Differential Effects of PPAR-γ Activation versus Chemical or Genetic Reduction of DPP-4 Activity on Bone Quality in Mice
Bibliographic record
Abstract
Patients with type 2 diabetes mellitus have an increased risk of fracture that can be further exacerbated by thiazolidinediones. A new class of antidiabetic agents control glucose through reduction of dipeptidyl peptidase-4 (DPP-4) activity; however the importance of DPP-4 for the control of bone quality has not been extensively characterized. We compared the effects of the thiazolidinedione pioglitazone and the DPP-4 inhibitor sitagliptin on bone quality in high-fat diet (HFD)-fed wild-type mice. In complementary studies, we examined bone quality in Dpp4(+/+) vs. Dpp4(-/-) mice. Pioglitazone produced yellow bones with greater bone marrow adiposity and significantly reduced vertebral bone mechanics in male, female, and ovariectomized (OVX) HFD fed female mice. Pioglitazone negatively affected vertebral volumetric bone mineral density, trabecular architecture, and mineral apposition rate in male mice. Sitagliptin treatment of HFD-fed wild-type mice significantly improved vertebral volumetric bone mineral density and trabecular architecture in female mice, but these improvements were lost in females after OVX. Genetic inactivation of Dpp4 did not produce a major bone phenotype in male and female Dpp4(-/-) mice; however, OVX Dpp4(-/-) mice exhibited significantly reduced femoral size and mechanics. These findings delineate the skeletal consequences of pharmacological and genetic reduction of DPP-4 activity and reveal significant differences in the effects of pioglitazone vs. sitagliptin vs. genetic Dpp4 inactivation on bone mechanics in mice.
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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".