Stanniocalcin-1 Co-Localizes with Insulin in the Pancreatic Islets
Bibliographic record
Abstract
The polypeptide hormone stanniocalcin-1 (STC-1) is widely expressed in mammals and signals both locally and systemically. In many tissues STC-1 ligand is sequestered by target cell organelles (mitochondria, nuclei, and cholesterol lipid droplets) to exert diverse biological effects. Most notably, STC-1 serves as an uncoupler of oxidative phosphorylation in liver, muscle, and kidney mitochondria. The present paper describes the identification of STC-1 receptors in mouse pancreatic β cells and the discovery that the ligand co-localizes with insulin in pancreatic β cells. In situ hybridization (ISH) analysis subsequently revealed that pancreatic β cells were the source of the ligand. Intriguingly however, all ISH signal was localized over putative islet cell nuclei as opposed to the cell cytoplasm. Real-time qPCR and agarose gel electrophoresis revealed that the STC-1 amplicon generated from islet cell total RNA was the same size as that from kidney. However, relative levels of STC-1 gene expression were >100-fold lower in islets than those in kidney tissue. Collectively, these findings are indicative of a local STC-1 signalling pathway in pancreatic β cells. The role of STC-1 in this context remains to be established, but it could very well entail the regulation of β cell mitochondria membrane potential which is an integral aspect of regulated insulin release. Interestingly, STC-1 immunoreactivity was not evident in embryonic pancreatic islets, suggesting that ligand synthesis may only commence postnatally.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".