The role of well-defined nanotopography of titanium implants on osseointegration: cellular and molecular events in vivo
Bibliographic record
Abstract
Dimitrios Karazisis,1–3 Ahmed M Ballo,1,2,4 Sarunas Petronis,2,5 Hossein Agheli,1,2 Lena Emanuelsson,1,2 Peter Thomsen,1,2 Omar Omar1,2 1Department of Biomaterials, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; 2BIOMATCELL, VINN Excellence Center of Biomaterials and Cell Therapy, Gothenburg, Sweden; 3Department of Oral and Maxillofacial Surgery, Sahlgrenska Academy, University of Gothenburg, Sweden; 4Department of Oral Health Sciences, Faculty of Dentistry, University of British Columbia, Vancouver, BC, Canada; 5Department of Chemistry, Materials and Surfaces, SP Technical Research Institute of Sweden, Borås, Sweden Purpose: Mechanisms governing the cellular interactions with well-defined nanotopography are not well described in vivo. This is partly due to the difficulty in isolating a particular effect of nanotopography from other surface properties. This study employed colloidal lithography for nanofabrication on titanium implants in combination with an in vivo sampling procedure and different analytical techniques. The aim was to elucidate the effect of well-defined nanotopography on the molecular, cellular, and structural events of osseointegration.Materials and methods: Titanium implants were nanopatterned (Nano) with semispherical protrusions using colloidal lithography. Implants, with and without nanotopography, were implanted in rat tibia and retrieved after 3, 6, and 28 days. Retrieved implants were evaluated using quantitative polymerase chain reaction, histology, immunohistochemistry, and energy dispersive X-ray spectroscopy (EDS).Results: Surface characterization showed that the nanotopography was well defined in terms of shape (semispherical), size (79±6 nm), and distribution (31±2 particles/µm2). EDS showed similar levels of titanium, oxygen, and carbon for test and control implants, confirming similar chemistry. The molecular analysis of the retrieved implants revealed that the expression levels of the inflammatory cytokine, TNF-α, and the osteoclastic marker, CatK, were reduced in cells adherent to the Nano implants. This was consistent with the observation of less CD163-positive macrophages in the tissue surrounding the Nano implant. Furthermore, periostin immunostaining was frequently detected around the Nano implant, indicating higher osteogenic activity. This was supported by the EDS analysis of the retrieved implants showing higher content of calcium and phosphate on the Nano implants.Conclusion: The results show that Nano implants elicit less periimplant macrophage infiltration and downregulate the early expression of inflammatory (TNF-α) and osteoclastic (CatK) genes. Immunostaining and elemental analyses show higher osteogenic activity at the Nano implant. It is concluded that an implant with the present range of well-defined nanocues attenuates the inflammatory response while enhancing mineralization during osseointegration. Keywords: nanofabrication, gene expression, immunohistochemistry, energy dispersive X-ray spectroscopy, inflammatory cytokines, 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".