Effects of tenascin-C on dental pulp tissue in mice in vivo and on the proliferation and differentiation of dental pulp stem cells into odontoblasts and calcification in vitro
Kojima, K.; Akashi, Y.; Nakajima, K.; Kokubun, K.; Shintani, S.; Matsuzaka, K.
Show abstract
This study aimed to investigate the effects of tenascin-C (TN-C) on dental pulp tissue and on dental pulp stem cells (DPSCs). In in vivo studies, A collagen sponge with phosphate-buffered saline (PBS) for the control group or with TN-C for the experimental group was placed over the dental pulp of mice. The root pulp was excised at 7 and 21 days postoperatively and was observed microscopically using HE staining and immunohistochemistry. Inflammatory cells were found in the entire pulp tissue in the control group but no inflammatory cells were identified in the pulp tissue in the TN-C-treated experimental group. Further, nestin-positive cells at 7 days and dentin sialophosphoprotein (DSPP)-positive cells at 21 days were seen in the experimental group. In in vitro studies, DPSCs were cultured in a medium with or without TN-C, after which the proliferation rate of DPSCs was measured mRNA expression levels were examined using quantitative reverse transcription polymerase chain reaction (qRT-PCR), and the formation of calcified nodules was investigated using alizarin red staining. The cell proliferation rate was not significantly different between the experimental and control groups. The expression of nestin mRNA on day 7 was significantly higher in the experimental group than in the control group (P<0.05), but the expression of osteocalcin (OCN) mRNA was significantly higher in the control group than in the experimental group (P<0.05). More calcified nodules formed in the control group than in the experimental group. These results suggest that TN-C regulates inflammation during the healing process in the dental pulp and induces the differentiation of dental pulp into odontoblast-like cells. Further, TN-C promotes the early differentiation of DPSCs into odontoblast-like cells, which suggests that TN-C may further contribute to the inhibition of excessive dentin formation.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- C-Jun N-terminal kinase (JNK) pathway activation is essential for dental papilla cells polarization 97%
- Correlation of two different devices for the evaluation of primary implant stability depending on dental implant length and bone density: an in vitro study 95%
- Oral Microbiota Interactions with Titanium Implants: A pilot in-vivo and in-vitro study on the impact of Peri-implantitis 94%
Similar papers in this journal
- RT-qPCR analyses on the osteogenic differentiation from human iPS cells: An investigation of reference genes 95%
- Trabeculae microstructure parameters serve as effective predictors for marginal bone loss of dental implant in the mandible 94%
- Lactobacillus rhamnosus attenuates bone loss and maintains bone health by skewing Treg-Th17 cell balance in Ovx mice 93%
Similar papers in this journal
- EGCG-modified bone graft to modulate the recruitment of M1 macrophage and alleviate the forming of fibrous capsule 94%
- Which surface treatment improves the long-term repair bond strength of aged methacrylate-based composite resin restorations? A systematic review and network meta-analysis 92%
- Identification of differential gene expression pattern in lens epithelial cells derived from cataractous and non-cataractous lenses of Shumiya cataract rat 90%
Similar papers in this journal
- Novel application method for mesenchymal stem cell therapy utilizing its attractant-responsive accumulation property 94%
- Impact of long-term storage on mid-infrared spectral patterns of serum and synovial fluid samples of dogs with osteoarthritis 89%
- Genetic deletion of interleukin-15 is not associated with major structural changes following experimental post-traumatic knee osteoarthritis in rats 89%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.