Publications by authors named "Shuyi Shao"

Objective: In observational studies, polycystic ovary syndrome (PCOS) has been associated with an increased risk of hypertensive disorders of pregnancy (HDPs); however, the causality between these conditions remains to be determined. This study aimed to investigate the causal relationship between PCOS and HDPs.

Methods: This genome-wide association study (GWAS), conducted from November to December 2023, aimed to investigate the causal relationships between PCOS and HDPs, gestational hypertension and preeclampsia/eclampsia via two-sample Mendelian randomization (MR) analysis.

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Background: CircRNA-encoded proteins (CEPs) are emerging as new players in health and disease, and function as baits for the common partners of their cognate linear-spliced RNA encoded proteins (LEPs). However, their prevalence across human tissues and biological roles remain largely unexplored. The placenta is an ideal model for identifying CEPs due to its considerable protein diversity that is required to sustain fetal development during pregnancy.

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Background: Unhealthy sleep patterns are common during pregnancy and have been associated with an increased risk of developing hypertensive disorders of pregnancy (HDPs) in observational studies. However, the causality underlying these associations remains uncertain. This study aimed to evaluate the potential causal association between seven sleep traits and the risk of HDPs using a two-sample Mendelian randomization study.

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Background: The Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome is a rare condition with significant psychological implications. However, our understanding of its impact on postoperative sexual function and mental health is still limited.

Aim: Evaluate the mental health status and sexual functioning of women with MRKH syndrome after vaginoplasty surgery.

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Article Synopsis
  • The article presents an adaptive neural tracking control method for complex multi-input multi-output nonlinear systems, focusing on uncertainties and time-varying constraints.
  • It employs neural networks to approximate uncertainties and introduces a saturation disturbance observer (SDO) to reduce estimation errors compared to traditional methods.
  • The method includes three layers of constraints (prescribed performance functions, actual constraints, and virtual constraints) to ensure performance while addressing challenges like the "explosion of complexity" and singularity issues, demonstrated through a numerical simulation for unmanned aerial vehicle flight control.
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In this article, an event-triggered (ET) fractional-order adaptive tracking control scheme (ATCS) is studied for the uncertain nonlinear system with the output saturation and the external disturbances by using the nonlinear disturbance observer (NDO) and the neural networks (NNs). Based on NNs, the system uncertainties are approximated. An NN-based NDO is designed to estimate the bounded disturbances.

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In this article, an adaptive neural network (NN) tracking control scheme is proposed for uncertain multi-input-multi-output (MIMO) nonlinear system in strict-feedback form subject to system uncertainties, time-varying state constraints, and bounded disturbances. The radial basis function NNs (RBFNNs) are adopted to approximate the system uncertainties. By constructing the intermediate variables, the external disturbances that cannot be directly measured are approximated by the disturbance observers.

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Introduction And Hypothesis: The negative psychological impact on women with Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome is long-lasting, resulting from not only the disease itself, but also the cumbersome and painful treatment process. However, little is known about the postoperative psychological status of these patients and related interventions to improve mental health. Here, in our study, we postulated that mental disorders exist in MRKH patients with a surgical neovagina and that psychological intervention will be helpful.

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Declining female fertility has become a global health concern. It results partially from an abnormal circadian clock caused by unhealthy diet and sleep habits in modern life. The circadian clock system is a hierarchical network consisting of central and peripheral clocks.

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This paper studies the adaptive neural control (ANC)-based tracking problem for discrete-time nonlinear dynamics of an unmanned aerial vehicle subject to system uncertainties, bounded time-varying disturbances, and input saturation by using a discrete-time disturbance observer (DTDO). Based on the approximation approach of neural network, system uncertainties are tackled approximately. To restrain the negative effects of bounded disturbances, a nonlinear DTDO is designed.

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This paper studies the problem of prescribed performance adaptive neural control for a class of uncertain multi-input and multi-output (MIMO) nonlinear systems in the presence of external disturbances and input saturation based on a disturbance observer. The system uncertainties are tackled by neural network (NN) approximation. To handle unknown disturbances, a Nussbaum disturbance observer is presented.

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