Bibliographic record
Abstract
The way to a person's heart is through their stomach - not just their heart. All aspects of health are affected by sources of nutrition; not just health but social and political issues, too. The metabolism of starch into glucose is linked directly to the development of the human brain. There is considerable interest worldwide into the processing of starch and other foods by the intestinal microbiome. This talk will focus on the main mammalian intestinal enzymes that process starch, their structures, functions and potential roles in human health and disease. The alpha-glucosidases maltase-glucoamylase (MGAM) and sucrase-isomaltast (SI) are resident in the small-intestinal lumen and are responsible for generating glucose from a wide variety of starch structures. Their malfunction is responsible for many nutritional intolerances and diseases including diabetes, gastrointestinal cancers and obesity. A pediatric nutritional disorder directly associated with mutations in SI, Congenital Sucrase-Isomaltase Deficiency (CSID) has significant occurrence, especially in northern and indigenous populations. The structural analyses presented in this talk will shed light on the molecular basis for this disease, as well as the development of inhibitor analyses that are designed to investigate the roles of human intestinal glucosidases in health and disease.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".