Usage Information
Citation Information: JCI Insight. 2021;6(4):e143228. https://doi.org/10.1172/jci.insight.143228.
Abstract
Somatostatin (SS) inhibits glucagon-like peptide-1 (GLP-1) secretion in a paracrine manner. We hypothesized that blocking somatostatin subtype receptor 2 (SSTR2) and 5 (SSTR5) would improve glycemia by enhancing GLP-1 secretion. In the perfused mouse small intestine, the selective SSTR5 antagonist (SSTR5a) stimulated glucose-induced GLP-1 secretion to a larger degree than the SSTR2 antagonist (SSTR2a). In parallel, mice lacking the SSTR5R showed increased glucose-induced GLP-1 secretion. Both antagonists improved glycemia in vivo in a GLP-1 receptor–dependent (GLP-1R–dependent) manner, as the glycemic improvements were absent in mice with impaired GLP-1R signaling and in mice treated with a GLP-1R–specific antagonist. SSTR5a had no direct effect on insulin secretion in the perfused pancreas, whereas SSTR2a increased insulin secretion in a GLP-1R–independent manner. Adding a dipeptidyl peptidase 4 inhibitor (DPP-4i) in vivo resulted in additive effects on glycemia. However, when glucose was administered intraperitoneally, the antagonist was incapable of lowering blood glucose. Oral administration of SSTR5a, but not SSTR2a, lowered blood glucose in diet-induced obese mice. In summary, we demonstrate that selective SSTR antagonists can improve glucose control primarily through the intestinal GLP-1 system in mice.
Authors
Sara L. Jepsen, Nicolai J. Wewer Albrechtsen, Johanne A. Windeløv, Katrine D. Galsgaard, Jenna E. Hunt, Thomas B. Farb, Hannelouise Kissow, Jens Pedersen, Carolyn F. Deacon, Rainer E. Martin, Jens J. Holst
Usage data is cumulative from January 2021 through February 2021.
| Usage | JCI | PMC |
|---|---|---|
| Text version | 440 | 0 |
| 182 | 0 | |
| Figure | 2 | 0 |
| Supplemental data | 18 | 0 |
| Citation downloads | 7 | 0 |
| Totals | 649 | 0 |
| Total Views | 649 | |
Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.
Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.
