Local Delivery of Exosomes and Antibiotics in Hydroxyapatite-Based Nanocement for Osteomyelitis Management
Bibliographic record
Abstract
The management of bone and joint infections is a formidable challenge in orthopedics and poses a global health concern. While clinical management emphasizes infection prevention and complete eradication, an effective strategy for stabilizing skeletal tissue with adequate soft tissue coverage remains limited. In this study, we have employed a novel approach of using the local delivery of exosomes and antibiotics (rifampicin) using a hydroxyapatite-based nanocement carrier to manage the residual space created during debridement effectively. Additionally, we synthesized a periosteum-guiding antioxidant herbal membrane to leverage the inherent periosteum regeneration capability of the bone, facilitating bone callus repair and natural healing. The synthesized scaffolds were biocompatible and demonstrated potent antibacterial activity in vitro . When evaluated in vivo in the Staphylococcus aureus -induced rat tibial osteomyelitis model, the released drugs successfully cleared the residual bacteria and the released exosome promoted bone healing, resulting in 3-fold increase in bone volume as analyzed via micro-CT analysis. Immunofluorescence staining of periosteum-specific markers also indicated the complete formation of periosteal layers, thus highlighting the complete bone repair.
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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) | 0.000 | 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 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".