In Vitro Assay to Examine Osteoclast Resorptive Activity Under Estrogen Withdrawal
Bibliographic record
Abstract
The bone is a highly dynamic organ that undergoes continuous remodeling through an intricate balance of bone formation and degradation. Hyperactivation of the bone-degrading cells, the osteoclasts (OCs), occurs in disease conditions and hormonal changes in females, resulting in osteoporosis, a disease characterized by altered microarchitecture of the bone tissue, and increased bone fragility. Thus, building robust assays to quantify OC resorptive activity to examine the molecular mechanisms underlying bone degradation is critical. Here, we establish an in vitro model to investigate the effect of estrogen withdrawal on OCs derived from the mouse macrophage RAW 264.7 cell line in a bone biomimetic microenvironment. This simple and robust model can also be adapted to examine the effect of drugs and genetic factors influencing OC resorptive activity in addition to being compatible with fluorescent imaging. Key features • A robust in vitro protocol that allows molecular and functional studies of mature osteoclasts in response to estrogen and its withdrawal. • Generation of inorganic bone-mimetic substrates for culturing and examining osteoclast resorptive behavior. • This quantitative image-based approach is compatible with brightfield and fluorescence microscopy to assess osteoclast resorptive activity.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".