The Effects of Hypogonadism and Conjugated Linoleic Acid on Regional Adipose Tissue and Fatty Acid Composition in Male Guinea Pigs
Bibliographic record
Abstract
Background Aging in men is associated with gains in body fat, which are due in part to the age‐related decline in testosterone. Conjugated linoleic acid (CLA) has been consistently shown to reduce body fat or fat gain in animal models through a similarly suggested mechanism as testosterone. Therefore, CLA may counteract the progressive body fat gain that occurs with testosterone decline. Objectives. To determine whether CLA modulates changes in body fat, regional fat distribution and adipose tissue fatty acid composition in hypogonadal male guinea pigs. Methods. Male, retired breeder guinea pigs (n=40, 70‐72 wk) were block randomized by weight into 4 groups: 1) SHAM/ CTRL, 2) SHAM/ CLA diet (1%), 3) Orchidectomy (ORX)/ CTRL diet, 4) ORX/ CLA diet. Dual‐energy x‐ray absorptiometry scans were performed at baseline and 16 wk to analyze body composition. Visceral and subcutaneous adipose fatty acids were extracted and methylated for gas chromatography (GC) analysis to determine fatty acid composition. Results. In ORXCTRL guinea pigs, percent body fat increased by 6.1% and percent lean mass decreased by 6.7 % over the 16 wks while no significant changes in percent body composition were observed in ORXCLA guinea pigs. Guinea pigs fed CLA diet gained less % total body fat and % upper and lower body fat than those fed CTRL regardless of surgical treatment. Regional adipose tissue of fatty acid composition showed that it was reflective of dietary fatty acids. Conclusion Hypogonadism in male guinea pigs results in increased fat mass and decreased lean mass. CLA is effective in reducing fat gain and maintaining lean mass in both hypogonadal and intact guinea pigs.
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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 | 0.001 | 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 | 0.001 |
| 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".