Paradoxical Response to Mechanical Unloading in Bone Loss, Microarchitecture, and Bone Turnover Markers
Bibliographic record
Abstract
BACKGROUND: Sclerostin, encoded by the SOST gene, has been implicated in the response to mechanical loading in bone. Some studies demonstrated that unloading leads to up-regulated SOST expression, which may induce bone loss. PURPOSE: Most reported studies regarding the changes caused by mechanical unloading were only based on a single site. Considering that the longitudinal bone growth leads to cells of different age with different sensitivity to unloading, we hypothesized that bone turnover in response to unloading is site specific. METHODS: We established a disuse rat model by sciatic neurectomy in tibia. In various regions at two time-points, we evaluated the bone mass and microarchitecture in surgically-operated rats and control rats by micro-Computed Tomography (micro-CT) and histology, sclerostin/SOST by immunohistochemistry, enzyme-linked immunosorbent assay (ELISA), and quantitative reverse transcription polymerase chain reaction (qPCR), tartrate resistant acid phosphatase 5b (TRAP 5b) by ELISA and TRAP staining, and other bone markers by ELISA. RESULTS: Micro-CT and histological analysis confirmed bone volume in the disuse rats was significantly decreased compared with those in the time-matched control rats, and microarchitecture also changed 2 and 8 weeks after surgery. Compared with the control groups, SOST mRNA expression in the diaphysis was down-regulated at both week 2 and 8. On the contrary, the percentage of sclerostin-positive osteocytes showed an up-regulated response in the 5 - 6 mm region away from the growth plate, while in the 2.5 - 3.5 mm region, the percentage was no significant difference. Nevertheless, in 0.5 - 1.5 mm region, the percentage of sclerostin-positive osteocytes decreased after 8 weeks, consistent with serum SOST level. Besides, the results of TRAP also suggested that the expression in response to unloading may be opposite in different sites or system. CONCLUSION: Our data indicated that unloading-induced changes in bone turnover are probably site specific. This implies a more complex response pattern to unloading and unpredictable therapeutics which target SOST or TRAP 5b.
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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 | 0.001 |
| 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".