Reuteransucrase-catalytic kinetic modeling and functional characteristics for novel prebiotic gluco-oligomers
Bibliographic record
Abstract
This work describes the reuteransucrase-catalyzed reaction and structural characterization as well as in vitro fermentation for the acceptor products of gluco-oligomers from sucrose and maltose. At a low concentration of sucrose, the production of gluco-oligomers was favored, resulting in a relatively large number of acceptor products (DP3-5). A mathematical model was also proposed to simulate gluco-oligomer production depending on the reaction conditions. The fine structures of major linear gluco-oligomer fractions for a sucrose : maltose ratio of 1 : 1 were assigned as follows: α-d-Glcp-(1→6)-α-d-Glcp-(1→4)-d-Glcp, α-d-Glcp-(1→4)-α-d-Glcp-(1→4)-α-d-Glcp-(1→4)-d-Glcp, α-d-Glcp-(1→4)-α-d-Glcp-(1→6)-α-d-Glcp-(1→4)-d-Glcp, and α-d-Glcp-(1→6)-α-d-Glcp-(1→4)-α-d-Glcp-(1→6)-α-d-Glcp-(1→4)-d-Glcp, respectively. Compared with dextran and GOS57, the results of fermentation selectivity indicated that gluco-oligomers promoted the proliferation of gut bacteria and total SCFA production with a higher concentration of propionate. These data suggested that the gluco-oligomers synthesized via the reuteransucrase acceptor reaction had a prebiotic effect on gastrointestinal health.
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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 | 0.001 |
| 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 | 0.001 | 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".