Treatment with eldecalcitol positively affects mineralization, microdamage, and collagen crosslinks in primate bone
Bibliographic record
Abstract
Eldecalcitol (ELD), an active form of vitamin D analog approved for the treatment of osteoporosis in Japan, increases lumbar spine bone mineral density (BMD), suppresses bone turnover markers, and reduces fracture risk in patients with osteoporosis. We have previously reported that treatment with ELD for 6 months improved the mechanical properties of the lumbar spine in ovariectomized (OVX) cynomolgus monkeys. ELD treatment increased lumbar BMD, suppressed bone turnover markers, and reduced histomorphometric parameters of both bone formation and resorption in vertebral trabecular bone. In this study, we elucidated the effects of ELD on bone quality (namely, mineralization, microarchitecture, microdamage, and bone collagen crosslinks) in OVX cynomolgus monkeys in comparison with OVX-vehicle control monkeys. Density fractionation of bone powder prepared from lumbar vertebrae revealed that ELD treatment shifted the distribution profile of bone mineralization to a higher density, and backscattered electron microscopic imaging showed improved trabecular bone connectivity in the ELD-treated groups. Higher doses of ELD more significantly reduced the amount of microdamage compared to OVX-vehicle controls. The fractionated bone powder samples were divided according to their density, and analyzed for collagen crosslinks. Enzymatic crosslinks were higher in both the high-density (≥2.0 mg/mL) and low-density (<2.0 mg/mL) fractions from the ELD-treated groups than in the corresponding fractions in the OVX-vehicle control groups. On the other hand, non-enzymatic crosslinks were lower in both the high- and low-density fractions. These observations indicated that ELD treatment stimulated the enzymatic reaction of collagen crosslinks and bone mineralization, but prevented non-enzymatic reaction of collagen crosslinks and accumulation of bone microdamage. Bone anti-resorptive agents such as bisphosphonates slow down bone remodeling so that bone mineralization, bone microdamage, and non-enzymatic collagen crosslinks all increase. Bone anabolic agents such as parathyroid hormone decrease bone mineralization and bone microdamage by stimulating bone remodeling. ELD did not fit into either category. Histological analysis indicated that the ELD treatment strongly suppressed bone resorption by reducing the number of osteoclasts, while also stimulating focal bone formation without prior bone resorption (bone minimodeling). These bidirectional activities of ELD may account for its unique effects on bone quality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".