HPLC and LC-MS Studies of the Transesterification Reaction of Methylparaben with Twelve 3- to 6-Carbon Sugar Alcohols and Propylene Glycol and the Isomerization of the Reaction Products by Acyl Migration
Bibliographic record
Abstract
Sugar alcohols and parabens are commonly used ingredients in oral suspension formulations. However, their possible incompatibility because of transesterification reaction is a concern during formulation development. In order to gain more knowledge about the reaction, a high-performance liquid chromatographic (HPLC) method is developed to separate the transesterification reaction products of methylparaben preservative with twelve 3- to 6-carbon sugar alcohols and propylene glycol. It is found that the number of peaks separated or partially separated correlate well with the number of distinct hydroxyl groups present in the sugar alcohol molecules. This means that all the hydroxyl groups in a sugar alcohol molecule can react with methylparaben to form transesterification reaction products. These products are positional isomers that have identical UV spectra with a maximum at 255 nm and the same m/z ratio for molecular ions by liquid chromatography-mass spectrometry. When isolated individually, they can isomerize (interconvert) under suitable conditions to form other positional isomers by intramolecular acyl migration. The acyl migration pathway for each of the isolated positional isomers from the transesterification reaction of methylparaben with sorbitol, ribitol, and xylitol is followed by HPLC. Based on the information, a tentative assignment of the six isomer peaks generated from the transesterification reaction between methylparaben and sorbitol is proposed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".