Chlorthalidone improves vertebral bone quality in genetic hypercalciuric stone-forming rats
Bibliographic record
Abstract
We have bred a strain of rats to maximize urine (u) calcium (Ca) excretion and model hypercalciuric nephrolithiasis. These genetic hypercalciuric stone-forming (GHS) rats excrete more uCa than control Sprague-Dawley rats, uniformly form kidney stones, and similar to patients, demonstrate lower bone mineral density. Clinically, thiazide diuretics reduce uCa and prevent stone formation; however, whether they benefit bone is not clear. We used GHS rats to test the hypothesis that the thiazide diuretic chlorthalidone (CTD) would have a favorable effect on bone density and quality. Twenty GHS rats received a fixed amount of a 1.2% Ca diet, and half also were fed CTD (4 to 5 mg/kg/d). Rats fed CTD had a marked reduction in uCa. The axial and appendicular skeletons were studied. An increase in trabecular mineralization was observed with CTD compared with controls. CTD also improved the architecture of trabecular bone. Using micro-computed tomography (µCT), trabecular bone volume (BV/TV), trabecular thickness, and trabecular number were increased with CTD. A significant increase in trabecular thickness with CTD was confirmed by static histomorphometry. CTD also improved the connectivity of trabecular bone. Significant improvements in vertebral strength and stiffness were measured by vertebral compression. Conversely, a slight loss of bending strength was detected in the femoral diaphysis with CTD. Thus results obtained in hypercalciuric rats suggest that CTD can favorably influence vertebral fracture risk. CTD did not alter formation parameters, suggesting that the improved vertebral bone strength was due to decreased bone resorption and retention of bone structure.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".