Mucosal C‐terminal maltase‐glucoamylase hydrolyzes large size starch digestion products that may contribute to rapid postprandial glucose generation
Bibliographic record
Abstract
SCOPE: The four mucosal α-glucosidases, which differ in their digestive roles, generate glucose from glycemic carbohydrates and accordingly can be viewed as a control point for rate of glucose delivery to the body. In this study, individual recombinant enzymes were used to understand how α-glucan oligomers are digested by each enzyme, and how intermediate α-amylolyzed starches are hydrolyzed, to elucidate a strategy for moderating the glycemic spike of rapidly digestible starchy foods. METHODS AND RESULTS: The C-terminal maltase-glucoamylase (ctMGAM, commonly termed "glucoamylase") was able to rapidly hydrolyze longer maltooligosaccharides, such as maltotetraose and maltopentaose, to glucose. Moreover, it was found to convert larger size maltodextrins, as would be produced early in α-amylase digestion of starch, efficiently to glucose. It is postulated that ctMGAM has the additional capacity to hydrolyze large α-amylase products that are produced immediately on starch digestion in the duodenum and contribute to the rapid generation of glucose from starch-based meals. CONCLUSION: The findings suggest that partial inhibition of ctMGAM, such as by natural inhibitors found in foods, might be used to moderate the early stage of high glycemic response, as well as to extend digestion distally; thereby having relevance in regulating glucose delivery to the body.
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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".