Lipid Nanoparticle Delivery of siRNA to Osteocytes Leads to Effective Silencing of SOST and Inhibition of Sclerostin In Vivo
Bibliographic record
Abstract
Sclerostin is a protein secreted by osteocytes that is encoded by the SOST gene; it decreases bone formation by reducing osteoblast differentiation through inhibition of the Wnt signaling pathway. Silencing the SOST gene using RNA interference (RNAi) could therefore be an effective way to treat osteoporosis. Here, we investigate the utility of lipid nanoparticle (LNP) formulations of siRNA to silence the SOST gene in vitro and in vivo. It is shown that primary mouse embryonic fibroblasts (MEF) provide a useful model system in which the SOST gene can be induced by incubation in osteogenic media, allowing development of optimized SOST siRNA for silencing the SOST gene. Incubation of MEF cells with LNP containing optimized SOST siRNA produced significant, prolonged knockdown of the induced SOST gene in vitro, which was associated with an increase in osteogenic markers. Intravenous (i.v.) administration of LNP containing SOST siRNA to mice showed significant accumulation of LNP in osteocytes in compact bone, depletion of SOST mRNA and subsequent reduction of circulating sclerostin protein, establishing the potential utility for LNP siRNA systems to promote bone formation.
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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".