A Mendelian randomization study between chronic periodontitis and non-alcoholic fatty liver disease.

BACKGROUND AND OBJECTIVE: Observational studies have suggested a potential association between non-alcoholic fatty liver disease (NAFLD) and chronic periodontitis (CP). However, these studies are prone to confounding factors. The aim of this study was to assess the causal relationship between NAFLD and CP using a two-sample bidirectional Mendelian randomization (MR) analysis method. METHODS: Datasets of CP and NAFLD were retrieved from the European database, and instrumental variables (IVs) related to exposure were selected for the MR analysis. Sensitivity tests, including heterogeneity and horizontal pleiotropy tests, were conducted to ensure the consistency of the selected IVs, following which the analysis results were visualized. RESULTS: Genetic variants associated with CP and NAFLD were identified as IVs, and the MR assessment was performed using the summary data (CP: 3046 cases and 195 395 controls; NAFLD: 894 cases and 217 898 controls). CP increased the risk of NAFLD (inverse variance weighted [IVW], b = 0.132 > 0, p = .006 < .05), whereas the reverse was not observed (IVW, b = -0.024 < 0, p = .081 > .05). The sensitivity analysis indicated no heterogeneity or horizontal pleiotropy. CONCLUSION: The MR analysis suggested that CP could increase the risk of NAFLD among European populations.

Evaluation Algorithm of Root Canal Shape Based on Steklov Spectrum Analysis.

In recent years, we have seen more and more interest in the field of medical images and shape comparison motivated by the latest advances in microcomputed tomography (µCT) acquisition, modelling, and visualization technologies. Usually, biologists need to evaluate the effect of different root canal preparation systems. Current root canal preparation evaluation methods are based on the volume difference, area difference, and transportation of two root canals before and after treatment. The purpose of root canal preparation is to minimize the volume difference and ensure the complete removal of the smear layer. Previous methods can reflect some general geometric differences, but they are not enough to evaluate the quality of root canal shape. To solve this problem, we proposed a novel root canal evaluation method based on spectrum and eigenfunctions of Steklov operators, which can be served as a better alternative to current methods in root canal preparation evaluation. Firstly, the ideal root canal model was simulated according to the root canal model before and after preparation. Secondly, the Steklov spectrum of the two models was calculated. Thirdly, based on the spectrum and the histogram of the Gaussian curvature on the surface, the weight of each eigenvalue was computed. Therefore, the Steklov spectrum distance (SSD), which measures shape difference between the root canals, was defined. Finally, the calculation method that quantifies the root canal preparation effect of root canals was obtained. Through experiments, our method manifested high robustness and accuracy compared with existing state-of-the-art approaches. It also demonstrates the significance of our algorithm's advantages on a variety of challenging root canals through result comparison with counterpart methods.