The Secretogranin II-Derived Peptide Secretoneurin Stimulates Luteinizing Hormone Secretion from Gonadotrophs
Bibliographic record
Abstract
Secretoneurin (SN) is a 33- to 34-amino acid neuropeptide derived from secretogranin-II, a member of the chromogranin family. We previously synthesized a putative goldfish (gf) SN and demonstrated its ability to stimulate LH release in vivo. However, it was not known whether goldfish actually produced the free SN peptide or whether SN directly stimulates LH release from isolated pituitary cells. Using a combination of reverse-phase HPLC and mass spectrometry analysis, we isolated for the first time a 34-amino acid free gfSN peptide from the whole brain. Moreover, Western blot analysis indicated the existence of this peptide in goldfish pituitary. Immunocytochemical localization studies revealed the presence of SN immunoreactivity in prolactin cells of rostral pars distalis of the anterior pituitary. Additionally, we found that magnocellular cells of the goldfish preoptic region are highly immunoreactive for SN. These neurons send heavily labeled projections that pass through the pituitary stalk and innervate the neurointermediate and anterior lobes. In static 12-h incubation of dispersed pituitary cells, application of SN antiserum reduced LH levels, whereas 1 and 10 nM gfSN, respectively, induced 2.5-fold (P < 0.001) and 1.9-fold (P < 0.01) increments of LH release into the medium, increases similar to those elicited by 100 nM concentrations of GnRH. Like GnRH, gfSN elevated intracellular Ca(2+) in identified gonadotrophs. Whereas we do not yet know the relative contribution of neural SN or pituitary SN to LH release, we propose that SN could act as a neuroendocrine and/or paracrine factor to regulate LH release from the anterior pituitary.
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 | 0.000 | 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".