Investigating the Interactions Between G Proteins and Estrogen Loss in the Mouse Skeletal System
Bibliographic record
Abstract
Postmenopausal osteoporosis is the most common bone disease, as estrogen deficiency is directly related to reductions in trabecular and cortical bone. In addition to sex steroids, G proteins play important roles in bone development and maintenance. We have previously developed two transgenic mouse models that have high levels of Gαs (Gs-Tg) or Gα11 (G11-Tg) in osteoblasts. Gs-Tg mice had increased bone, whereas G11-Tg mice had osteopenia. To investigate how variations in G protein signaling in osteoblasts impact postmenopausal bone health, we ovariectomized (ovx) Gs-Tg and G11-Tg mice at 4 months of age and examined their skeletal phenotypes 5 weeks post-surgery. The high bone turnover in Gs-Tg mice made them more susceptible to bone loss with ovx. Conversely, G11-Tg mice were protected from ovx-induced bone loss. This offers new insight into predicting postmenopausal bone health in individuals with high G protein levels, in addition to potentially elucidating therapeutic targets.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".