Design and development of 3D printed shape memory triphasic polymer-ceramic bioactive scaffolds for bone tissue engineering.

Scaffolds for bone tissue engineering require considerable mechanical strength to repair damaged bone defects. In this study, we designed and developed mechanically competent composite shape memory triphasic bone scaffolds using fused filament fabrication (FFF) three dimensional (3D) printing. Wollastonite particles (WP) were incorporated into the poly lactic acid (PLA)/polycaprolactone (PCL) matrix as a reinforcing agent (up to 40 wt%) to harness osteoconductive and load-bearing properties from the 3D printed scaffolds. PCL as a minor phase (20 wt%) was added to enhance the toughening effect and induce the shape memory effect in the triphasic composite scaffolds. The 3D-printed composite scaffolds were studied for morphological, thermal, and mechanical properties, in vitro degradation, biocompatibility, and shape memory behaviour. The composite scaffold had interconnected pores of 550 µm, porosity of more than 50%, and appreciable compressive strength (∼50 MPa), which was over 90% greater than that of the pristine PLA scaffolds. The flexural strength was improved by 140% for 40 wt% of WP loading. The inclusion of WP did not affect the thermal property of the scaffolds; however, the inclusion of PCL reduced the thermal stability. An accelerated in vitro degradation was observed for WP incorporated composite scaffolds compared to pristine PLA scaffolds. The inclusion of WP improved the hydrophilic property of the scaffolds, and the result was significant for 40 wt% WP incorporated composite scaffolds having a water contact angle of 49.61°. The triphasic scaffold exhibited excellent shape recovery properties with a shape recovery ratio of ∼84%. These scaffolds were studied for their protein adsorption, cell proliferation, and bone mineralization potential. The incorporation of WP reduced the protein adsorption capacity of the composite scaffolds. The scaffold did not leach any toxic substance and demonstrated good cell viability, indicating its biocompatibility and growth-promoting behavior. The osteogenic potential of the WP incorporated scaffolds was observed in MC3T3-E1 cells, revealing early mineralization in pre-osteoblast cells cultured in different WP incorporated composite scaffolds. These results suggest that 3D-printed WP reinforced PLA/PCL composite bioactive scaffolds are promising for load bearing bone defect repair.

Health prediction of reciprocating endodontic instrument based on the machine learning and exponential degradation models.

This study proposes an intelligent health prediction and fault prognosis of the endodontic file during the root canal treatment. Root canal treatment is the procedure of disinfecting the infected pulp through the canal with the help of an endodontic instrument. Force signals are acquired with the help of a dynamometer during the canal preparation, and statistical features are extracted. The extracted features are selected through the window-wise feature extraction process. Characteristic features for endodontic file prognostics include time-domain features of the signals are evaluated. The extracted feature has inappropriate information, that is, noise between the signals; hence the smoothing of the feature is required at this stage to observe a trend in the signals. Based on the smoothing feature and post-processing of the feature, defined the health index to calculate the health condition of the endodontic instruments. A machine learning algorithm and exponential degradation model are used to predict the health of the endodontic instrument during the root canal treatment. This model is used to forecast the degradation of the endodontic file so that actions can be taken before actual failures happen. The proposed methodology can analyze the failures and micro-crack initiation of the endodontic instruments. Endodontics practitioners can use the machine learning models as well as an exponential model for estimating the health condition of the endodontic instrument. This study may help the clinician to progress the efficiency of the root canal treatment and the competence of the endodontic instruments.

The implication of oversampling on the effectiveness of force signals in the fault detection of endodontic instruments during RCT.

This work provides an innovative endodontic instrument fault detection methodology during root canal treatment (RCT). Sometimes, an endodontic instrument is prone to fracture from the tip, for causes uncertain the dentist's control. A comprehensive assessment and decision support system for an endodontist may avoid several breakages. This research proposes a machine learning and artificial intelligence-based approach that can help to diagnose instrument health. During the RCT, force signals are recorded using a dynamometer. From the acquired signals, statistical features are extracted. Because there are fewer instances of the minority class (i.e. faulty/moderate class), oversampling of datasets is required to avoid bias and overfitting. Therefore, the synthetic minority oversampling technique (SMOTE) is employed to increase the minority class. Further, evaluating the performance using the machine learning techniques, namely Gaussian Naïve Bayes (GNB), quadratic support vector machine (QSVM), fine k-nearest neighbor (FKNN), and ensemble bagged tree (EBT). The EBT model provides excellent performance relative to the GNB, QSVM, and FKNN. Machine learning (ML) algorithms can accurately detect endodontic instruments' faults by monitoring the force signals. The EBT and FKNN classifier is trained exceptionally well with an area under curve values of 1.0 and 0.99 and prediction accuracy of 98.95 and 97.56%, respectively. ML can potentially enhance clinical outcomes, boost learning, decrease process malfunctions, increase treatment efficacy, and enhance instrument performance, contributing to superior RCT processes. This work uses ML methodologies for fault detection of endodontic instruments, providing practitioners with an adequate decision support system.

Preparation of 3D printed calcium sulfate filled PLA scaffolds with improved mechanical and degradation properties.

