10 arrays for subcutaneous fat samples and 10 arrays for visceral fat samples) were used. Differential gene expression was confirmed by real-time polymerase chain reaction in a subset of genes. A total of 5894 transcripts were detected in both depots in all 10 subjects, and 409 transcripts representing 347 encoded genes were differentially expressed. Of these, 131 genes were expressed at higher levels in subcutaneous adipose tissue, and 216 were expressed more abundantly in visceral fat. Differentially expressed profiles included genes of the Wnt signaling pathway, as well as CEPBA and HOX genes. In addition, genes involved in lipolytic stimuli and cytokine secretion were differentially expressed. The identification of a consistent and rather uniform pattern of differentially expressed genes between the two fat depots using multiple array replicates (10 arrays per fat compartment) generated new perspectives for future research on regional differences in adipose tissue biology.
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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 | 0.000 | 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".