Effects of Liver-Derived Insulin-Like Growth Factor I on Bone Metabolism in Mice
Bibliographic record
Abstract
Insulin-like growth factor (IGF) I is an important regulator of both skeletal growth and adult bone metabolism. To better understand the relative importance of systemic IGF-I versus locally expressed IGF-I we have developed a transgenic mouse model with inducible specific IGF-I gene inactivation in the liver (LI-IGF-I-/-). These mice are growing normally up to 12 weeks of age but have a disturbed carbohydrate and lipid metabolism. In this study, the long-term effects of liver-specific IGF-I inactivation on skeletal growth and adult bone metabolism were investigated. The adult (week 8-55) axial skeletal growth was decreased by 24% in the LI-IGF-I-/- mice whereas no major reduction of the adult appendicular skeletal growth was seen. The cortical cross-sectional bone area, as measured in the middiaphyseal region of the long bones, was decreased in old LI-IGF-I-/- mice. This reduction in the amount of cortical bone was caused mainly by decreased periosteal circumference and was associated with a weaker bone determined by a decrease in ultimate load. In contrast, the amount of trabecular bone was not decreased in the LI-IGF-I-/- mice. DNA microarray analysis of 30-week-old LI-IGF-I-/- and control mice indicated that only four genes were regulated in bone whereas approximately 40 genes were regulated in the liver, supporting the hypothesis that liver-derived IGF-I is of minor importance for adult bone metabolism. In summary, liver-derived IGF-I exerts a small but significant effect on cortical periosteal bone growth and on adult axial skeletal growth while it is not required for the maintenance of the trabecular bone in adult mice.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".