Exercise improves femoral whole-bone and tissue-level biomechanical properties in hyperphagic OLETF rats
Bibliographic record
Abstract
An often-overlooked comorbidity of type 2 diabetes (T2D) is increased fracture risk. Since traditional T2D therapies focus solely on glucose homeostasis, there is an increased need for effective treatment strategies that improve both metabolic and bone health. The current study evaluated if previously reported protective effects of exercise (EX) on cortical bone geometry and biomechanical properties are due to the prevention of obesity compared with obese Otsuka Long-Evans Tokushima Fatty (OLETF) rats or the unique skeletal effects of exercise. Four-week-old male OLETF rats were randomly assigned to 1 of 3 groups, each fed a standard rodent chow diet until 40 weeks of age: ad libitum-fed sedentary (O-SED), ad libitum-fed EX (O-EX), or a control group body-weight-matched to the O-EX group by caloric restriction (O-CR). Ad libitum-fed sedentary Long-Evans Tokushima Otsuka (L-SED) rats were used as a lean control. EX or CR prevented the excess body mass accumulation and elevated HbA1c observed in O-SED. Total-body bone mineral density was greater in O-EX than O-CR, but similar to L-SED and O-SED. O-EX and O-CR had lower osteocalcin and TRAP5b than O-SED and L-SED. EX or CR prevented the ∼3-fold increase in CTx in O-SED versus L-SED. EX increased femoral cortical mass accumulation and expansion at the mid-diaphysis compared with O-CR. EX or CR significantly increased tissue-level stiffness and strength compared with O-SED and L-SED, but O-EX had greater whole-bone stiffness than all other groups. In summary, EX has distinct advantages over CR for improving bone biomechanical properties in hyperphagic OLETF rats.
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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) | 0.001 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".