An artificial intelligence grading system of apical periodontitis in cone-beam computed tomography data.

OBJECTIVES: In order to assist junior doctors in better diagnosing apical periodontitis (AP), an artificial intelligence AP grading system was developed based on deep learning (DL) and its reliability and accuracy were evaluated. METHODS: One hundred and twenty cone-beam computed tomography (CBCT) images were selected to construct a classification dataset with four categories, which were divided by CBCT periapical index (CBCTPAI), including normal periapical tissue, CBCTPAI 1-2, CBCTPAI 3-5, and young permanent teeth. Three classic algorithms (ResNet50/101/152) as well as one self-invented algorithm (PAINet) were compared with each other. PAINet were also compared with two recent Transformer-based models and three attention models. Their performance was evaluated by accuracy, precision, recall, balanced F score (F1-score), and the area under the macro-average receiver operating curve (AUC). Reliability was evaluated by Cohen's kappa to compare the consistency of model predicted labels with expert opinions. RESULTS: PAINet performed best among the four algorithms. The accuracy, precision, recall, F1-score, and AUC on the test set were 0.9333, 0.9415, 0.9333, 0.9336, and 0.9972, respectively. Cohen's kappa was 0.911, which represented almost perfect consistency. CONCLUSIONS: PAINet can accurately distinguish between normal periapical tissues, CBCTPAI 1-2, CBCTPAI 3-5, and young permanent teeth. Its results were highly consistent with expert opinions. It can help junior doctors diagnose and score AP, reducing the burden. It can also be promoted in areas where experts are lacking to provide professional diagnostic opinions.

Development of a multi-stage model for intelligent and quantitative appraising of skeletal maturity using cervical vertebras cone-beam CT images of Chinese girls.

PURPOSE: Nowadays, the integration of Artificial intelligence algorithms and quantified radiographic imaging-based diagnostic procedures is hailing amplified deliberation particularly in assessment of skeletal maturity. So we intend to formulate a logistic regression model for intelligent and quantitative estimation of Fishman skeletal maturation index (SMI) based on the parameters attained from the cervical vertebrae CBCT images of Chinese girls. METHODS: From 709 hand wrist radiographs and CBCT images, 447 samples were randomly selected (called as G1) to build a logistic regression model. The reliability and reproducibility were assessed by the intraclass correlation coefficient (ICC) and weighted Cohen's kappa, followed by Spearman's rank correlation coefficient to identify the parameters significantly associated with the SMI. Two hundred and sixty-two other subjects (named G2) were recruited for external examination of the models by direct visual comparison and the receiver operating characteristic (ROC) curve. In cases of confusion and mispredictions, the model was modified to improve the consistency. RESULTS: Five significant parameters (Chronological age, C3 height (H3)[Formula: see text], C4 upper width (UW4), C4 lower width (LW4), and the ratio of posterior height to lower width of C4 ([Formula: see text]) were administered into logistic regression model. Despite total agreement percentage which was 84% (total AUC = 0.92), unsatisfactory performance was noticed for the 6th and 8th stages which were confused with their neighboring stages. After adjustments of the models, the total agreement percentage and AUC were upgraded to 88% and 0.96, respectively. CONCLUSION: Consistency and fitness evaluation of our models demonstrated adequate prediction percentage and reliability for automated classification of skeletal maturation. The presented constructed logistic regression model has the potential to serve as a maturity evaluation index in clinical craniofacial orthopedics in Chinese girls. The proposed model in this study showed promising strength for being expended in the event of other clinical multi-stage conditions.

Intelligent quantitative assessment of skeletal maturation based on multi-stage model: a retrospective cone-beam CT study of cervical vertebrae.

OBJECTIVE: To develop new logistic regression estimative models of the cervical vertebral maturation index (CVMI) based on cone-beam CT (CBCT)-derived parameters for intelligent evaluating skeletal maturation. METHODS: From 231 CBCT volumes (age range 7-17, mean age 11.09 years), 154 were randomly selected to produce 2D sagittal projections of the second to fourth cervical vertebrae (C2-C4). From 19 quantitative parameters, significant predictors were deduced to formulate logistic models. Using the CVMI and significant predictors of 77 other subjects, performance of the models was externally examined by direct comparison and the area under the receiver operating characteristic curve (AUC). Models were modified if required, to improve their accuracy. RESULTS: Chronological age, C3 height ([Formula: see text], and ratio of posterior height to lower width of C4 [Formula: see text] were entered as significant predictors. Accuracy of the models was acceptable (total AUC = 0.91) except for 4th and 5th stage (AUC of 0.82 and 0.83, respectively), which were mis-predicted inversely. Adjusted models were generated by bivariate logistic regression analysis and adding significant parameters ([Formula: see text] and [Formula: see text], with odds ratios of 3.308 and 3.38, respectively) from 58 subjects in 4th and 5th stages of CVMI in the model establishment group. The total AUC increased to 0.94, along with an increase in the accuracy of the latter optimized models to 77.9 and 87%, respectively. CONCLUSION: The new intelligent models reliably estimated skeletal maturation and can be utilized in the clinical field or machine learning-based skeletal maturation assessment.

