Countercurrent approach to the enrichment of Δ9<i>c</i>,11<i>t</i>‐and Δ10<i>t</i>,12<i>c</i>‐18:2 isomers by urea complexation
Bibliographic record
Abstract
Abstract CLA refers to a group of geometrical and positional isomers of linoleic acid. CLA has been shown to have potentially beneficial effects on cancer, atherosclerosis, and body metabolism in animals. Mixtures containing equal amounts of these isomers are commonly used in many research studies because of their greater availability and lower cost relative to pure isomers. This has hindered progress in elucidating the biological properties of specific isomers and their relevance in animal and human biology. A method was developed that offers a compromise between cost and utility to make available enriched mixtures of either the Δ9c,11t‐ or Δ10t,12c‐18:2 isomers for use in a wide range of experimental applications. A countercurrent approach was developed to separate the Δ9c,11t‐ and Δ10t,12c‐18:2 isomers from an equal mixture of these two isomers by urea complexation. After three successive rounds of complexation using an equal amount of CLA and urea, a fraction enriched in Δ9c,11t‐18:2 containing 42.5 and 17.4% of Δ9c,11t‐and Δ10t,12c‐18:2, respectively, was recovered. After a single round of complexation using 2.5 g urea/g CLA, a fraction enriched in Δ10t,12c‐18:2 was recovered containing 29.7 and 69.1% of Δ9c,11t‐ and Δ10t,12c‐18:2, respectively.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".