Differential Bone Metabolism and Protein Expression in Mice Fed a High-Fat diet Versus Pre-Hibernation Fattening in Daurian Ground Squirrels: A Comparison Between Pathological and Healthy Obesity
Bibliographic record
Abstract
Abstract Background This study compared effects on bone metabolism and morphology of pathological obesity induced by excessive fat intake in a non-hibernator (mice) versus healthy obesity due to pre-hibernation fattening in a hibernator (ground squirrels). Methods Kunming mice were fed a high-fat diet for 3 months to provide a model of pathological obesity (OB group). Daurian ground squirrels fattened naturally in their pre-hibernation season (PRE group) were used as a healthy obesity model. Body weight and adipose tissue wet weight were measured. Micro-computed tomography and three-point bending tests were used to determine the microstructure and mechanical properties of bone. Western blots were used to analyze protein expression levels related to bone formation (RunX2, OCN, ALP), bone resorption (RANKL, Cathepsin K, MMP9) and Wnt signaling (P-β-catenin, GSK-3β). Results Micro-CT showed that there was no obvious bone loss in the OB group, compared with controls, whereas bone formation in the PRE group was enhanced, compared to summer-active squirrels. Results of three-point bending tests showed that stiffness of the femur in OB mice was significantly enhanced, whereas the mechanical properties of bone in the PRE group did not change. Analysis of bone protein expression showed significantly increased expression levels of ALP, OCN, RANKL, MMP9, Cathepsin K, GSK-3β and P-β-catenin in OB mice, but RunX2 expression did not change. By contrast, PRE ground squirrels, showed significantly increased expression of most proteins except for OCN that decreased significantly, and P-β-catenin that did not change. Conclusion For non-hibernating mice, moderate obesity had a certain protective effect on bones, demonstrating two-way regulation, enhancing both bone loss and bone formation, so that bone metabolism was at a higher level of metabolic balance. For pre-hibernating ground squirrels, the healthy obesity acquired before hibernation had a positive effect on the microstructure of bones and also enhanced the expression levels of proteins related to bone formation, bone resorption and Wnt signaling.
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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) | 0.000 | 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".