Accuracy of three-dimensional photogrammetry and cone beam computed tomography based on linear measurements in patients with facial deformities.

OBJECTIVES: This study was aimed to investigate the accuracy of soft-tissue measurements obtained by two imaging modalities, three-dimensional (3D) photogrammetry and cone beam CT (CBCT) when confounded by influence factors (facial deformities and partitions). METHODS: 60 wax facial models from facially deformed patients were captured by 3D photogrammetry and CBCT. 19 linear distances on each image were measured and juxtaposed to reference values attained via a coordinate-measuring machine (CMM) as the gold-standard. Paired t-tests were used to compare linear accuracy of the test and reference systems. The influence of deformities and partitions (created by dividing the face with three vertical and five horizontal lines) on the measurement errors were analyzed by independent sample t-test and one-way ANOVA. RESULTS: Statistically significant differences were found between linear accuracy of the test and reference systems. The test values obtained by 3D photogrammetry were closer to the reference values than CBCT's. 3D photogrammetry's measurement errors were significantly higher in deformed areas, unlike CBCT's. Both systems reported significantly lower errors within partitions 8 and 13 compared to other partitions; for CBCT, aside from partitions 8 and 13, the differences in the errors for partitions 6 and 10 were significant compared to partitions 8, 12, 13, 14. CONCLUSION: 3D photogrammetry showed a higher linear accuracy than CBCT in patients with facial deformities due to protuberances. Facial reconstruction by both test modalities was significantly influenced in different facial partitions, but facial deformities extensively affected the results from 3D photogrammetry.

Root dilaceration in maxillary impacted canines and adjacent teeth: A retrospective analysis of the difference between buccal and palatal impaction.

INTRODUCTION: This research aimed to analyze the prevalence of root dilaceration in buccally impacted canines (BICs) and palatally impacted canines (PICs) with their adjacent teeth based on a retrospective cone-beam computed tomography (CBCT) investigation. METHODS: Pretreatment CBCT images of 145 subjects with unilateral maxillary canine impaction and 145 age- and sex-matched subjects without impaction were used. Prevalence of dilaceration (subclassified to root curvature and apical hook based on severity) in canines and adjacent teeth was determined in CBCT records. The root length of maxillary impacted canines was measured for further morphologic evaluations. RESULTS: Impacted canines had a significantly higher prevalence of root dilaceration than the control group and compared with the erupted contralateral canines in the experimental group (P < 0.001 for both). A significantly higher prevalence of root dilaceration was found in adjacent lateral incisors of the PICs subgroup than that of the control group (P < 0.001). Adjacent premolars had a higher prevalence of dilacerated roots in the PICs subgroup (P < 0.001) than the control group, but not for the BICs subgroup. Significantly higher prevalence of curvature (P < 0.001 for both) and hook (P = 0.008 and P < 0.001, respectively) were found in BICs and PICs roots compared with the control group. Both types of impacted canines had significantly shorter roots than the control group (P < 0.001 for both). CONCLUSIONS: BICs and PICs have a higher tendency to present root dilaceration and shorter roots. Unlike BICs, adjacent teeth to PICs were more frequently observed to have root dilaceration.

Machine Learning Predicts Lymph Node Metastasis in Early-Stage Oral Tongue Squamous Cell Carcinoma.

