A trans 10-18:1 enriched fraction from beef fed a barley grain-based diet induces lipogenic gene expression and reduces viability of HepG2 cells
Bibliographic record
Abstract
Beef fat is a natural source of trans (t) fatty acids, and is typically enriched with either t 10-18:1 or t 11-18:1. Little is known about the bioactivity of individual t -18:1 isomers, and the present study compared the effects of t 9-18:1, cis ( c )9-18:1 and trans (t) -18:1 fractions isolated from beef fat enriched with either t 10-18:1 (HT10) or t 11-18:1 (HT11). All 18:1 isomers resulted in reduced human liver (HepG2) cell viability relative to control. Both c 9-18:1 and HT11were the least toxic, t 9-18:1had dose response increased toxicity, and HT10 had the greatest toxicity ( P <0.05). Incorporation of t 18:1 isomers was 1.8–2.5 fold greater in triacylglycerol (TG) than phospholipids (PL), whereas Δ9 desaturation products were selectively incorporated into PL. Culturing HepG2 cells with t 9-18:1 and HT10 increased ( P <0.05) the Δ9 desaturation index ( c 9–16:1/16:0) compared to other fatty acid treatments. HT10 and t 9-18:1 also increased expression of lipogenic genes (FAS, SCD1, HMGCR and SREBP2) compared to control ( P <0.05), whereas c 9-18:1 and HT11 did not affect the expression of these genes. Our results suggest effects of HT11 and c 9-18:1 were similar to BSA control, whereas HT10 and t -9 18:1 (i.e. the predominant trans fatty acid isomer found in partially hydrogenated vegetable oils) were more cytotoxic and led to greater expression of lipogenic genes.
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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 | 0.000 | 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) | 0.002 | 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".