Incretin hormones and the expanding families of glucagon‐like sequences and their receptors
Bibliographic record
Abstract
Peptide hormones encoded by the proglucagon (Gcg) and glucose-dependent insulinotropic polypeptide (Gip) genes are evolutionarily related glucagon-like sequences and act through a subfamily of G-protein-coupled receptors. A better understanding of the evolutionary history of these hormones and receptors should yield insight into their biological functions. The availability of a large number of near-complete vertebrate genome sequences is a powerful resource to address questions concerning the evolution of sequences; here, we utilize these resources to examine the evolution of glucagon-like sequences and their receptors. These studies led to the discovery of novel genes for a glucagon receptor-like receptor (Grlr) and a glucagon-like sequence (exendin) in vertebrates. Both exendin and GRLR have ancient origins, early in vertebrate evolution, but have been lost on the ancestral lineage leading to extant mammals. We also show that exendin and GRLR are both expressed in the brain of the chicken and Xenopus tropicals, results that suggest that the products of these genes function in this tissue. The lack of exendin or Grlr genes in mammals suggests that other genes may have acquired the functions of exendin and Grlr during mammalian evolution.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".