PURPOSE: Early-stage oral tongue squamous cell cancer (OTSCC) has a rate of metastasis to the cervical lymph nodes of 20 to 50%. This study aimed to build and validate 4 machine learning (ML) models to predict the occurrence of lymph node metastasis before and after surgery for early-stage (cT1N0 to cT2N0) OTSCC. MATERIALS AND METHODS: We designed a retrospective cross-sectional study and reviewed the clinical and pathologic records of patients with early-stage OTSCC. The sample was composed of 2 groups with different node status (positive or negative) and was randomly split into training (70%) and testing (30%) sets. Four common ML algorithms-logistic regression, random forest, support vector machine, and naive Bayes-were used to predict pathologic nodal metastasis of early-stage OTSCC. The area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were used to assess the performance of these models and conventional methods including depth of invasion (DOI), neutrophil-to-lymphocyte ratio (NLR), and tumor budding. RESULTS: A total of 145 patients (56 with positive and 89 with negative lymph nodes) were included in this study. The performance of ML models was significantly superior to that of conventional prediction methods. The random forest model performed best (AUC, 0.786; sensitivity, 85%; specificity, 75%) and exceeded the performance of NLR (AUC, 0.539; sensitivity, 53.6%; specificity, 53.9%; P = .003). When DOI, worst pattern of invasion, lymphocytic host response, and tumor budding were added to model analysis according to patients' postoperative pathologic records, the support vector machine model performed best (AUC, 0.956; sensitivity, 100%; specificity, 87.5%) and was superior to univariate assessment of tumor budding (AUC, 0.830; sensitivity, 80.9%; specificity, 87.5%, P = .002), DOI (AUC, 0.613; sensitivity, 91.1%; specificity, 31.5%; P < .001), and NLR. CONCLUSIONS: ML shows a better performance in predicting lymph node metastasis of early-stage OTSCC than conventional prediction methods of DOI, NLR, or tumor budding.

Toxicity Assessment of 4 Azo Dyes in Zebrafish Embryos.

Azo dyes are used widely as color additives in food, drugs, and cosmetics; hence, there is an increasing concern about their safety and possible health hazards. In the present study, we chose 4 azo dyes tartrazine, Sunset Yellow, amaranth, and Allura red and evaluated their developmental toxicity on zebrafish embryos. At concentration levels of 5 to 50 mM, we found that azo dyes can induce hatching difficulty and developmental abnormalities such as cardiac edema, decreased heart rate, yolk sac edema, and spinal defects including spinal curvature and tail distortion. Exposure to 100 mM of each azo dye was completely embryolethal. The median lethal concentration (LC50), median effective concentration (EC50), and teratogenic index (TI) were calculated for each azo dye at 72 hours postfertilization. For tartrazine, the LC50 was 47.10 mM and EC50 value was at 42.66 mM with TI ratio of 1.10. For Sunset Yellow, the LC50 was 38.93 mM and EC50 value was at 29.81 mM with TI ratio of 1.31. For amaranth, the LC50 was 39.86 mM and EC50 value was at 31.94 mM with TI ratio of 1.25. For Allura red, the LC50 was 47.42 mM and EC50 value was 40.05 mM with TI ratio of 1.18. This study reports the developmental toxicity of azo dyes in zebrafish embryos at concentrations higher than the expected human exposures from consuming food and drugs containing azo dyes.

Ordered subsets Non-Local means constrained reconstruction for sparse view cone beam CT system.

Sparse-view sampling scans reduce the patient's radiation dose by reducing the total exposure duration. CT reconstructions under such scan mode are often accompanied by severe artifacts due to the high ill-posedness of the problem. In this paper, we use a Non-Local means kernel as a regularization constraint to reconstruct image volumes from sparse-angle sampled cone-beam CT scans. To overcome the huge computational cost of the 3D reconstruction, we propose a sequential update scheme relying on ordered subsets in the image domain. It is shown through experiments on simulated and real data and comparisons with other methods that the proposed approach is robust enough to deal with the number of views reduced up to 1/10. When coupled with a CUDA parallel computing technique, the computation speed of the iterative reconstruction is greatly improved.

[Accuracy of three-dimensional camera system based on stereophotography on photographic acquisition of deformity facial images].

OBJECTIVE: To evaluate and analyze the accuracy of three-dimensional camera system acquisition based on stereophotography for the photographic acquisition of images of facial deformities. METHODS: 3D digital models of 45 waxen facial models of patients with facial deformities were obtained via a 3D camera system based on stereophotography. A total of 19 feature lines were measured on each 3D model by using the software. The measurements taken by the coordinate-measuring machine were accepted as standard values. Statistical analysis was performed to evaluate the accuracy of the system and the corresponding factors. RESULTS: Statistical analysis results showed that the measured values of the characteristic distance obtained by 3D camera system were statistically different from the standard values (P<0.001). Convex deformities had significant influence on the measuring error of 3D camera system (P<0.05), while cleft deformities had no significant influence on the measuring error (P>0.05). The facial regions significantly influenced measuring error (P<0.05). The deformities had no significant influence on the percentage of measurement values (P>0.05). The middle facial regions had significant difference with bilateral facial regions on the percentage of measurement values (P<0.05), while the left and right facial regions had no significant difference (P>0.05). CONCLUSIONS: The accuracy of 3D camera system based on stereophotography for the photographic acquisition of facial deformities are influenced by the morphology of the facial deformities and facial regions. Moreover, the measuring error is acceptable in clinical settings.

