Tandem mass spectrometry of the B‐type procyanidins in wine and B‐type dehydrodicatechins in an autoxidation mixture of (+)‐catechin and (−)‐epicatechin
Bibliographic record
Abstract
We describe the characterization of the B-type procyanidins in wine and the B-type dehydrodicatechins (dimeric flavan-3-ols) obtained for the autoxidation of (+)-catechin and (-)-epicatechin by tandem mass spectrometry (MS/MS) coupled to reversed-phase high-performance liquid chromatography (HPLC). The MS/MS analysis demonstrates that the interesting major fragments derive from the dissociations of the C-ring on the catechin or epicatechin unit, such as retro-Diels-Alder reactions. The two kinds of dimers give completely different fragmentations because of the striking effect of the C-C interflavan linkage (IFL). For the natural dimers in wine, a catechin or epicatechin unit linking to the C-4 position stabilizes the product ions by forming a large pi-pi hyperconjugated system, whereas a similar pi-pi system is formed within dehydrodicatechin B through the C-C IFL. Thus dissociation in MS/MS experiments was inhibited. Apparently, the fragmentations of the dimers differ from that of the monomer, which is very important in the study of the gas-phase ion behaviour of the polymeric flavan-3-ols. In addition, two specific fragment ions at m/z 451 for native dimers and at m/z 393 for autoxidation species in HPLC/MS/MS were found to be very useful for analysing mixtures of B-type procyanidins and B-type dehydrodicatechins in food and beverages.
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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) | 0.001 | 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".