This study evaluated trabecular patterns in posterior mandible using fractal dimensional analysis (FDA) of orthopantamograph (OPG) images for preimplant bone quality. Retrospective study of 200 OPGs was performed using Image J software that analyzed mesial, distal, and apical regions of teeth 36 and 46. No significant difference was noted between 36 and 46 in mean trabecular intensity and fractal dimension (FD). Males had significantly higher trabeculae intensity in the mesial region of 36 (P = 0.003). Females showed higher FDs in 36 (mesial, distal, apical; P = 0.04, P = 0.01, and P = 0.002) and in 46 distal (P = 0.02). FDA of OPG images is a promising method for evaluating preimplant bone quality variations.
This article gathers a comprehensive experimental dataset to obtain the efficiency of the thermal conductivity of oxide nanoparticles with the variations in particle size, particle volume concentration, and suspension temperature using Machine learning approach. ML algorithms can be explored to design and develop trans-disciplinary predictive or forecasting models to enhance the existing system performances and efficiencies. Because of the efficiency of the proposed model, it provides several applications in various areas in industries, biomedical, etc. The present investigation is expected to be a Gradient Boosting Regression (GBR), and a new approach that overrides the 'Artificial Neural Network' (ANN). It is presented by considering a data set of 240 using the Koo-Kleinsture-Li (KKL) model conductivity of Al2O3 and CuO-water-based nanofluids. Further, the computation of 'Mean Absolute Error' (MAE), 'Root Mean Squared Error' (RMSE), and the 'Coefficient of Determination' (COD) is obtained and compared with five different approaches that validate the performances of the present technique. It is concluded that the GBR Model is proven as one of the powerful promising approaches over the other approaches used for the predictive enhancements in the performances of several inputs.
Vasculogenic mimicry (VM) refers to the ability of malignant cells to form microvascular channels, having nature of blood vessels but are not endothelium lined. These channels contain blood cells & plasma and provide sufficient nutrient supply to the cancerous cells to meet their metabolic demands. VM can be seen in various tumors and is associated with their malignant phenotype, high tumor grade, invasion, metastasis and poor clinical outcome. In this paper, we made an attempt to explain the mechanism, visualisation and prognostic significance of vasculogenic mimicry.
Background:The sealing ability of different liners under composite restorations in the reduction of microleakage.Aim:To evaluate the effects of three different liners in sandwich techniques on gingival microleakage of class II composite restorations.Materials and Methods:Standardized Class II box cavities were prepared on forty premolar teeth and randomly divided into four groups, n = 10: Group A, no liner (control); Group B, Polofil NHT Flow; Group C, Ionolux; and Group D, Fuji VII. The etching, bonding, and process for restoring the whole remaining mass of the cavities with G-aenial composite were the same, with the sandwich material expectations. Dye penetration was evaluated using a stereomicroscope.Statistical Analysis:Duncan's Post hoc analysis and Friedman's test.Results:Group A showed the highest microleakage followed by Group D, Group C, and Group B.Conclusion:Polofil NHT Flow seems to be a promising liner for gingivally deep class II cavities.
