PTH(1-84) Administration in Hypoparathyroidism Transiently Reduces Bone Matrix Mineralization
Bibliographic record
Abstract
Patients with hypoparathyroidism have low circulating parathyroid (PTH) levels and higher cancellous bone volume and trabecular thickness. Treatment with PTH(1-84) was shown to increase abnormally low bone remodeling dynamics. In this work, we studied the effect of 1-year or 2-year PTH(1-84) treatment on cancellous and cortical bone mineralization density distribution (Cn.BMDD and Ct.BMDD) based on quantitative backscattered electron imaging (qBEI) in paired transiliac bone biopsy samples. The study cohort comprised 30 adult hypoparathyroid patients (14 treated for 1 year; 16 treated for 2 years). At baseline, Cn.BMDD was shifted to higher mineralization densities in both treatment groups (average degree of mineralization Cn.CaMean +3.9% and +2.7%, p < 0.001) compared to reference BMDD. After 1-year PTH(1-84), Cn.CaMean was significantly lower than that at baseline (-6.3%, p < 0.001), whereas in the 2-year PTH(1-84) group Cn.CaMean did not differ from baseline. Significant changes of Ct.BMDD were observed in the 1-year treatment group only. The change in histomorphometric bone formation (mineralizing surface) was predictive for Cn.BMDD outcomes in the 1-year PTH(1-84) group, but not in the 2-year PTH(1-84) group. Our findings suggest higher baseline bone matrix mineralization consistent with the decreased bone turnover in hypoparathyroidism. PTH(1-84) treatment caused differential effects dependent on treatment duration that were consistent with the histomorphometric bone formation outcomes. The greater increase in bone formation during the first year of treatment was associated with a decrease in bone matrix mineralization, suggesting that PTH(1-84) exposure to the hypoparathyroid skeleton has the greatest effects on BMDD early in treatment.
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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) | 0.000 | 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".