Pathways of adipose tissue androgen metabolism in women: depot differences and modulation by adipogenesis
Why this work is in the frame
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Bibliographic record
Abstract
The objective was to examine pathways of androgen metabolism in abdominal adipose tissue in women. Abdominal subcutaneous (SC) and omental (OM) adipose tissue samples were surgically obtained in women. Total RNA was isolated from whole adipose tissue samples and from primary preadipocyte cultures before and after induction of differentiation. Expression levels of several steroid-converting enzyme transcripts were examined by real-time RT-PCR. Androgen conversion rates were also measured. We found higher expression levels in SC compared with OM adipose tissue for type 1 3beta-hydroxysteroid dehydrogenase (3beta-HSD-1; P < 0.05), for aldo-keto reductase 1C3 (AKR1C3; P < 0.0001), for AKR1C2 (P < 0.0001), and for the androgen receptor (P < 0.0001). 17beta-HSD-2 mRNA levels were lower in SC adipose tissue (P < 0.05). Induction of adipocyte differentiation led to significantly increased expression levels in SC cultures for AKR1C3 (4.7-fold, P < 0.01), 11-cis-retinol dehydrogenase (6.9-fold, P < 0.02), AKR1C2 (5.6-fold, P < 0.004), P-450 aromatase (5.7-fold, P < 0.02), steroid sulfatase (3.1-fold, P < 0.02), estrogen receptor-beta (11.8-fold, P < 0.01), and the androgen receptor (4.0-fold, P < 0.0005). Generally similar but nonsignificant trends were obtained in OM cultures. DHT inactivation rates increased with differentiation, this effect being mediated by dexamethasone alone, through a glucocorticoid receptor-dependent mechanism. In conclusion, higher mRNA levels of enzymes synthesizing and inactivating androgens are found in differentiated adipocytes, consistent with higher androgen-processing rates in these cells. Glucocorticoid-induced androgen inactivation may locally modulate the exposure of adipose cells to active androgens.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it