Luminal Substrate “Brake” on Mucosal Maltase‐glucoamylase Activity Regulates Total Rate of Starch Digestion to Glucose
Bibliographic record
Abstract
BACKGROUND: Starches are the major source of dietary glucose in weaned children and adults. However, small intestine alpha-glucogenesis by starch digestion is poorly understood due to substrate structural and chemical complexity, as well as the multiplicity of participating enzymes. Our objective was dissection of luminal and mucosal alpha-glucosidase activities participating in digestion of the soluble starch product maltodextrin (MDx). PATIENTS AND METHODS: Immunoprecipitated assays were performed on biopsy specimens and isolated enterocytes with MDx substrate. RESULTS: Mucosal sucrase-isomaltase (SI) and maltase-glucoamylase (MGAM) contributed 85% of total in vitro alpha-glucogenesis. Recombinant human pancreatic alpha-amylase alone contributed <15% of in vitro alpha-glucogenesis; however, alpha-amylase strongly amplified the mucosal alpha-glucogenic activities by preprocessing of starch to short glucose oligomer substrates. At low glucose oligomer concentrations, MGAM was 10 times more active than SI, but at higher concentrations it experienced substrate inhibition whereas SI was not affected. The in vitro results indicated that MGAM activity is inhibited by alpha-amylase digested starch product "brake" and contributes only 20% of mucosal alpha-glucogenic activity. SI contributes most of the alpha-glucogenic activity at higher oligomer substrate concentrations. CONCLUSIONS: MGAM primes and SI activity sustains and constrains prandial alpha-glucogenesis from starch oligomers at approximately 5% of the uninhibited rate. This coupled mucosal mechanism may contribute to highly efficient glucogenesis from low-starch diets and play a role in meeting the high requirement for glucose during children's brain maturation. The brake could play a constraining role on rates of glucose production from higher-starch diets consumed by an older population at risk for degenerative metabolic disorders.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".