Estrogen withdrawal alters cytoskeletal and primary ciliary dynamics resulting in increased Hedgehog and osteoclastogenic paracrine signalling in osteocytes
Bibliographic record
Abstract
Abstract Estrogen deficiency during post-menopausal osteoporosis leads to osteoclastogenesis and bone loss. Increased pro-osteoclastogenic signalling (RANKL/OPG) by osteocytes occurs following estrogen withdrawal (EW) and is associated with impaired focal adhesions (FAs) and a disrupted actin cytoskeleton. RANKL production is mediated by Hedgehog signalling in osteocytes, a signalling pathway associated with the primary cilium, and the ciliary structure is tightly coupled to the cytoskeleton. Therefore, the objective of this study was to investigate the role of the cilium and associated signalling in EW-mediated osteoclastogenic signalling in osteocytes. We report that EW leads to an elongation of the cilium and increase in Hedgehog and osteoclastogenic signalling. Significant trends were identified linking cilia elongation with reductions in cell area and % FA area/cell area, indicating that cilia elongation is associated with disruption of FAs and actin contractility. To verify this, we inhibited FA assembly via α v β 3 antagonism and inhibited actin contractility and demonstrated an elongated cilia and increased expression of Hh markers and Rankl expression. Therefore, our results suggest that the EW conditions associated with osteoporosis lead to a disorganisation of α v β 3 integrins and reduced actin contractility, which were associated with an elongation of the cilium, activation of the Hh pathway and osteoclastogenic paracrine signalling.
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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 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".