A potential control point of glucose delivery from starchy foods: intestinal mucosal α‐glucosidase digestion
Bibliographic record
Abstract
To control the glucose delivery from starchy foods, much attention has been given to α‐amylase (AMY), as opposed to the contribution from mucosal α‐glucosidases. The aim of this research was to investigate the digestion capability of mucosal α‐glucosidases on various starch structures to explore their possible expanded roles in digestion. Substrates were incubated with recombinant N‐ (Nt) and C‐terminals (Ct) of maltase‐glucoamylase (MGAM) and sucrase‐isomaltase (SI) for different digestion periods, and the glucogenesis and residue structures were examined. At raw starch granule level, mucosal α‐glucosidases showed the capability to produce glucose from uncooked starch granules at a low digestion completion. At the cooked starch level, CtMGAM showed high digestion completion near 80% without AMY participation; other three subunits reached 20–30% digestion. At the α‐limit dextrin (LDx) level, the four subunits showed different roles where NtMGAM only digested short linear oligomers but the other three subunits individually digested large branched molecules with different completion percentage. Collectively, these findings suggest mucosal α‐glucosidases, particularly CtMGAM, may be potential control points for glucose delivery in the human body. This work was supported by internal funding from the Whistler Center and Children's Nutrition Research Center of the ARS/USDA.
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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) | 0.000 | 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".