Bone Mineralization in Polyostotic Fibrous Dysplasia: Histomorphometric Analysis
Bibliographic record
Abstract
Fibrous dysplasia (FD) of bone can be complicated by renal phosphate wasting. The effect of hypophosphatemia on normal and dysplastic bone of FD patients has not been well characterized. In this study, we compared serum phosphorus (sPi) levels to histomorphometric findings in 27 iliac bone samples from 23 children and adolescents (aged 4.2-16.4 years) with polyostotic FD. The samples were separated into two groups, based on the presence (n = 10) or absence (n = 17) of a dysplastic lesion within the specimen. Histomorphometric results were compared with those from 18 age-matched control subjects without metabolic bone disease. In dysplastic lesions, trabeculae were clearly thinner and increased in number. Osteoid indices, osteoblast surface per bone surface, and mineralization lag time were elevated in dysplastic areas, but there was no detectable effect of sPi concentrations on these indices. In nondysplastic bone tissue, low sPi levels were associated with mildly increased osteoid thickness and prolonged mineralization lag time. None of the 13 patients in whom hand X-rays were available at the time of biopsy had radiological signs of rickets. In conclusion, low sPi can cause a mild systemic mineralization defect in FD, but the more severe mineralization defect seen in dysplastic lesions is independent of sPi levels. It is debatable whether the mild systemic mineralization defect warrants treatment with oral phosphorus supplementation if signs of rickets are absent.
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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 | 0.002 | 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".