PAC1 Receptor Activation by PACAP-38 Mediates Ca2+ Release from a cAMP-dependent Pool in Human Fetal Adrenal Gland Chromaffin Cells
Bibliographic record
Abstract
Previous studies have shown that human fetal adrenal gland from 17- to 20-week-old fetuses expressed pituitary adenylate cyclase-activating polypeptide (PACAP) receptors, which were localized on chromaffin cells. The aim of the present study was to identify PACAP receptor isoforms and to determine whether PACAP can affect intracellular calcium concentration ([Ca(2+)](i)) and catecholamine secretion. Using primary cultures and specific stimulation of chromaffin cells, we demonstrate that PACAP-38 induced an increase in [Ca(2+)](i) that was blocked by PACAP (6-38), was independent of external Ca(2+), and originated from thapsigargin-insensitive internal stores. The PACAP-triggered Ca(2+) increase was not affected by inhibition of PLC beta (preincubation with U-73122) or by pretreatment of cells with Xestospongin C, indicating that the inositol 1,4,5-triphosphate-sensitive stores were not mobilized. However, forskolin (FSK), which raises cytosolic cAMP, induced an increase in Ca(2+) similar to that recorded with PACAP-38. Blockage of PKA by H-89 or (R(p))-cAMPS suppressed both PACAP-38 and FSK calcium responses. The effect of PACAP-38 was also abolished by emptying the caffeine/ryanodine-sensitive Ca(2+) stores. Furthermore, treatment of cells with orthovanadate (100 microm) impaired Ca(2+) reloading of PACAP-sensitive stores indicating that PACAP-38 can mobilize Ca(2+) from secretory vesicles. Moreover, PACAP induced catecholamine secretion by chromaffin cells. It is concluded that PACAP-38, through the PAC(1) receptor, acts as a neurotransmitter in human fetal chromaffin cells inducing catecholamine secretion, through nonclassical, recently described, ryanodine/caffeine-sensitive pools, involving a cAMP- and PKA-dependent phosphorylation mechanism.
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) | 0.002 | 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".