Characterization of Mammalian Stanniocalcin Receptors
Bibliographic record
Abstract
The polypeptide hormone stanniocalcin (STC) is widely expressed in mammalian tissues. STC acts locally in kidney and gut to modulate calcium and phosphate excretion, and its overexpression in mice results in high serum phosphate, dwarfism, and increased metabolic rate. STC has also been linked to cancer, pregnancy, lactation, angiogenesis, organogenesis, cerebral ischemia, and hypertonic stress. In this report we have characterized the STC receptor and the functional targeting of ligand and receptor to mitochondria. For receptor binding analysis, a stanniocalcin-alkaline phosphatase fusion protein was engineered. Subsequent binding assays using the fusion protein indicated that kidney and liver contained the highest number of binding sites with affinities of 0.8 and 0.25 nm, respectively. Intriguingly, purified mitochondria from both tissues yielded similar high affinity binding sites. Fractionation analysis revealed that the majority of binding sites were localized to the inner mitochondrial membrane. In further studies, we characterized the time course of STC-alkaline phosphatase fusion protein sequestration by intact mitochondria. In situ ligand binding also revealed discrete, displaceable binding to plasma membranes and mitochondria of nephron cells and liver hepatocytes. The existence of mitochondrial receptors prompted a similar search for the ligand. Immunogold electron microscopy revealed that STC was preferentially concentrated in the mitochondria of all nephron segments targeted by STC. Subcellular fractionation revealed that >90% of cellular STC immunoreactivity was mitochondrial, confined to the inner matrix, and similar in size to recombinant STC (50 kDa). In functional studies, recombinant STC had concentration-dependent stimulatory effects on electron transfer by sub-mitochondrial particles. Collectively the evidence implies a role for STC in cell metabolism.
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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 | 0.000 |
| 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) | 0.001 | 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".