Quantitative Microcomputed Tomography Assessment of Intratrabecular, Intertrabecular, and Cortical Bone Architecture in a Rat Model of Severe Renal Osteodystrophy
Bibliographic record
Abstract
OBJECTIVE: To determine the effects of renal osteodystrophy (ROD) on bone microarchitecture in growing rats. METHODS: A total of 24 rats underwent 5/6 nephrectomy (NX) and were fed a high-phosphorus diet to induce ROD; another 6 underwent sham NX. In vitro microcomputed tomography images (GEMS, London, Ontario, Canada) were obtained in the femoral metaphysis and midshaft. RESULTS: Trabecular and cortical bone volume/total volume (BV/TV) were significantly lower in NX specimens because of pores within the trabeculae and along the endosteal surface. Topological analysis using component labeling in 3-dimensions verified that trabecular pores connected to the marrow space. After the trabecular pores were filled using a morphological filter, trabecular thickness was significantly increased in NX. In contrast, cortical thickness was significantly decreased in NX compared with controls; however, after filling the endocortical pores, thickness did not differ. CONCLUSIONS: The ROD resulted in decreased cortical and trabecular BV/TV, increased porosity, and increased trabecular thickness. Advanced image processing algorithms demonstrated the effects of cortical and trabecular porosity on BV/TV and structure in ROD.
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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) | 0.000 | 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 | 0.001 |
| 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".