Human stanniocalcin-2 exhibits potent growth-suppressive properties in transgenic mice independently of growth hormone and IGFs
Bibliographic record
Abstract
Stanniocalcin (STC)-2 was discovered by its primary amino acid sequence identity to the hormone STC-1. The function of STC-2 has not been examined; thus we generated two lines of transgenic mice overexpressing human (h)STC-2 to gain insight into its potential functions through identification of overt phenotypes. Analysis of mouse Stc2 gene expression indicates that, unlike Stc1, it is not highly expressed during development but exhibits overlapping expression with Stc1 in adult mice, with heart and skeletal muscle exhibiting highest steady-state levels of Stc2 mRNA. Constitutive overexpression of hSTC-2 resulted in pre- and postnatal growth restriction as early as embryonic day 12.5, progressing such that mature hSTC-2-transgenic mice are approximately 45% smaller than wild-type littermates. hSTC-2 overexpression is sometimes lethal; we observed 26-34% neonatal morbidity without obvious dysmorphology. hSTC-2-induced growth retardation is associated with developmental delay, most notably cranial suture formation. Organ allometry studies show that hSTC-2-induced dwarfism is associated with testicular organomegaly and a significant reduction in skeletal muscle mass likely contributing to the dwarf phenotype. hSTC-2-transgenic mice are also hyperphagic, but this does not result in obesity. Serum Ca2+ and PO4 were unchanged in hSTC-2-transgenic mice, although STC-1 can regulate intra- and extracellular Ca2+ in mammals. Interestingly, severe growth retardation induced by hSTC-2 is not associated with a decrease in GH or IGF expression. Consequently, similar to STC-1, STC-2 can act as a potent growth inhibitor and reduce intramembranous and endochondral bone development and skeletal muscle growth, implying that these tissues are specific physiological targets of stanniocalcins.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".