Expression, pharmacology, and functional role of somatostatin receptor subtypes 1 and 2 in human macrophages
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Somatostatin (SRIF)-14 is recognized as an important mediator between the nervous and the immune system, although the functional role of its receptors (sst(1)-sst(5)) is poorly understood in humans. In our study, we demonstrate that human macrophages, differentiated from PBMC-derived monocytes, express sst(1) and sst(2) mRNAs. sst(1) and sst(2) are mostly localized at the cell surface and display active binding sites. In particular, sst(1)/sst(2) activation results in a weak internalization of sst(1), and the sst(2) internalization appears more efficient. At the functional level, the activation of SRIF receptors by the multiligand analogs SOM230 and KE108, but not by SRIF-14 or cortistatin-14, reduces macrophage viability. Their effects are mimicked by the selective activation of sst(1) and sst(2) using CH-275 and SMS 201-995/L-779,976, respectively. Further, sst(1)- and sst(2)-mediated effects are reversed by the sst(1) antagonist SRA-880 or the sst(2) antagonist CYN 154806, respectively. CH-275, SMS 201-995, and L-779,976, but not SRIF-14, decrease mRNA expression and secretion of the MCP-1. In addition, SRIF-14, CH-275, SMS 201-995, and L-779,976 decrease IL-8 secretion, and they do not affect IL-8 mRNA expression. In contrast, SRIF-14 and sst(1)/sst(2) agonists do not affect the secretion of matrix metalloproteinase-9. Collectively, our results suggest that the SRIF system, through sst(1) and sst(2), exerts mainly an immunosuppressive effect in human macrophages and may, therefore, represent a therapeutic window that can be exploited for the development of new strategies in pharmacological therapy of inflammation.
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.
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 | 0.000 | 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) | 0.000 | 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 it