Mechanical Stress Via Muscle Contractile Exercise Suppresses Atrophic Alterations of Bone-microstructure in Immobilized Rat Femurs.
Bibliographic record
Abstract
OBJECTIVES: This study aimed to determine whether mechanical stress via muscle contractile exercise with belt electrode-skeletal muscle electrical stimulation (B-SES) device effectively prevents immobilization-induced bone atrophy. METHODS: Wistar rats were randomly divided into the control (CON) group, immobilization (IM) group (immobilized treatment only), HES and LES groups (immobilized treatment and high or low-intensity electrical muscular stimulation through B-SES device). Bilateral femurs were used for X-ray micro-CT and biomechanical tests. RESULTS: The maximum load value was significantly lower in the IM and HES groups than in the CON group and significantly higher in the LES group than in the IM group. The maximum crushing load was significantly lower in the IM, HES, and LES groups than in the CON group, and significantly higher in the HES and LES groups than that in the IM group. In micro-CT, the mechanical stress by B-SES device did not affect degenerative microstructural changes in the cortical bone, but prevented those changes in the cancellous bone. CONCLUSIONS: Applying mechanical stress via B-SES device suppressed the loss of cancellous bone density and degenerative microstructural changes caused by immobilization, which in turn suppressed the reduction of bone strength. From these findings, muscle contractile exercise may be effective in preventing immobilization-induced bone atrophy.
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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 | 0.000 | 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) | 0.001 | 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".