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Objective:To construct a polygenic risk score (PRS) for stroke and evaluate its utility in risk stratification and primary prevention for stroke.Methods:Using meta-analytic approach and large genome-wide association results for stroke and stroke-related traits in East Asians, we generated a combined PRS (metaPRS) by incorporating 534 genetic variants in a training set of 2,872 patients with stroke and 2,494 controls. We then validated its association with incident stroke using Cox regression models in large Chinese population-based prospective cohorts comprising 41,006 individuals.Results:During a total of 367,750 person-years (mean follow-up 9.0 years), 1,227 participants developed stroke before age of 80 years. Individuals with high polygenic risk had an about 2-fold higher risk of incident stroke compared with those with low polygenic risk (HR: 1.99, 95% CI: 1.66-2.38), with the lifetime risk of stroke being 25.2% (95% CI: 22.5%-27.7%) and 13.6% (95% CI: 11.6%-15.5%), respectively. Individuals with both high polygenic risk and family history displayed the lifetime risk as high as 41.1% (95% CI: 31.4%-49.5%). Moreover, individuals with high polygenic risk achieved greater benefits in terms of absolute risk reductions from adherence to ideal fasting blood glucose and total cholesterol than those with low polygenic risk. Maintaining favorable cardiovascular health (CVH) profile could substantially mitigate the increased risk conferred by high polygenic risk to the level of the low polygenic risk (from 34.6 % to 13.2%).Conclusions:Our metaPRS has great potential for risk stratification of stroke and identification of individuals who may benefit more from maintaining ideal CVH.Classification of Evidence:This study provides Class I evidence that a meta-polygenic risk score is predictive of stroke risk.

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According to the grasping damage of apple during the process of robot picking apple, the variation of interior tensions inside the apple skin in the grasping process of apple with different type finger of robot end‐effector is researched. The finite element model for apple is established by ANSYS. Some simulations for the grasping process of apple with plane and arc‐shaped finger are carried out. The Von Mises stress nephograms of apple different tissue under different load force by different type fingers are obtained. The experimental results show that the apple cortex is more easily to get damaged due to its small failure stress. And the deformation and stress of apple caused by arc‐shaped finger are smaller than by plane finger. At last, the actual experiment for apple grasping damage of end‐effector with arc‐shaped finger validates the reliability of simulated results. The research results demonstrated that the finite element method can make accurate evaluation for apple damage. Practical applications A major problem associated with robot harvesting is the mechanical damage of apple caused by end‐effector of robot. When the apple is grasped by the end‐effector, the mechanical damage is often occurred underneath apple skin thus, which is difficult to find by the naked eye immediately. The results in our paper can accurate evaluation for apple damage and provide a foundational basis to develop an injury‐reduce device of apple harvesting robot.