Evidence for a Role for Nanoporosity and Pyridinoline Content in Human Mild Osteogenesis Imperfecta
Bibliographic record
Abstract
Osteogenesis imperfecta (OI) is a clinically and genetically heterogeneous connective tissue disorder characterized by bone fragility that arises from decreased bone mass and abnormalities in bone material quality. OI type I represents the milder form of the disease and according to the original Sillence classification is characterized by minimal skeletal deformities and near-normal stature. Raman microspectroscopy is a vibrational spectroscopic technique that allows the determination of bone material properties in bone biopsy blocks with a spatial resolution of ∼1 µm, as a function of tissue age. In the present study, we used Raman microspectroscopy to evaluate bone material quality in transiliac bone biopsies from children with a mild form of OI, either attributable to collagen haploinsufficiency OI type I (OI-Quant; n = 11) or aberrant collagen structure (OI-Qual; n = 5), as a function of tissue age, and compared it against the previously published values established in a cohort of biopsies from healthy children (n = 54, ages 1 to 23 years). The results indicated significant differences in bone material compositional characteristics between OI-Quant patients and healthy controls, whereas fewer were evident in the OI-Qual patients. Differences in both subgroups of OI compared with healthy children were evident for nanoporosity, mineral maturity/crystallinity as determined by maxima of the v1 PO4 Raman band, and pyridinoline (albeit in different direction) content. These alterations in bone material compositional properties most likely contribute to the bone fragility characterizing this disease. © 2016 American Society for Bone and Mineral Research.
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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 | 0.001 | 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) | 0.001 | 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".