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Polycystic ovary syndrome (PCOS) and periodontal disease (PDD) share common risk factors. The bidirectional interaction between PCOS and PDD has been reported, but until now, the underlying molecular mechanisms remain unclear. Endocrine disorders including hyperandrogenism (HA) and insulin resistance (IR) in PCOS disturb the oral microbial composition and increase the abundance of periodontal pathogens. Additionally, PCOS has a detrimental effect on the periodontal supportive tissues, including gingiva, periodontal ligament, and alveolar bone. Systemic low-grade inflammation status, especially obesity, persistent immune imbalance, and oxidative stress induced by PCOS exacerbate the progression of PDD. Simultaneously, PDD might increase the risk of PCOS through disturbing the gut microbiota composition and inducing low-grade inflammation and oxidative stress. In addition, genetic or epigenetic predisposition and lower socioeconomic status are the common risk factors for both diseases. In this review, we will present the latest evidence of the bidirectional association between PCOS and PDD from epidemiological, mechanistic, and interventional studies. A deep understanding on their bidirectional association will be beneficial to provide novel strategies for the treatment of PCOS and PDD.

In order to improve the quality of the bionic robot vision tracking, the new automatic tracking algorithm system is proposed in this paper. Based on the completed system hardware design and implementing scheme, the scene noise is removed by adaptive wiener filtering. Through the improved sequential particle filter algorithm, the dynamic target tracking is realized. The experiment result shows that the improved algorithm system still can lock the dynamic target accurately under the condition of that the outer contour of target changing and the partial occlusion existing.

Aiming at completing search task under disaster condition problems, an optimizing strategy based on multi-sensor information fusion is proposed in this paper. Firstly, search and rescue robot control system hardware circuit is designed; secondly, embedded system software design is realized; and then, a polymerization Kalman filtering model is proposed, it uses local Kalman filter weights scheduling principle to improve system fault-tolerant ability and overall fusion performance. What’s more, Adaboost algorithm realizes the multi-sensor information optimal fusion. Through simulation test experiment, the robot search traversal ability is verified under unstructured environment

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