Effect of Titanium and Zirconium Oxide Microparticles on Pro-Inflammatory Response in Human Macrophages under Induced Sterile Inflammation: An In Vitro Study.
Liza L RamenzoniLaura B FlückigerThomas AttinPatrick R SchmidlinPublished in: Materials (Basel, Switzerland) (2021)
The wear-debris particles released by shearing forces during dental implant insertion may contribute to inflammatory reactions or osteolysis associated with peri-implantitis by stimulating inflammasome-activation. The study aim was to examine cytotoxic and pro-inflammatory effects of titanium (TiO2) and zirconia (ZrO2) particles in macrophages regarding their nature/particle concentration over time under sterile lipopolysaccharide (LPS) inflammation. Macrophages were exposed to TiO2 and ZrO2 particles (≤5 µm) in cell culture. Dental glass was used as inert control and LPS (1 μg/mL) was used to promote sterile inflammation. Cytotoxicity was determined using MTT assays and cytokine expression of TNF-α, IL-1β and IL-6 was evaluated by qRT-PCR. Data were analyzed using Student's t-test and ANOVA (p ≤ 0.05). Cytotoxicity was significantly increased when exposed to higher concentrations of glass, TiO2 and ZrO2 (≥107 particles/mL) compared to controls (p ≤ 0.05). Macrophages challenged with TiO2 particles expressed up to ≈3.5-fold higher upregulation than ZrO2 from 12 to 48 h. However, when exposed to LPS, TiO2 and ZrO2 particle-induced pro-inflammatory gene expression was further enhanced (p ≤ 0.05). Our data suggest that ZrO2 particles produce less toxicity/inflammatory cytokine production than TiO2. The present study shows that the biological reactivity of TiO2 and ZrO2 depends on the type and concentration of particles in a time-dependent manner.
Keyphrases
- inflammatory response
- oxidative stress
- quantum dots
- visible light
- gene expression
- anti inflammatory
- poor prognosis
- lps induced
- lipopolysaccharide induced
- toll like receptor
- rheumatoid arthritis
- endothelial cells
- high glucose
- electronic health record
- dna methylation
- cell proliferation
- binding protein
- high throughput
- deep learning
- stress induced