Rational Design of Bioactive Materials for Bone Hemostasis and Defect Repair
Bibliographic record
Abstract
Everyday unnatural events such as trauma, accidents, military conflict, disasters, and even medical malpractice create open wounds and massive blood loss, which can be life-threatening. Fractures and large bone defects are among the most common types of injuries. Traditional treatment methods usually involve rapid hemostasis and wound closure, which are convenient and fast but may result in various complications such as nerve injury, deep infection, vascular injury, and deep hematomas. To address these complications, various studies have been conducted on new materials that can be degraded in the body and reduce inflammation and abscesses in the surgical area. This review presents the latest research progress in biomaterials for bone hemostasis and repair. The mechanisms of bone hemostasis and bone healing are first introduced and then principles for rational design of biomaterials are summarized. After providing representative examples of hemostatic biomaterials for bone repair, future challenges and opportunities in the field are proposed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".