76 research outputs found

    Development of pre and post-operative models to predict early recurrence of hepatocellular carcinoma after surgical resection

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    Background & Aims Resection is the most widely used potentially curative treatment for patients with early hepatocellular carcinoma (HCC). However, recurrence within 2 years occurs in 30–50% of patients, being the major cause of mortality. Herein, we describe 2 models, both based on widely available clinical data, which permit risk of early recurrence to be assessed before and after resection. Methods A total of 3,903 patients undergoing surgical resection with curative intent were recruited from 6 different centres. We built 2 models for early recurrence, 1 using preoperative and 1 using pre and post-operative data, which were internally validated in the Hong Kong cohort. The models were then externally validated in European, Chinese and US cohorts. We developed 2 online calculators to permit easy clinical application. Results Multivariable analysis identified male gender, large tumour size, multinodular tumour, high albumin-bilirubin (ALBI) grade and high serum alpha-fetoprotein as the key parameters related to early recurrence. Using these variables, a preoperative model (ERASL-pre) gave 3 risk strata for recurrence-free survival (RFS) in the entire cohort – low risk: 2-year RFS 64.8%, intermediate risk: 2-year RFS 42.5% and high risk: 2-year RFS 20.7%. Median survival in each stratum was similar between centres and the discrimination between the 3 strata was enhanced in the post-operative model (ERASL-post) which included 'microvascular invasion'. Conclusions Statistical models that can predict the risk of early HCC recurrence after resection have been developed, extensively validated and shown to be applicable in the international setting. Such models will be valuable in guiding surveillance follow-up and in the design of post-resection adjuvant therapy trials. Lay summary The most effective treatment of hepatocellular carcinoma is surgical removal of the tumour but there is often recurrence. In this large international study, we develop a statistical method that allows clinicians to estimate the risk of recurrence in an individual patient. This facility enhances communication with the patient about the likely success of the treatment and will help in designing clinical trials that aim to find drugs that decrease the risk of recurrence

    Patterns of co-morbidity with anxiety disorders in Chinese women with recurrent major depression

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    BACKGROUND: Studies conducted in Europe and the USA have shown that co-morbidity between major depressive disorder (MDD) and anxiety disorders is associated with various MDD-related features, including clinical symptoms, degree of familial aggregation and socio-economic status. However, few studies have investigated whether these patterns of association vary across different co-morbid anxiety disorders. Here, using a large cohort of Chinese women with recurrent MDD, we examine the prevalence and associated clinical features of co-morbid anxiety disorders. METHOD: A total of 1970 female Chinese MDD patients with or without seven co-morbid anxiety disorders [including generalized anxiety disorder (GAD), panic disorder, and five phobia subtypes] were ascertained in the CONVERGE study. Generalized linear models were used to model association between co-morbid anxiety disorders and various MDD features. RESULTS: The lifetime prevalence rate for any type of co-morbid anxiety disorder is 60.2%. Panic and social phobia significantly predict an increased family history of MDD. GAD and animal phobia predict an earlier onset of MDD and a higher number of MDD episodes, respectively. Panic and GAD predict a higher number of DSM-IV diagnostic criteria. GAD and blood-injury phobia are both significantly associated with suicidal attempt with opposite effects. All seven co-morbid anxiety disorders predict higher neuroticism. CONCLUSIONS: Patterns of co-morbidity between MDD and anxiety are consistent with findings from the US and European studies; the seven co-morbid anxiety disorders are heterogeneous when tested for association with various MDD features

    AAV-Mediated Cone Rescue in a Naturally Occurring Mouse Model of CNGA3-Achromatopsia

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    Achromatopsia is a rare autosomal recessive disorder which shows color blindness, severely impaired visual acuity, and extreme sensitivity to bright light. Mutations in the alpha subunits of the cone cyclic nucleotide-gated channels (CNGA3) are responsible for about 1/4 of achromatopsia in the U.S. and Europe. Here, we test whether gene replacement therapy using an AAV5 vector could restore cone-mediated function and arrest cone degeneration in the cpfl5 mouse, a naturally occurring mouse model of achromatopsia with a CNGA3 mutation. We show that gene therapy leads to significant rescue of cone-mediated ERGs, normal visual acuities and contrast sensitivities. Normal expression and outer segment localization of both M- and S-opsins were maintained in treated retinas. The therapeutic effect of treatment lasted for at least 5 months post-injection. This study is the first demonstration of substantial, relatively long-term restoration of cone-mediated light responsiveness and visual behavior in a naturally occurring mouse model of CNGA3 achromatopsia. The results provide the foundation for development of an AAV5-based gene therapy trial for human CNGA3 achromatopsia

    A Novel Kinematic Parameters Identification Method for Articulated Arm Coordinate Measuring Machines Using Repeatability and Scaling Factor