Scaffold is one of the key components for tissue engineering application. Three-dimensional (3D) printing has given a new avenue to the scaffolds design to closely mimic the real tissue. However, material selection has always been a challenge in adopting 3D printing for scaffolds fabrication, especially for hard tissue. The fused filament fabrication technique is one of the economical 3D printing technology available today, which can efficiently fabricate scaffolds with its key features. In the present study, a hybrid polymer-ceramic scaffold has been prepared by combining the benefit of synthetic biodegradable poly (lactic acid) (PLA) and osteoconductive calcium sulphate (CaS), to harness the advantage of both materials. Composite PLA filament with maximum ceramic loading of 40 wt% was investigated for its printability and subsequently scaffolds were 3D printed. The composite filament was extruded at a temperature of 160 °C at a constant speed with an average diameter of 1.66 ± 0.34 mm. PLA-CaS scaffold with ceramic content of 10%, 20%, and 40% was 3D printed with square pore geometry. The developed scaffolds were characterized for their thermal stability, mechanical, morphological, and geometrical accuracy. The mechanical strength was improved by 29% at 20 wt% of CaS. The porosity was found to be 50-60% with an average pore size of 550 µm with well-interconnected pores. The effect of CaS particles on the degradation behaviour of scaffolds was also assessed over an incubation period of 28 days. The CaS particles acted as porogen and improved the surface chemistry for future cellular activity, while accelerating the degradation rate.

Engineering biomaterials to 3D-print scaffolds for bone regeneration: practical and theoretical consideration.

There are more than 2 million bone grafting procedures performed annually in the US alone. Despite significant efforts, the repair of large segmental bone defects is a substantial clinical challenge which requires bone substitute materials or a bone graft. The available biomaterials lack the adequate mechanical strength to withstand the static and dynamic loads while maintaining sufficient porosity to facilitate cell in-growth and vascularization during bone tissue regeneration. A wide range of advanced biomaterials are being currently designed to mimic the physical as well as the chemical composition of a bone by forming polymer blends, polymer-ceramic and polymer-degradable metal composites. Transforming these novel biomaterials into porous and load-bearing structures via three-dimensional printing (3DP) has emerged as a popular manufacturing technique to develop engineered bone grafts. 3DP has been adopted as a versatile tool to design and develop bone grafts that satisfy porosity and mechanical requirements while having the ability to form grafts of varied shapes and sizes to meet the physiological requirements. In addition to providing surfaces for cell attachment and eventual bone formation, these bone grafts also have to provide physical support during the repair process. Hence, the mechanical competence of the 3D-printed scaffold plays a key role in the success of the implant. In this review, we present various recent strategies that have been utilized to design and develop robust biomaterials that can be deployed for 3D-printing bone substitutes. The article also reviews some of the practical, theoretical and biological considerations adopted in the 3D-structure design and development for bone tissue engineering.

Force and vibration analysis in biomechanical preparation of root canals using reciprocating endodontic file system: In vitro study.

The shaping and cleaning of the root canal are very important in root canal treatment. The excessive force and vibration during biomechanical preparation of the root canal may result in failure of the endodontic file. In this study, force and vibration analysis was carried out during root canal preparation. The samples of human extracted (premolar) teeth were provided by the College of Dental Science and Hospital. Endodontic instruments for reciprocating motion, such as the WaveOne Gold file system, had been used for root canal preparation. Force and vibration signals were recorded by dynamometer and accelerometer, respectively. The acquired signals were denoised using the db4 (SWT denoising 1-D) wavelet. Four levels of decomposition were carried out for each signal. The signal denoising technique was used to remove unwanted noise from the acquired signal. FESEM analysis was used to visualize the levels of severity of endodontic files during the cleaning and shaping of the root canal. In most of the cases, the failure occurred due to the improper use of the root canal instrumentation. The optimum amount of force was used to avoid the file failure and provided the proper instrumentation. The curve fitting regression model was used to find the interdependency between force and vibration.

Force and vibration correlation analysis in the self-adjusting file during root canal shaping: An in-vitro study.

BACKGROUND/PURPOSE: The focus of this study was to find a correlation between the forces and vibrations during root canal shaping. This can be used to predict the fracture of the self-adjusting file (SAF) in root canal shaping. MATERIALS AND METHODS: Forty J-shaped resin blocks were used in this study. Simulated root canals of resin blocks were prepared with the SAF. Force and vibration during root canal shaping were measured by dynamometer and accelerometer respectively. The recorded time domain signal of force and vibration were transformed to frequency domain signals. Frequency domain signals had been used for correlation study between force and vibration amplitude. The root mean square (RMS) value of force and vibration signature for new file and file just before failure were statistically compared using t-test at 95% confidence interval (CI). RESULTS: Vibrations generated during root canal shaping exhibited positive linear correlation (r = 0.9173) with force exerted by the SAF on the root canal. It means vibration has strong correlation with force. The RMS values of force and vibration increase significantly (P < 0.05) just before the fracture. CONCLUSION: From force and vibration analysis of SAF it was concluded that the vibration is well associated with force applied by the SAF on root canal. Therefore, the trend of force variation was reflected in the vibration signature. The sudden increment in vibration was the symptom of bulge formation and the end of useful life of the SAF.