Bone structure and composition in a hyperglycemic, obese, and leptin receptor-deficient rat: Microscale characterization of femur and calvarium
Bibliographic record
Abstract
Metabolic abnormalities, such as diabetes mellitus and obesity, can impact bone quantity and/or bone quality. In this work, we characterize bone material properties, in terms of structure and composition, in a novel rat model with congenic leptin receptor (LepR) deficiency, severe obesity, and hyperglycemia (type 2 diabetes-like condition). Femurs and calvaria (parietal region) from 20-week-old male rats are examined to probe bones formed both by endochondral and intramembranous ossification. Compared to the healthy controls, the LepR-deficient animals display significant alterations in femur microarchitecture and in calvarium morphology when analyzed by micro-computed X-ray tomography (micro-CT). In particular, shorter femurs with reduced bone volume, combined with thinner parietal bones and shorter sagittal suture, point towards a delay in the skeletal development of the LepR-deficient rodents. On the other hand, LepR-deficient animals and healthy controls display analogous bone matrix composition, which is assessed in terms of tissue mineral density by micro-CT, degree of mineralization by quantitative backscattered electron imaging, and various metrics extrapolated from Raman hyperspectral images. Some specific microstructural features, i.e., mineralized cartilage islands in the femurs and hyper-mineralized areas in the parietal bones, also show comparable distribution and characteristics in both groups. Overall, the altered bone microarchitecture in the LepR-deficient animals indicates compromised bone quality, despite the normal bone matrix composition. The delayed development is also consistent with observations in humans with congenic Lep/LepR deficiency, making this animal model a suitable candidate for translational research.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".