Sex-specific responses in trabecular and cortical microstructure of tibia due to repeated irradiation from micro-computed tomography in adult CD-1 mice
Bibliographic record
Abstract
While repeated in vivo micro-computed tomography (μCT) allows for longitudinal measurement of bone outcomes in rodent models, it is important to determine that the resulting irradiation – dependent on the frequency and number of scans - does not exceed the effects of the intervention. The objective of this study was to determine whether repeated irradiation exposure from μCT scans at 1-month intervals for a total of four scans would alter trabecular or cortical bone structure outcomes and/or bone mineral density in tibias from both male and female CD-1 mice. The right tibia of male (n = 12) and female (n = 11) CD-1 mice were scanned using μCT at 2, 3, 4, and 5 months of age, while the contralateral left tibia served as a control and was scanned only at 5 months of age. All scans were performed at a resolution of 9 μm using a radiation dose of 460 mGy per scan. Some outcomes of trabecular bone structure were affected by repeated irradiation in both males and females. The bone volume fraction was lower in the irradiated right tibia compared to the non-irradiated left tibia in both males (p < 0.05) and females (p < 0.01) as a result of decreased trabecular number (males p < 0.05; females p < 0.05) and increased trabecular separation (males p < 0.05; females p < 0.01). Some cortical measures were also affected in females but not in males, including lower cortical bone periosteal perimeter (p < 0.05), lower total area (p < 0.01) and lower marrow area (p < 0.05) with repeated irradiation. Exposure to repeated radiation at intervals of 1 month, for a total of four scans, altered trabecular bone in both male and female CD-1 mice while outcomes of cortical bone structure were altered only in females.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".