Effects of Male Hypogonadism on Regional Adipose Tissue Fatty Acid Storage and Lipogenic Proteins
Bibliographic record
Abstract
Testosterone has long been known to affect body fat distribution, although the underlying mechanisms remain elusive. We investigated the effects of chronic hypogonadism in men on adipose tissue fatty acid (FA) storage and FA storage factors. Twelve men with chronic hypogonadism and 13 control men matched for age and body composition: 1) underwent measures of body composition with dual energy x-ray absorptiometry and an abdominal CT scan; 2) consumed an experimental meal containing [(3)H]triolein to determine the fate of meal FA (biopsy-measured adipose storage vs. oxidation); 3) received infusions of [U-(13)C]palmitate and [1-(14)C]palmitate to measure rates of direct free (F)FA storage (adipose biopsies). Adipose tissue lipoprotein lipase, acyl-CoA synthetase (ACS), and diacylglycerol acetyl-transferase (DGAT) activities, as well as, CD36 content were measured to understand the mechanism by which alterations in fat storage occur in response to testosterone deficiency. Results of the study showed that hypogonadal men stored a greater proportion of both dietary FA and FFA in lower body subcutaneous fat than did eugonadal men (both p<0.05). Femoral adipose tissue ACS activity was significantly greater in hypogonadal than eugonadal men, whereas CD36 and DGAT were not different between the two groups. The relationships between these proteins and FA storage varied somewhat between the two groups. We conclude that chronic effects of testosterone deficiency has effects on leg adipose tissue ACS activity which may relate to greater lower body FA storage. These results provide further insight into the role of androgens in body fat distribution and adipose tissue metabolism in humans.
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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) | 0.002 | 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".