Bone Matrix Mineralization in Patients With Gain-of-Function Calcium-Sensing Receptor Mutations Is Distinctly Different From that in Postsurgical Hypoparathyroidism
Bibliographic record
Abstract
The role of the calcium-sensing receptor (CaSR) as a regulator of parathyroid hormone secretion is well established, but its function in bone is less well defined. In an effort to elucidate the CaSR's skeletal role, bone tissue and material characteristics from patients with autosomal dominant hypocalcemia (ADH), a genetic form of primary hypoparathyroidism caused by CASR gain-of-function mutations, were compared to patients with postsurgical hypoparathyroidism (PSH). Bone structure and formation/resorption indices and mineralization density distribution (BMDD), were examined in transiliac biopsy samples from PSH (n = 13) and ADH (n = 6) patients by histomorphometry and quantitative backscatter electron imaging, respectively. Bone mineral density (BMD by DXA) and biochemical characteristics were measured at the time of the biopsy. Because both study groups comprised children and adults, all measured biopsy parameters and BMD outcomes were converted to Z-scores for comparison. Histomorphometric indices were normal and not different between ADH and PSH, with the exception of mineral apposition rate Z-score, which was higher in the ADH group. Similarly, average BMD Z-scores were normal and not different between ADH and PSH. Significant differences were observed for the BMDD: average Z-scores of mean and typical degree of mineralization (CaMean, CaPeak, respectively) were lower (p = 0.02 and p = 0.03, respectively), whereas the heterogeneity of mineralization (CaWidth) and percentage of lower mineralized areas (CaLow) were increased in ADH versus PSH (p = 0.01 and p = 0.002, respectively). The BMDD outcomes point toward a direct, PTH-independent role of the CaSR in the regulation of bone mineralization. © 2018 American Society for Bone and Mineral Research.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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 | 0.000 |
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".