Bone Adaptation to Mechanical Loading Is Disrupted by Inhibition of Endothelin Receptor A in Ex Vivo Human Trabecular Bone
Bibliographic record
Abstract
Interactive effects among loading and biochemical signaling on the skeleton are incompletely understood. Endothelin-1 (ET1) is an essential potent autocrine/paracrine signaling molecule recognized for its role in bone mechanotransduction. Ex vivo experiments are a novel alternative method (NAM) to investigate factors, like ET1, that otherwise would harm the organism health. The hypothesis that antagonism of endothelin receptor A (EDNRA) would inhibit mechanotransduction pathways associated with mechanical load adaptation in human trabecular bone was tested in a 4-week ex vivo study with microstructural analyses. Ex vivo trabecular bone cores (n = 48, 5 mm × 10 mm) from hip heads donated by two hip arthroplasty patients were subjected to compressive loading in the presence or absence of EDNRA antagonist. Cores were allocated to four groups: control, blocked (10 μM/L BQ-123), loaded (-3000 με), and loaded+blocked. Data were analyzed with Kruskal-Wallace tests with Dunn's posthoc test, and Friedman analysis with repeated measures. Microstructural analyses were validated against physical measurements (R2 > 0.96). Pan endothelin (ET) and prostaglandin E2 (PGE2) increased over time for all groups. Pan ET was higher in blocked in comparison to loaded cores; whereas, PGE2 was higher in the loaded cores in comparison to controls. Percent change in apparent elastic modulus was highest in loaded (26.1% IQR 12.7-35.9%) and 56% lower in both blocked groups. EDNRA inhibition was found to interact with pathways that respond to mechanical load. This finding suggests that endothelin is required for the transduction of mechanical cues into biochemical signals during the anabolic response of bone to mechanical load.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".