The anti-inflammatory feature of glucagon-like peptide-1 and its based diabetes drugs—Therapeutic potential exploration in lung injury
Bibliographic record
Abstract
Since 2005, GLP-1 receptor (GLP-1R) agonists (GLP-1RAs) have been developed as therapeutic agents for type 2 diabetes (T2D). GLP-1R is not only expressed in pancreatic islets but also other organs, especially the lung. However, controversy on extra-pancreatic GLP-1R expression still needs to be further resolved, utilizing different tools including the use of more reliable GLP-1R antibodies in immune-staining and co-immune-staining. Extra-pancreatic expression of GLP-1R has triggered extensive investigations on extra-pancreatic functions of GLP-1RAs, aiming to repurpose them into therapeutic agents for other disorders. Extensive studies have demonstrated promising anti-inflammatory features of GLP-1RAs. Whether those features are directly mediated by GLP-1R expressed in immune cells also remains controversial. Following a brief review on GLP-1 as an incretin hormone and the development of GLP-1RAs as therapeutic agents for T2D, we have summarized our current understanding of the anti-inflammatory features of GLP-1RAs and commented on the controversy on extra-pancreatic GLP-1R expression. The main part of this review is a literature discussion on GLP-1RA utilization in animal models with chronic airway diseases and acute lung injuries, including studies on the combined use of mesenchymal stem cell (MSC) based therapy. This is followed by a brief summary.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".