An Enriched Mixture of Trans-10,Cis-12-CLA Inhibits Linoleic Acid Metabolism and PGE2 Synthesis in MDA-MB-231 Cells
Why this work is in the frame
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Bibliographic record
Abstract
Conjugated linoleic acid (CLA) isomers are potent inhibitors of mammary tumor cell growth. Evidence suggests that CLA modulates essential fatty acid (EFA) metabolism; however, it is not clear which parts of this pathway are important regulatory points modulated by CLA. Enriched mixtures of D9-cis,11-trans (D9c,11t)- and D10-trans,12-cis (D10t,12c)-18:2 were used to assess outcome measures of EFA metabolism pertaining to membrane phospholipid incorporation, tumor cell growth, and prostaglandin E2 (PGE2) synthesis in the MDA-MB-231 mammary tumor cell line. Tumor cells were treated with linoleic acid (LA), an equal mixture (Mix), or enriched preparations of D9c,11t- or D10t,12c-18:2. Treatment with Mix or the enriched mixture of D10t,12c-18:2 significantly inhibited the synthesis of arachidonic acid (AA) from LA, resulting in increased levels of LA and decreased levels of AA in membrane phosphatidylcholine and phosphatidylethanolamine (P < 0.05). LA and AA levels were not altered in cells treated with enriched D9c,11t-18:2 and were similar to those in LA control treated cells. All CLA treatments reduced [3H]thymidine uptake, an indicator of tumor cell growth, by more than one-half relative to LA controls. MDA-MB-231 cells challenged with AA in the presence of all CLA mixtures resulted in significantly reduced PGE2 synthesis relative to controls treated with LA (P < 0.05). It is evident that individual isomers exert inhibitory effects at specific steps of EFA metabolism, which correspondingly leads to a reduction in PGE2 synthesis and, ultimately, tumor growth.
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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 | 0.000 | 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) | 0.001 | 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 it