Effect of conjugated linoleic acid type, treatment period, and dosage on differentiation of 3T3 cells
Bibliographic record
Abstract
This study was conducted to determine effect of CLA and linoleic acid (LA) on cell differentiation, cellular glycerol-3-phosphate dehydrogenase (GPDH) activity, and FA accumulation in differentiating 3T3-L1 cells (3 isomers x 3 treatment periods x 4 doses). The cells were cultured in 24-well plates for proliferation until confluence. Then they were treated with media containing 0, 10, 35, or 70 mg/L (0, 35, 125, or 250 mmol/L, respectively) of LA, cis9,trans11- or trans10,cis12-CLA during early (day 0-2), intermediate and late (day 3-8), or overall (day 0-8) differentiation periods. Dexamethasone, methyl-isobutylxanthine, and insulin were supplemented to the media only for the early period to induce the differentiation. On day 8 of postconfluence the cells were harvested for Oil Red O staining, analysis of GPDH activity, and determination of the FA Concentration. Cellular LA or CLA was found to accumulate in a dose-response manner, mainly during the intermediate/late period. Treatment with trans10,cis12-CLA lowered (P < 0.05) GPDH activity and the concentration of FA including palmitic acid (16:0) and palmitoleic acid (16:1), especially during the intermediate/late and overall periods, or whenever a high dose of 70 mg/L was applied. This also resulted in a higher (P < 0.05) ratio of saturated FA to monounsaturated FA. Treatment with LA or cis9,trans11-CLA lowered cellular FA only when they applied during the early period at a dose of 70 mg/L. The results demonstrated that the inhibitory effects of CLA on differentiation, GPDH activity, and FA accumulation of 3T3-L1 cells are dependent on the isomer type, treatment period, and dose.
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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) | 0.001 | 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 | 0.001 |
| 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".