Limited-view CT Reconstruction Based on Autoencoder-like Generative Adversarial Networks with Joint Loss.

Limiting the scan views of X-ray computed tomography (CT) can make radiation dose reduced efficiently and consequently weaken the damage of ionizing radiation. However, it will degrade the reconstructed CT images. In this paper, we proposed to predict the missing projections and improve the reconstructed CT images by constructing an autoencoder-like generative adversarial network (GAN) with joint loss function. In the generator network, we train an autoencoder-like convolutional neural network (CNN) to generate the missing projections given a sinogram of the limited-view CT projections. For the discriminator network, a CNN is used to classify an input sinogram as real or synthetic one. To produce more realistic images, the joint loss function which includes not only reconstruction loss, but the adversarial loss is employed. While reconstruction loss can capture the overall structure of the missing projections, the latter can pick a particular mode from the distribution and make the results much sharper. After the missing projections have been estimated, we reconstruct the CT images from the completed projections by utilizing conventional filtered back-projection (FBP) method. The experiments prove the capability of our method to achieve a considerable improvement in limited-view CT reconstruction.

Macrophages mediate corticotomy-accelerated orthodontic tooth movement.

Clinical evidence has suggested that surgical corticotomy of the alveolar bone can accelerate local orthodontic tooth movement (OTM), but the underlying cell and molecular mechanisms remain largely unclear. The present study examined the role of macrophages played in corticotomy-assisted OTM. Orthodontic nickel-titanium springs were applied to the left maxillary first molars of rats or mice to induce OTM with or without corticotomy. Corticotomy enhanced OTM distance by accelerating movement through induction of local osteoclastogenesis and macrophage infiltration during OTM. Further analysis showed that macrophages were polarized toward an M1-like phenotype immediately after corticotomy and then switched to an M2-like phenotype during OTM. The microenvironment of corticotomy induced macrophage infiltration and polarization through the production of TNF-α. More importantly, the amount of OTM induced by corticotomy was significantly decreased after mice were depleted of monocyte/macrophages by injection of liposome-encapsulated clodronate. Further experiments by incubating cultured macrophages with fresh tissue suspension obtained from post-corticotomy gingiva switched the cells to an M1 phenotype through activation of the nuclear factor-κB (NF-κB) signaling pathway, and to an M2 phenotype through activation of the JAK/STAT3 signaling pathway. Our results suggest that corticotomy induces macrophage polarization first by activating the NF-κB signaling pathway and later by activating the JAK/STAT3 signaling pathway, and that these processes contribute to OTM by triggering production of inflammatory cytokines and osteoclastogenesis.

Artifact Removal using Improved GoogLeNet for Sparse-view CT Reconstruction.

Sparse-view Reconstruction can be used to provide accelerated low dose CT imaging with both accelerated scan and reduced projection/back-projection calculation. Despite the rapid developments, image noise and artifacts still remain a major issue in the low dose protocol. In this paper, a deep learning based method named Improved GoogLeNet is proposed to remove streak artifacts due to projection missing in sparse-view CT reconstruction. Residual learning is used in GoogLeNet to study the artifacts of sparse-view CT reconstruction, and then subtracts the artifacts obtained by learning from the sparse reconstructed images, finally recovers a clear correction image. The intensity of reconstruction using the proposed method is very close to the full-view projective reconstructed image. The results indicate that the proposed method is practical and effective for reducing the artifacts and preserving the quality of the reconstructed image.

Discriminative Prior - Prior Image Constrained Compressed Sensing Reconstruction for Low-Dose CT Imaging.