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    Kinematic parameters identification and compensation are effective ways to improve the accuracy of articulated arm coordinate measuring machines (AACMMs) and robotic arms without increasing the cost of hardware. Generally, kinematic parameters identification methods based on standard references are relatively high in accuracy but time-consuming and not suitable for industrial sites, while kinematic parameters identification methods based on repeatability are flexible and easy to implement but lack reliability in accuracy. A novel kinematic parameters identification method for AACMMs using repeatability and scaling factor is proposed in this paper, which combines the advantages of methods based on both standard references and repeatability. Through theoretical analysis and numerical simulations, we found that the commonly used single-point-repeatability-based identification method has problems in identifying the length parameters, which is due to that high repeatability cannot guarantee the accuracy of the kinematic parameters and the measurement accuracy of the AACMM. Further analysis showed that the error of the length parameters is determined by a scaling factor which can be used to remove the error of length parameters. Therefore, a two-step novel kinematic parameters identification method for the AACMMs using repeatability and scaling factor was proposed to get accurate parameters with convenient operation. Experimental studies showed the effectiveness of the proposed identification method, which indicated that 93% more error in spatial length can be decreased comparing to the traditional method of repeatability-based identification

    Research on Melt Wettability Measurements Under Microgravity

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    Wetting and the interaction between liquid and solid phases are significantly affected by gravity. In recent years, Chinese scientists have carried out wettability experiments in space, but the limitations of experimental facilities have hindered their ability to carry out in-situ observations of the dynamic process of wettability in space. The future Chinese space station will provide a platform for real-time observation of the melt wettability in space. To study the wettability of melt under microgravity, a research method for real-time observation on orbit is proposed. The change in the image contour is determined on the basis of Hu moments, according to changes in the image, to control the acquisition frame rate. This can greatly reduce the memory required to store the images. At the same time, the proposed method uses the binarization method to process the images, and then performs target searching and positioning. Furthermore, it uses the Canny multi-level edge detection operator to extract the target contour. The Young-Laplace equation is used to fit the contour of the droplet. Finally, it obtains the surface tension and contact angle of the melt droplet in real time. The experimental results show that the data storage capacity can be reduced by 90% nearly using this method, and the change in the contact angle and surface tension in the melting process can be obtained in real time

    A Novel Approach for Detecting Rotational Angles of a Precision Spherical Joint Based on a Capacitive Sensor

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    Precision spherical joints are commonly employed as multiple degree-of-freedom (DOF) mechanical hinges in many engineering applications, e.g., robots and parallel manipulators. Real-time and precise measurement of the rotational angles of spherical joints is not only beneficial to the real-time and closed-loop control of mechanical transmission systems, but also is of great significance in the prediction and compensation of their motion errors. This work presents a novel approach for rotational angle measurement of spherical joints with a capacitive sensor. First, the 3-DOF angular motions of a spherical joint were analyzed. Then, the structure of the proposed capacitive sensor was presented, and the mathematical model for the rotational angles of a spherical joint and the capacitance of the capacitors was deduced. Finally, the capacitance values of the capacitors at different rotations were simulated using Ansoft Maxwell software. The simulation results show that the variation in the simulated capacitance values of the capacitors is similar to that of the theoretical values, suggesting the feasibility and effectiveness of the proposed capacitive detection method for rotational angles of spherical joints

    A Novel Method for the Micro-Clearance Measurement of a Precision Spherical Joint Based on a Spherical Differential Capacitive Sensor

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    A spherical joint is a commonly used mechanical hinge with the advantages of compact structure and good flexibility, and it becomes a key component in many types of equipment, such as parallel mechanisms, industrial robots, and automobiles. Real-time detection of a precision spherical joint clearance is of great significance in analyzing the motion errors of mechanical systems and improving the transmission accuracy. This paper presents a novel method for the micro-clearance measurement with a spherical differential capacitive sensor (SDCS). First, the structure and layout of the spherical capacitive plates were designed according to the measuring principle of capacitive sensors with spacing variation. Then, the mathematical model for the spatial eccentric displacements of the ball and the differential capacitance was established. In addition, equipotential guard rings were used to attenuate the fringe effect on the measurement accuracy. Finally, a simulation with Ansoft Maxwell software was carried out to calculate the capacitance values of the spherical capacitors at different eccentric displacements. Simulation results indicated that the proposed method based on SDCS was feasible and effective for the micro-clearance measurement of the precision spherical joints with small eccentricity

    Progress and Perspective of CRISPR‐Cas9 Technology in Translational Medicine

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    Abstract Translational medicine aims to improve human health by exploring potential treatment methods developed during basic scientific research and applying them to the treatment of patients in clinical settings. The advanced perceptions of gene functions have remarkably revolutionized clinical treatment strategies for target agents. However, the progress in gene editing therapy has been hindered due to the severe off‐target effects and limited editing sites. Fortunately, the development in the clustered regularly interspaced short palindromic repeats associated protein 9 (CRISPR‐Cas9) system has renewed hope for gene therapy field. The CRISPR‐Cas9 system can fulfill various simple or complex purposes, including gene knockout, knock‐in, activation, interference, base editing, and sequence detection. Accordingly, the CRISPR‐Cas9 system is adaptable to translational medicine, which calls for the alteration of genomic sequences. This review aims to present the latest CRISPR‐Cas9 technology achievements and prospect to translational medicine advances. The principle and characterization of the CRISPR‐Cas9 system are firstly introduced. The authors then focus on recent pre‐clinical and clinical research directions, including the construction of disease models, disease‐related gene screening and regulation, and disease treatment and diagnosis for multiple refractory diseases. Finally, some clinical challenges including off‐target effects, in vivo vectors, and ethical problems, and future perspective are also discussed
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