Effect of <i>trans</i>8, <i>cis</i>10+<i>cis</i>9, <i>trans</i>11 Conjugated Linoleic Acid Mixture on Lipid Metabolism in 3T3‐L1 Cells
Bibliographic record
Abstract
Evidence suggests that minor isomers of conjugated linoleic acid (CLA), such as trans8, cis10 CLA, can elicit unique biological effects of their own. In order to determine the effect of a mixture of t8, c10+c9, t11 CLA isomers on selected aspects of lipid metabolism, 3T3-L1 preadipocytes were differentiated for 8 days in the presence of 100 microM linoleic acid (LA); t8, c10+c9, t11 CLA; t10, c12+c9, t11 CLA or purified c9, t11 CLA. Whereas supplementation with c9, t11 and t10, c12+c9, t11 CLA resulted in cellular triglyceride (TG) concentrations of 3.4 +/- 0.26 and 1.3 +/- 0.11 microg TG/microg protein, respectively (P < 0.05), TG accumulation following treatment with CLA mixture t8, c10+c9, t11 was significantly intermediate (2.5 +/- 0.22 microg TG/microg protein, P < 0.05) between the two other CLA treatments. However, these effects were not attributable to an alteration of the Delta(9) desaturation index. Adiponectin content of adipocytes treated with t8, c10+c9, t11 mixture was similar to the individual isomer c9, t11 CLA, and both the t8, c10+c9, t11 and c9, t11 CLA groups were greater (P < 0.05) than in the t10, c12+c9, t11 CLA group. Overall, these results suggest that t8, c10+c9, t11 CLA mixture affects TG accumulation in 3T3-L1 cells differently from the c9, t11 and t10, c12 isomers. Furthermore, the reductions in TG accumulation occur without adversely affecting the adiponectin content of these cells.
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How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".