Subcutaneous Adipose Tissue Metabolism at Menopause: Importance of Body Fatness and Regional Fat Distribution<sup>1</sup>
Bibliographic record
Abstract
The aim of this study was to examine the contribution of menopause per se on sc adipose tissue (AT) metabolism in 16 women classified on the basis of their menopausal status: 8 postmenopausal (mean +/- SD age, 57 +/- 6 yr) vs. 8 premenopausal individuals (37 +/- 5 yr). These 2 groups were matched for sc abdominal adipose cell size (within 0.02 microg lipid/cell) and visceral AT accumulation (within 15 cm2), measured by computed tomography. Fasting plasma glucose and insulin levels as well as their responses to an oral glucose load were similar regardless of the women's hormonal status. Subcutaneous abdominal and femoral AT lipoprotein lipase activities as well as fat cell lipolysis were determined in both groups. Epinephrine induced antilipolysis at low concentrations and lipolysis at higher doses in both adipose sites and groups. The maximal lipolytic response to epinephrine or to isoproterenol (beta-adrenergic agonist) as well as the maximal antilipolytic effect of either the catecholamine or UK-14304 (alpha2-adrenergic agonist) assessed in sc adipocytes were similar in pre- and postmenopausal women. In addition, neither the beta- nor the alpha2-adrenoceptor sensitivity of sc adipose cells differed according to subjects' age. Finally, maximal lipolysis promoted by postadrenoceptor agents and AT-lipoprotein lipase activity did not vary among adipose regions or between groups. Taken together, these results suggest that menopause per se does not influence sc AT metabolism once the variation related to adipose cell size and total body fatness is taken into account.
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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".