Tissue response to a novel bone adhesive implanted subcutaneously in rats: A histological and gene expression analysis
Bibliographic record
Abstract
Abstract Median sternotomy provides access to the heart and surrounding valves for cardiothoracic surgery. However, complications arise such as micro‐motion and separation between the two sternal halves. To prevent these complications, the use of a bone adhesive has been proposed to augment the mechanical union of the two sternal halves when combined with wire cerclage. Our group has developed a bone adhesive for sternal fixation, utilizing a glass polyalkenoate cement (GPC) based on a zinc silicate ionomeric glass (mole fraction: SiO 2 :0.48, ZnO:0.36, CaO:0.12, SrO:0.04). Here we present the first soft‐tissue biological safety assessment of this novel Sr/Zn‐GPC, where we implanted the material subcutaneously in rats for 6 and 12 weeks. Polymethyl‐methacrylate (PMMA) bone cement was used as a baseline control with respect to inflammation and biocompatibility. Histological assessment revealed no adverse tissue reaction nor ectopic bone formation in response to the novel material. Additionally, relative expression of pro‐inflammatory and osteogenic genes (Col1a1, SOX9, Runx2, IL‐1, IL‐6, and TNF‐α) was assessed in the tissue surrounding implants and revealed no significant differences in expression between the Sr/Zn‐GPC and PMMA implants.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".