Expression of Genes Related to Prostaglandin Synthesis or Signaling in Human Subcutaneous and Omental Adipose Tissue: Depot Differences and Modulation by Adipogenesis
Bibliographic record
Abstract
OBJECTIVES: (1) To examine depot-specific PGE2 and PGF2α release and mRNA expression of enzymes or receptors involved in PG synthesis or signaling in human adipose tissues; (2) to identify changes in expression of these transcripts through preadipocyte differentiation; and (3) to examine associations between adipose tissue mRNA expression of these transcripts and adiposity measurements. METHODS: Fat samples were obtained surgically in women. PGE2 and PGF2α release by preadipocytes and adipose tissue explants was measured. Expression levels of mRNA coding for enzymes or receptors involved in PG synthesis or signaling were measured by RT-PCR. RESULTS: Cultured preadipocytes and explants from omental fat released more PGE2 and PGF2α than those from the subcutaneous depot and the corresponding transcripts showed consistent depot differences. Following preadipocyte differentiation, expression of PLA2G16 and PTGER3 mRNA was significantly increased whereas COX-1, COX-2, PTGIS, and PTGES mRNA abundance were decreased in both compartments (P ≤ 0.01 for all). Transcripts that were stimulated during adipogenesis were those that correlated best with adiposity measurements. CONCLUSION: Cells from the omental fat compartment release more PGE2 and PGF2α than those from the subcutaneous depot. Obesity modulates expression of PG-synthesizing enzymes and PG receptors which likely occurs through adipogenesis-induced changes in expression of these transcripts.
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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".