Somatostatin Receptors in Brain and Pituitary
Bibliographic record
Abstract
Somatostatin (SRIF) actions in the brain and pituitary are mediated by specific receptors. Using radioiodinated ligands it has been possible to characterize the kinetics of specific binding sites in the brain and pituitary, and to determine their cellular localization by autoradiography. At the pituitary level, the inhibition of growth hormone, prolactin and thyrotropin secretions induced by SRIF is mediated through a single binding site which is coupled to the inhibition of adenylate cyclase. In the brain, SRIF receptors are localized on neurons and glial cells and are also coupled to adenylate cyclase inhibition. Two sites are differentiated in the brain with an analogue of somatostatin, SMS 201995. In humans, SRIF-binding sites have been related to a number of pathologies. At the pituitary level, it has been shown that the number of binding sites was negatively correlated to growth hormone levels in acromegaly. Furthermore, SRIF-binding sites were undetectable in a patient which did not respond to SMS 201995 therapy. In the brain, meningiomas and gliomas are rich in SRIF binding sites. This suggests a possible role for SRIF on glia. In neurodegenerative diseases, cortical SRIF concentrations are decreased in Alzheimer's and Parkinson's disease associated with dementia while SRIF-binding sites are only affected in Alzheimer's disease. In conclusion, the physiological role of SRIF in the brain and pituitary can be evaluated by studying the receptors of the peptide. Such studies allow to question the implication of SRIF in endocrine and neuropathologies.
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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 | 0.000 | 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) | 0.001 | 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 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".