Effects of dietary conjugated linoleic acid on the expression of uncoupling proteins in mice and rats
Bibliographic record
Abstract
CLA inhibits mammary cancer and reduces body fat accumulation in rodents. It is not known whether uncoupling proteins (UCP), which are modulators of energy balance and metabolism, play a role in these actions of CLA. To determine the effects of dietary CLA on the expression of UCP in various tissues, 5-wk-old Sprague-Dawley rats and C57Bl/6 mice were fed diets containing 1% CLA for 3 wk. CLA treatment reduced adipose depot weights in both rats and mice but had no significant effects on body weight. There was a species-specific effect of CLA on the expression of UCP. Whereas CLA did not affect the expression of UCP in most tissues in rats, mice fed CLA had increased expression of UCP2 in the mammary gland, brown adipose tissue (BAT), and white adipose tissue (WAT). Furthermore, UCP1 and UCP3 mRNA and protein levels in BAT were significantly lower in CLA-fed mice compared to controls. Skeletal muscle UCP3 mRNA was unchanged, but UCP3 protein levels were significantly increased in mice, suggesting translational or posttranslational regulation of this protein. Results from this study suggest that alterations in the expression of UCP in mice may be related to the previously reported effects of dietary CLA in lowering adiposity and increasing FA oxidation. In rats, however, induction of UCP is not likely to be responsible for fat reduction or for the inhibitory action of CLA on mammary carcinogenesis.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".