The Origin and Function of the Pituitary Adenylate Cyclase-Activating Polypeptide (PACAP)/Glucagon Superfamily*
Bibliographic record
Abstract
The pituitary adenylate cyclase-activating polypeptide (PACAP)/ glucagon superfamily includes nine hormones in humans that are related by structure, distribution (especially the brain and gut), function (often by activation of cAMP), and receptors (a subset of seven-transmembrane receptors). The nine hormones include glucagon, glucagon-like peptide-1 (GLP-1), GLP-2, glucose-dependent insulinotropic polypeptide (GIP), GH-releasing hormone (GRF), peptide histidine-methionine (PHM), PACAP, secretin, and vasoactive intestinal polypeptide (VIP). The origin of the ancestral superfamily members is at least as old as the invertebrates; the most ancient and tightly conserved members are PACAP and glucagon. Evidence to date suggests the superfamily began with a gene or exon duplication and then continued to diverge with some gene duplications in vertebrates. The function of PACAP is considered in detail because it is newly (1989) discovered; it is tightly conserved (96% over 700 million years); and it is probably the ancestral molecule. The diverse functions of PACAP include regulation of proliferation, differentiation, and apoptosis in some cell populations. In addition, PACAP regulates metabolism and the cardiovascular, endocrine, and immune systems, although the physiological event(s) that coordinates PACAP responses remains to be identified.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".