Physiological studies in heterozygous calcium sensing receptor \n(CaSR) gene-ablated mice confirm that the CaSR regulates \ncalcitonin release in vivo
Bibliographic record
Abstract
Background: The calcium sensing receptor (CaSR) regulates serum calcium by suppressing secretion of parathyroid hormone; it also regulates renal tubular calcium excretion. Inactivating mutations of CaSR raise serum calcium and reduce urine calcium excretion. Thyroid C-cells (which make calcitonin) express CaSR and may, therefore, be regulated by it. Since calcium stimulates release of calcitonin, the higher blood calcium caused by inactivation of CaSR should increase serum calcitonin, unless CaSR mutations alter the responsiveness of calcitonin to calcium. To demonstrate regulatory effects of CaSR on calcitonin release, we studied calcitonin responsiveness to calcium in normal and CaSR heterozygous-ablated (Casr+/-) mice. Casr+/- mice have hypercalcemia and hypocalciuria, and live normal life spans. Each mouse received either 500 μl of normal saline or one of two doses of elemental calcium (500 μmol/kg or 5 mmol/kg) by intraperitoneal injection. Ionized calcium was measured at baseline and 10 minutes, and serum calcitonin was measured on the 10 minute sample. Results: At baseline, Casr+/- mice had a higher blood calcium, and in response to the two doses of elemental calcium, had greater increments and peak levels of ionized calcium than their wild type littermates. Despite significantly higher ionized calcium levels, the calcitonin levels of Casr+/- mice were consistently lower than wild type at any ionized calcium level, indicating that the dose-response curve of calcitonin to increases in ionized calcium had been significantly blunted or shifted to the right in Casr+/- mice. Conclusions: These results confirm that the CaSR is a physiological regulator of calcitonin; therefore, in response to increases in ionized calcium, the CaSR inhibits parathyroid hormone secretion and stimulates calcitonin secretion.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".