Upper gastrointestinal responses to intraduodenal nutrient in type 1 diabetes mellitus
Bibliographic record
Abstract
BACKGROUND: Abnormal nutrient-related small-intestinal feedback may contribute to disordered gastric motility and upper gastrointestinal symptoms in patients with diabetes. AIM: To evaluate the motor, sensory and incretin responses to intraduodenal nutrients in patients with type 1 diabetes and in controls. METHODS: Eight type 1 diabetes patients (two with autonomic neuropathy) and nine controls were studied during euglycaemia. A manometric catheter was positioned across the pylorus, and nutrient was infused intraduodenally (90 kcal over 30 min). Blood glucose and plasma glucagon-like peptide 1 and gastric inhibitory polypeptide were measured, and sensations were assessed with visual analogue questionnaires. RESULTS: During nutrient infusion, neither the number of antral waves nor the stimulation of phasic or basal pyloric pressures differed between patients and controls. Upper gut sensations and areas under the plasma incretin peptide curves did not differ between the groups. CONCLUSIONS: During euglycaemia, the upper gastrointestinal motor, sensory and incretin peptide responses to small-intestinal nutrient are comparable in patients with relatively uncomplicated type 1 diabetes and in healthy subjects.
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 | 0.001 |
| 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) | 0.001 | 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".