Stanniocalcin Has Deep Evolutionary Roots in Eukaryotes
Bibliographic record
Abstract
Vertebrates have a large glycoprotein hormone, stanniocalcin, which originally was shown to inhibit calcium uptake from the environment in teleost fish gills. Later, humans, other mammals, and teleost fish were shown to have two forms of stanniocalcin (STC1 and STC2) that were widely distributed in many tissues. STC1 is associated with calcium and phosphate homeostasis and STC2 with phosphate, but their receptors and signaling pathways have not been elucidated. We undertook a phylogenetic investigation of stanniocalcin beyond the vertebrates using a combination of BLAST and HMMER homology searches in protein, genomic, and expressed sequence tag databases. We identified novel STC homologs in a diverse array of multicellular and unicellular organisms. Within the eukaryotes, almost all major taxonomic groups except plants and algae have STC homologs, although some groups like echinoderms and arthropods lack STC genes. The critical structural feature for recognition of stanniocalcins was the conserved pattern of ten cysteines, even though the amino acid sequence identity was low. Signal peptides in STC sequences suggest they are secreted from the cell of synthesis. The role of glycosylation signals and additional cysteines is not yet clear, although the 11th cysteine, if present, has been shown to form homodimers in some vertebrates. We predict that large secreted stanniocalcin homologs appeared in evolution as early as single-celled eukaryotes. Stanniocalcin's tertiary structure with five disulfide bonds and its primary structure with modest amino acid conservation currently lack an established receptor-signaling system, although we suggest possible alternatives.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".