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Aim: To investigate the association between periodontal diseases, airflow limitation and incident chronic obstructive pulmonary disease (COPD) in a large‐scale prospective UK Biobank cohort. Materials and Methods: Our approach comprised a cross‐sectional study and a prospective cohort. Periodontal diseases were determined based on the participants' self‐reported dental symptoms, including painful gums, bleeding gums and loose teeth. Logistic regression and Cox proportional hazards models were used to evaluate the association of periodontal diseases with airflow limitation and incident COPD in the cross‐sectional study and the prospective cohort, respectively. Results: The cross‐sectional study involved 495,610 participants. Multivariable analysis found that periodontal diseases were significantly associated with airflow limitation (odds ratio = 1.036, 95% confidence interval [CI]: 1.015–1.059). The cohort study included 379,266 participants with a median follow‐up period of 12.68 years. An elevated risk of incident COPD was associated with the presence of periodontal diseases (hazard ratio: 1.248, 95% CI: 1.174–1.326). The effect was consistent among subgroups, including baseline age (≤65 or >65 years), sex, smoking status and diabetes mellitus. Conclusions: Periodontal diseases are associated with airflow limitation and elevated COPD incidence. Maintaining good periodontal health in patients with chronic bronchitis and emphysema may help prevent the onset of COPD. [ABSTRACT FROM AUTHOR]

[Objective] For teaching experiments on the wheelset measurement of rail vehicles, manual measurement is usually conducted with the help of vernier calipers and a fourth type of checker. However, realizing the global dynamic measurement of the tread profile is impossible. Aiming at the issues of low measurement efficiency and poor accuracy in the contact measurement of the wheelset tread surface, this study obtained image information of the wheelset tread surface contour of railroad vehicles using an MV-DP090-02B laser contour sensor. Then, an outlier removal method, composite noise reduction, and feature extraction of three-dimensional (3D) point cloud data were proposed to realize the 3D reconstruction of the tread profile. [Methods] This study designed a measurement experimental device that performs the dynamic measurement of the wheel tread. Then, 3D point cloud data of the tread profile were obtained during low-speed rotation based on the laser triangulation method. Point cloud data processing was conducted in the following manner: 1) Statistical filtering was used to remove the obviously sparsely distributed outliers in the point cloud. 2) Composite filtering was used: median filtering to remove impulses and scanning noise, followed by Gaussian filtering to suppress Gaussian noise. 3) Cubic spline interpolation was used to smooth the pointclouds and restore the tread contour. 4) Geometric features were extracted, and tread contours were reconstructed. [Results] The experimental results showed the following: 1) After obtaining the original point cloud data of the tread profile using the laser profile sensor, the dynamic measurement of the tread profile was realized by combining the outlier rejection and the composite filter noise reduction processing. Compared with the traditional wheelset tread test, the operation was simpler and could be applied to the global measurement of the wheelset tread profile experiment in the course "Mechanical Overhaul of Railway Vehicles." 2) By removing outliers, filtering, and cubic spline interpolation on the original point cloud data obtained from the laser contour sensor and conducting 3D morphological modeling, the true profile of the tread in the entire region could be obtained. 3) The contour data in the dynamic measurement experiment of wheelset tread showed that the maximum relative error of the measurement results obtained using laser contour sensors and related data processing methods did not exceed 5.49%, the average relative error was less than or equal to 2.97%, and the absolute error was less than or equal to 1.01 mm. [Conclusions] The MV-DP090-02B laser profile sensor not only meets the demand of dynamic real-time sweep measurement of wear tread in the experiment but is also easy to operate. The method proposed in this study can greatly improve the measurement accuracy and efficiency and provides a new method of obtaining the tread profile of the wheelset in the experiment of the course "Mechanical Overhaul of Railway Vehicle." [ABSTRACT FROM AUTHOR]