Effect of Mouse Maltase‐glucoamylase (Mgam) Knockout on Starch Digestion to Glucose
Bibliographic record
Abstract
Digestion of starch requires activities provided by six different α‐glucosidase enzymes. Two activities are luminal α‐amylases (AMY). Four activities are mucosal activities described as maltases. Two of the activities are associated with sucrase‐isomaltase (Si) activities. Two activities are named Mgam. We knocked out (KO) the Mgam gene to determine its role in digestion of starch to glucose in mice. The activities of Mgam KO null (N) and wild‐type (WT) jejunum were assayed, with added recombinant AMY, using starch substrates and acarbose. Glucose release was measured by glucose‐oxidase assay. Antibody for C‐terminus was used for Western blots (WB).Oligomers of maltodextrin (MDx) were analyzed by MALDI‐TOF before and after digestion to limit dextrin (LDx) with AMY. Mgam was present in WT but absent in N by WB. Jejunal activities for MDx, LDx, and maltose (M) were reduced in N. The Km of N for M and MDx was 5 X slower. α‐Glucogenesis from MDx substrate was 20 X faster in WT. α‐Amylase amplified by 3 X mucosal activity for MDx, but not LDx. LDx had more short oligomers. Acarbose Ki for M and MDx in WT was 7X stronger than N. Mgam KO reduced mucosal α‐glucogenesis by 20 X. α‐Amylase had little activity but amplified N and WT mucosal activity 3X. WT Mgam determined maximal rates of normal amylopectin digestion. WT mucosa was more sensitive to acarbose inhibition.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".