Isotope Labeling Studies on the Formation of 5-(Hydroxymethyl)-2-furaldehyde (HMF) from Sucrose by Pyrolysis-GC/MS
Bibliographic record
Abstract
Although it is generally assumed that the reactivity of sucrose, a nonreducing sugar, in the Maillard reaction is due to its hydrolysis into free glucose and fructose, however, no direct evidence has been provided for this pathway, especially in dry and high temperature systems. Using specifically (13)C-labeled sucrose at C-1 of the fructose moiety, HMF formation was studied at different temperatures. Under dry pyrolytic conditions and at temperatures above 250 degrees C, 90% of HMF originated from fructose moiety and only 10% originated from glucose. Alternatively, when sucrose was refluxed in acidic methanol at 65 degrees C, 100% of HMF was generated from the glucose moiety. Moreover, the relative efficiency of the known HMF precursor 3-deoxyglucosone to generate HMF was compared to that of glucose, fructose and sucrose. Glucose exhibited a much lower conversion rate than 3-deoxyglucosone, however, both fructose and sucrose showed much higher conversion rates than 3-deoxyglucosone thus precluding it as a major precursor of HMF in fructose and sucrose solutions. Based on the data generated, a mechanism of HMF formation from sucrose is proposed. According to this proposal sucrose degrades into glucose and a very reactive fructofuranosyl cation. In dry systems this cation can be effectively converted directly into HMF.
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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) | 0.001 | 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 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".