Expression of Glucagon-Like Peptide 1 Receptor and its Effects on Biologic Behavior in Pancreatic Neuroendocrine Tumors
Bibliographic record
Abstract
OBJECTIVES: Glucagon-like peptide 1 (GLP-1) interacts with its specific high-affinity receptor, glucagon-like peptide 1 receptor (GLP-1R), and induces cellular growth and inhibition of apoptosis in pancreatic β cells. The aim of this study was to investigate the significance of GLP-1R expression in pancreatic neuroendocrine tumors (PNETs). METHODS: Glucagon-like peptide 1 receptor expression was semiquantitatively evaluated by immunohistochemical staining in 50 resected PNETs, and the correlation between the GLP-1R expression and clinicopathologic features was investigated. RESULTS: There were 23 PNETs with positive expression and 27 PNETs with negative expression of GLP-1R. Positive expression of GLP-1R was more frequently observed in insulinoma than in gastrinoma and nonfunctioning tumor (P < 0.05). Although expression status of GLP-1R did not affect the prognosis of the patients with PNETs (P = 0.82), most of the metastatic sites such as lymph node and liver showed positive staining for GLP-1R (8 of 11 PNETs, 73%). CONCLUSIONS: Glucagon-like peptide 1 receptor would be a diagnostic marker of insulinoma and might become a molecular target for treatment of metastatic PNETs and hormonal regulation of insulin.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".