X-ray computed tomography (CT) has been widely used to provide patient-specific anatomical information in the forms of tissue attenuation. However, the cumulative radiation induced in CT scan has raised extensive concerns in recently years. How to maintain reconstruction image quality is a major challenge for low-dose CT (LDCT) imaging. Generally, LDCT imaging can be greatly improved by incorporating prior knowledge in some specific forms. A joint estimation framework termed discriminative prior-prior image constrained compressed sensing (DP-PICCS) reconstruction is proposed in this paper. This DP-PICCS algorithm utilizes discriminative prior knowledge via two feature dictionary constraints which built on atoms from the samples of tissue attenuation feature patches and noise-artifacts residual feature patches, respectively. Also, the prior image construction relies on a discriminative feature representation (DFR) processing by two feature dictionary. Its comparison to other competing methods through experiments on low-dose projections acquired from torso phantom simulation study and clinical abdomen study demonstrated that the DP-PICCS method achieved promising improvement in terms of the effectively-suppressed noise and the well-retained structures.

Effects of nanosilver and nanozinc incorporated mesoporous calcium-silicate nanoparticles on the mechanical properties of dentin.

Mesoporous calcium-silicate nanoparticles (MCSNs) are advanced biomaterials for drug delivery and mineralization induction. They can load silver and exhibit significantly antibacterial effects. However, the effects of MCSNs and silver-loaded MCSNs on dentin are unknown. The silver (Ag) and/or zinc (Zn) incorporated MCSNs (Ag-Zn-MCSNs) were prepared by a template method, and their characterizations were tested. Then the nanoparticles were filled into root canals and their effects on the dentin were investigated. Ag-Zn-MCSNs showed characteristics of mesoporous materials and sustained release of ions over time. Ag-Zn-MCSNs adhered well to the root canal walls and infiltrated into the dentinal tubules after ultrasound activation. Ag-Zn-MCSNs showed no significantly negative effects on either the flexural strength or the modulus of elasticity of dentin, while CH decreased the flexural strength of dentin significantly (P<0.05). These findings suggested that Ag and Zn can be incorporated into MCSNs using a template method, and the Ag-Zn-MCSNs may be developed into a new disinfectant for the root canal and dentinal tubules.

An Effective CUDA Parallelization of Projection in Iterative Tomography Reconstruction.

Projection and back-projection are the most computationally intensive parts in Computed Tomography (CT) reconstruction, and are essential to acceleration of CT reconstruction algorithms. Compared to back-projection, parallelization efficiency in projection is highly limited by racing condition and thread unsynchronization. In this paper, a strategy of Fixed Sampling Number Projection (FSNP) is proposed to ensure the operation synchronization in the ray-driven projection with Graphical Processing Unit (GPU). Texture fetching is also used utilized to further accelerate the interpolations in both projection and back-projection. We validate the performance of this FSNP approach using both simulated and real cone-beam CT data. Experimental results show that compare to the conventional approach, the proposed FSNP method together with texture fetching is 10~16 times faster than the conventional approach based on global memory, and thus leads to more efficient iterative algorithm in CT reconstruction.

Low-dose lung CT processing using weighted intensity averaging over large-scale neighborhoods.

The aim of the proposed work is to improve low-dose lung CT (LDCT) screening using the processing of weighted intensity averaging over large-scale neighborhoods (WIA-LN). Both current and voltage reductions were considered for LDCT imaging. In the WIA-LN method, the processed pixel intensities are calculated by weighted averaging intensities among a large neighboring region. The weights are determined by the inter-similarity of the surrounding textures. A compute unified device architecture based parallelization was applied to accelerate the implementation. To evaluate the effectiveness of the proposed processing, low-dose lung CT images were obtained under both 75 % reduced tube current and 33.3 % reduced tube voltage condition respectively from a 16 detector rows Siemens CT. The standard routine standard-dose CT images were also collected as the reference images. In addition to clinical data from patients, an anthropomorphic lung phantom was also used in the study. Visual comparison and statistical qualitative analysis of image quality scores on the datasets are made in validation. Compared to the original LDCT images, improved visual and qualitative performance can be observed for the processed images. Statistically significant improvement of noise/artifacts suppression and nodule structure enhancement are achieved by using the proposed method (P < 0.05). The proposed method is capable of providing LDCT images under significantly reduced tube current and voltage settings in low-dose condition. Quality of the processed images was assessed by radiology specialists. Parallelization based algorithm optimization was also performed to increase the clinical applicability of the proposed processing.

[Morphology study of mandibular incisive canal in adults based on cone-beam computed tomography].

