Exendin-4 Normalized Postcibal Glycemic Excursions in Type 1 Diabetes
Bibliographic record
Abstract
Exendin-4 is a reptilian peptide that activates the mammalian receptor for truncated glucagon-like peptide 1 (tGLP-1) with relatively prolonged actions. Exendin-4 and tGLP-1 can reduce blood glucose levels by stimulating insulin secretion, inhibiting glucagon secretion, and delaying gastric emptying. We tested a range of doses of exendin-4 on postcibal glycemic excursions in nine volunteers with type 1 diabetes, all with negligible endogenous insulin secretion, in paired comparisons with vehicle in at least six volunteers with each of six doses. We established a side effect-free dose and an appropriate antecibal time for sc administration of exendin-4. Subsequently, exendin-4 was administered 15 min before breakfast, with usual insulin, to eight of the volunteers. Acetaminophen was ingested with the meal as an indicator of gastric emptying. The mean plasma glucose excursion was reduced by 90%, falling into the normal range, after breakfast, whereas plasma pancreatic polypeptide, glucagon, and acetaminophen levels were reduced, and insulin levels were not affected. Thus, normalization of postcibal glycemia was associated with delayed gastric emptying and suppression of glucagon secretion, without increased secretion or blood levels of insulin. We suggest that tGLP-1 agonists have therapeutic potential as congeners with insulin in C-peptide-negative type 1 diabetes.
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) | 0.001 | 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 | 0.001 |
| 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".