Dietary Proteins as Determinants of Metabolic and Physiologic Functions of the Gastrointestinal Tract
Bibliographic record
Abstract
Dietary proteins elicit a wide range of nutritional and biological functions. Beyond their nutritional role as the source of amino acids for protein synthesis, they are instrumental in the regulation of food intake, glucose and lipid metabolism, blood pressure, bone metabolism and immune function. The interaction of dietary proteins and their products of digestion with the regulatory functions of the gastrointestinal (GI) tract plays a dominant role in determining the physiological properties of proteins. The site of interaction is widespread, from the oral cavity to the colon. The characteristics of proteins that influence their interaction with the GI tract in a source-dependent manner include their physico-chemical properties, their amino acid composition and sequence, their bioactive peptides, their digestion kinetics and also the non-protein bioactive components conjugated with them. Within the GI tract, these products affect several regulatory functions by interacting with receptors releasing hormones, affecting stomach emptying and GI transport and absorption, transmitting neural signals to the brain, and modifying the microflora. This review discusses the interaction of dietary proteins during digestion and absorption with the physiological and metabolic functions of the GI tract, and illustrates the importance of this interaction in the regulation of amino acid, glucose, lipid metabolism, and food intake.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| 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".