OBJECTIVE: To investigate the mandibular incisive canal (MIC) with cone-beam computed tomography (CBCT). METHODS: Fifty adults were selected and CBCT was taken. The CBCT data were reconstructed to evaluate the visibility, shape, diameter, length of the MIC and its relationship with mandible. RESULTS: MIC could be identified in 100% (100/100) of CBCT with good clarity in 71% (71/100). The diameters (horizontal diameter versus vertical diameter) of MIC became smaller from origin to end (left origin of MIC was 2.17 mm×2.22 mm, left end was 0.82 mm×0.92 mm; right origin of MIC was 2.14 mm×2.08 mm, right end was 0.87 mm×0.86 mm). The left and right mean length of MIC was 17.84 mm and 17.73 mm respectively. In bucca-lingual direction, MIC was close to buccal cortical border, and in vertical direction, MIC was close to lower margin of mandible. The distance from MIC to apex of root was shortest in canine. CONCLUSIONS: CBCT can identify MIC with high visibility and prominent clarity. In the interforaminal region of mandible, MIC was close to buccal and lower margin of mandible.

A new method to standardize CBCT for quantitative evaluation of alveolar ridge preservation in the mandible: a case report and review of the literature.

Cone-beam computerized tomography (CBCT) is an effective technique for assessment of changes to the alveolar ridge (AR). However, its accuracy and reliability could be improved by standardization of imaging positions to remain unchanged during measurements. In this study, an alveolar ridge preservation procedure was performed on a left third molar (38) socket by filling it with a radiotransparent synthetic bone graft, mineralized collagen (MC). Photographic, X-ray and CBCT images were captured before and 3, 6 and 12 months after surgery. A new method was developed to standardize CBCT for quantitative evaluation. Obtained CBCT images showed good comparability. The post-extraction alveolar width and height were both over 95% of the original values, but some resorption of the lingual bone wall (>50%) and inter-crestal bone (>30%). It is concluded that an effective positional standardization method was developed for CBCT assessment of AR dimensional changes in the posterior mandible. The use of MC in combination with a collagen membrane improved dimensional preservation of the AR.

Mineral trioxide aggregate promotes the odonto/osteogenic differentiation and dentinogenesis of stem cells from apical papilla via nuclear factor kappa B signaling pathway.

INTRODUCTION: Mineral trioxide aggregate (MTA) has been widely used in clinical apexification and apexogenesis. However, the effects of MTA on the stem cells from apical papilla (SCAPs) and the precise mechanism of apexogenesis have not been elucidated in detail. METHODS: Multiple colony-derived stem cells were isolated from the apical papillae, and the effects of MTA on the proliferation and differentiation of SCAPs were investigated both in vitro and in vivo. Activation of nuclear factor kappa B (NFκB) pathway in MTA-treated SCAPs was analyzed by immunofluorescence assay and Western blot. RESULTS: MTA at the concentration of 2 mg/mL did not affect the proliferation activity of SCAPs. However, 2 mg/mL MTA-treated SCAPs presented the ultrastructural changes, up-regulated alkaline phosphatase, increased calcium deposition, up-regulated expression of odontoblast markers (dentin sialoprotein and dentin sialophosphoprotein) and odonto/osteoblast markers (runt-related transcription factor 2 and osteocalcin), suggesting that MTA enhanced the odonto/osteoblastic differentiation of SCAPs in vitro. In vivo results confirmed that MTA can promote the regular dentinogenesis of SCAPs. Moreover, MTA-treated SCAPs exhibited the up-regulated cytoplasmic phos-IκBα and phos-P65, enhanced nuclear P65, and increased nuclear translocation of P65. When co-treated with BMS345541 (the specific NFκB inhibitor), MTA-mediated odonto/osteoblastic differentiation was significantly attenuated. CONCLUSIONS: MTA at the concentration of 2 mg/mL can improve the odonto/osteogenic capacity of SCAPs via the activation of NFκB pathway.

A novel combination of nano-scaffolds with micro-scaffolds to mimic extracellularmatrices improve osteogenesis.

To improve bone engineering for clinical applications, we coupled nanofiber-peptide hydrogel to nano-hydroxyapatite/collagen to form a bioactive scaffold (cnHAC) that mimics extracellular matrices. In comparison to nano-hydroxyapatite/collagen, we found that cnHAC promoted cell adhesion and spreading, and DNA content measurements, alkaline phosphatase activity assays, and reverse transcriptase-polymerase chain reaction analyses of osteogenic gene expression showed that cnHAC significantly improved cellular attachment, proliferation, and osteogenic differentiation in vitro (P < 0.05). In vivo models based on rat calvarial implants showed that cnHAC significantly enhanced bone regeneration (P < 0.05). In conclusion, we demonstrated that novel cnHAC scaffolds could potentially facilitate future bone regenerative medicine.