Determination of stereochemical configuration of the glycerol moieties in glycoglycerolipids by chiral phase high‐performance liquid chromatography
Bibliographic record
Abstract
This study reports a simple and sensitive method for determining the absolute configuration of the glycerol moieties in glycoglycerolipids. The method is based on chiral phase high-performance liquid chromatography (HPLC) separations of enantiomeric di- and monoacylglycerols released from glycosyldi- and monoacylglycerols, respectively, by periodate oxidation followed by hydrazinolysis. The released di- and monoacylglycerols were chromatographed as their 3,5-dinitrophenylurethane (3,5-DNPU) and bis(3,5-DNPU) derivatives, respectively. The derivatives were separated on two chiral phases of opposite configuration, (R)- and (S)-1-(1-naphthyl)ethylamine polymers for diacylglycerols and N-(R)- -(1-naphthyl)ethylaminocarbonyl-(S)-valine and N-(S)-1 -(1-naphthyl)ethylamino-carbonyl-(R)-valine for monoacylglycerols. Clear enantiomer separations, which permit the assignment of the glycerol configuration, were achieved for sn-1,2(2,3)-diacyl- and sn-1(3)-monoacylglycerols generated from linseed oil triacylglycerols by partial Grignard degradation on all the chiral stationary phases employed. Using the method, we have determined the glycerol configuration in the glycosyldiacylglycerols (monogalactosyl-, digalactosyl-, and sulfquinovosyldiacylglycerols) and glycosylmonoacylglycerols (monogalactosyl-, digalactosyl-, and sulfoquinovosylmonoacylglycerols) isolated from spinach leaves and the coralline red alga Corallina pilulifera. The results clearly showed that the glycerol moieties in all the glycoglycerolipids examined have S-configuration (sn-1,2-diacyl- and sn-1-monoacylglycerols). The new method demonstrates that chiral phase HPLC provides unambiguous information on the configuration of the glycerol backbone in natural glycosyldi- and monoacylglycerols, and that the two-step liberation of the free acylglycerols does not compromise glycerol chirality.
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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 | 0.000 | 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) | 0.000 | 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".