The Effects of Mechanical Loading on the mRNA Expression of Growth-Plate Cells
Bibliographic record
Abstract
Bone growth is a complex process involving proliferation, maturation and hypertrophy of chondrocytes in the growth plates. Mechanical forces applied to growing bones alter their longitudinal growth. However, the mechanisms by which chondrocytes modulate longitudinal bone growth are not well understood. This in vitro study investigated the effects of mechanical loading on the mRNA expression pattern of key molecular components of the growth-plate. Short-term static loading was applied to rat proximal tibial growth-plate explants. Various age groups at specific developmental stages were investigated. In situ hybridization was used to assess the mRNA expression of the cells in different zones of the growth-plate. Four key components were investigated: 18s (basic cell metabolism), type II collagen (major extracellular matrix component), type X collagen (matrix component in hypertrophic zone) and PTH-PTHrP receptors (pre-hypertrophic chondrocytes). The spatial variation in the mRNA expression between loaded explants and their contralateral controls was compared to establish: -the sensitivity of the different growth-plate zones to mechanical loading; -the sensitivity of the different developmental stages to loading. Preliminary results indicated that static loading on the growth plate of 80 d.o. rats affects type II and X collagen gene expressions while PTH-PTHrP remains insensitive to static loading. Improved understanding of growth-plate mechanics and the underlying biology is required to provide a scientific basis for the treatment of progressive deformities.
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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) | 0.002 | 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".