Use of a biomimetic hydrogel depot technology for sustained delivery of GLP-1 receptor agonists reduces burden of diabetes management
Bibliographic record
Abstract
Glucagon-like peptide-1 (GLP-1) is an incretin hormone and neurotransmitter secreted from intestinal L cells in response to nutrients to stimulate insulin and block glucagon secretion in a glucose-dependent manner. Long-acting GLP-1 receptor agonists (GLP-1 RAs) have become central to treating type 2 diabetes (T2D); however, these therapies are burdensome, as they must be taken daily or weekly. Technological innovations that enable less frequent administrations would reduce patient burden and increase patient compliance. Herein, we leverage an injectable hydrogel depot technology to develop a GLP-1 RA drug product capable of months-long GLP-1 RA delivery. Using a rat model of T2D, we confirm that one injection of hydrogel-based therapy sustains exposure of GLP-1 RA over 42 days, corresponding to a once-every-4-months therapy in humans. Hydrogel therapy maintains management of blood glucose and weight comparable to daily injections of a leading GLP-1 RA drug. This long-acting GLP-1 RA treatment is a promising therapy for more effective T2D management.
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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) | 0.000 | 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".