Parathyroid Hormone An Anabolic Treatment for Osteoporosis.
Bibliographic record
Abstract
Osteoporosis is a disease characterised by low bone mass, structural deterioration of bone and increased risk of fracture. The prevalence, and cost, of osteoporosis is increasing dramatically with our ageing population and the World Health Organization now considers it to be the second-leading healthcare problem. All currently approved therapies for osteoporosis (eg., estrogen, bisphosphonates, calcitonin and selective estrogen receptor modulators) are anti-resorptive agents that act on osteoclasts to prevent further bone loss. A new class of bone anabolic agent capable of building mechanically strong new bone in patients with established osteoporosis is in development. While the parathyroid hormone (PTH) is classically considered to be a bone catabolic agent, when delivered intermittently at low doses PTH potently stimulates cortical and trabecular bone growth in animals humans. The native hPTH-(1-84) and its osteogenic fragment, hPTH-(1-34), have already entered Phase III clinical trials. Understanding the mechanism of PTH's osteogenic actions has led to the development of smaller PTH analogues which can also build mechanically normal bone in osteopenic rats. These new PTH analogues are promising candidates for treating osteoporosis in humans as they are as efficacious as hPTH-(1-84) and hPTH-(1-34), but there is evidence that they may have considerably less ability to induce hypercalcemia, the major side effect of PTH therapy. In addition to treating osteoporosis, PTHs may be used to promote fracture healing, to restore bone loss in immobilized patients, or following excessive glucocorticoid or prolonged spaceflight, and to treat psoriasis.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.026 | 0.012 |
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".