Ablation of Hepatic Production of the Acid-Labile Subunit in Bovine-GH Transgenic Mice: Effects on Organ and Skeletal Growth
Bibliographic record
Abstract
Growth hormone (GH) and insulinlike growth factor 1 (IGF-1) are anabolic hormones that facilitate somatic and skeletal growth and regulate metabolism via endocrine and autocrine/paracrine mechanisms. We hypothesized that excess tissue production of GH would protect skeletal growth and integrity in states of reduction in serum IGF-1 levels. To test our hypothesis, we used bovine GH (bGH) transgenic mice as a model of GH hypersecretion and ablated the liver-derived acid-labile subunit, which stabilizes IGF-1 complexes with IGF-binding protein-3 and -5 in circulation. We used a genetic approach to create bGH/als gene knockout (ALSKO) mice and small interfering RNA (siRNA) gene-silencing approach to reduce als or igf-1 gene expression. We found that in both models, decreased IGF-1 levels in serum were associated with decreased body and skeletal size of the bGH mice. Excess GH produced more robust bones but compromised mechanical properties in male mice. Excess GH production in tissues did not protect from trabecular bone loss in response to reductions in serum IGF-1 (in bGH/ALSKO or bGH mice treated with siRNAs). Reduced serum IGF-1 levels in the bGH mice did not alleviate the hyperinsulinemia and did not resolve liver or kidney pathologies that resulted from GH hypersecretion. We concluded that reduced serum IGF-1 levels decrease somatic and skeletal growth even in states of excess GH.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".