Destruction of Vitamin B1 by Benzaldehyde. Reactivity of Intermediates in the Fragmentation of <i>N</i>1‘-Benzyl-2-(1-hydroxybenzyl)thiamin
Bibliographic record
Abstract
Thiamin (vitamin B1) combines with benzaldehyde in alkaline solutions to form 2-(1-hydroxybenzyl)thiamin (HBzT), a reactive intermediate in the thiamin-catalyzed benzoin condensation. In neutral solutions, HBzT fragments into pyrimidine and thiazole constituents by cleavage of the bridging methylene−thiazole bond. The fragmentation is promoted by protonation of the pyrimidine moiety of HBzT. The N1‘-benzyl derivative of HBzT ( 4 in Scheme 4, BHT) also undergoes fragmentation in neutral and alkaline solutions, consistent with fragmentation being driven by positive charge on the pyrimidine derived from thiamin. Anionic Brønsted bases catalyze the reaction ( β = 0.5, for a series of substituted acetates). The dependence of the observed first-order rate coefficient for fragmentation of BHT on buffer concentration is nonlinear, becoming buffer-independent at concentrations above 0.05 M. This is consistent with a change in rate-determining step with buffer concentration from proton removal to subsequent fragmentation of the conjugate base of BHT. The solvent isotope effect is inverse, also consistent with reversible formation of the conjugate base. Analysis of the kinetic data reveals that the fragmentation step is very fast ( k f = 1.2 × 10 5 s - 1 at 40 °C). Such a low barrier is consistent with electron-shift mechanisms for the fragmentation step.
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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".