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The prevalence of type II diabetes mellitus (T2DM) in coronary artery disease (CAD) patients has been steadily increasing, especially in East Asian countries. Although many studies have suggested that certain genetic variants may predispose to the development of T2DM, very few studies investigated the genetic link with T2DM in CAD patients of East Asia. In this study, we investigated the relationship between Glu504Lys polymorphism in the acetaldehyde dehydrogenase 2 (ALDH2) gene, a key enzyme of alcohol metabolism, and the risk of having T2DM in Chinese Han CAD patients. We enrolled 542 CAD patients (180 women and 362 men) and 309 CADÀ/DMÀ subjects (152 women and 157 men). T2DM was confirmed in 47.4% of CAD patients. Logistic and linear regression analyses showed that ALDH2 mutant genotypes (*1/*2 and *2/*2) were an independent risk factor for both T2DM in female CAD patients, even after controlling for alcohol consumption (OR¼1.95, P¼0.043), and fasting plasma glucose (FPG) in CADÀ/DMÀ women (P¼0.015), whereas the association with FPG disappeared after controlling for high-sensitivity C-reactive protein, a classic inflammatory biomarker. However, there was no relationship between the ALDH2 genetic polymorphism and T2DM or FPG in men. These findings suggest that the ALDH2 polymorphism is associated with an increased risk of T2DM in female CAD patients, and this association could be causal on the basis of the association between the polymorphism and FPG, which is partly explained by an increased inflammatory status. These findings will benefit the screening and treatment of a high-risk population in East Asians.

Background: Worldwide propagation of minimally invasive surgeries (MIS) is hindered by their drawback of indirect observation and manipulation, while monitoring of surgical instruments moving in the operated body required by surgeons is a challenging problem. Tracking of surgical instruments by vision-based methods is quite lucrative, due to its flexible implementation via software-based control with no need to modify instruments or surgical workflow. Methods: A MIS instrument is conventionally split into a shaft and end-effector portions, while a 2D/3D tracking-by-detection framework is proposed, which performs the shaft tracking followed by the end-effector one. The former portion is described by line features via the RANSAC scheme, while the latter is depicted by special image features based on deep learning through a well-trained convolutional neural network. Results: The method verification in 2D and 3D formulation is performed through the experiments on ex-vivo video sequences, while qualitative validation on in-vivo video sequences is obtained. Conclusion: The proposed method provides robust and accurate tracking, which is confirmed by the experimental results: its 3D performance in ex-vivo video sequences exceeds those of the available state-of -the-art methods. Moreover, the experiments on in-vivo sequences demonstrate that the proposed method can tackle the difficult condition of tracking with unknown camera parameters. Further refinements of the method will refer to the occlusion and multi-instrumental MIS applications.

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Background and purposeThe use of involved field radiotherapy (IFRT) has generated concern about the increasing incidence of elective nodal failure (ENF) in contrast to elective nodal irradiation (ENI). This meta-analysis aimed to provide more reliable and up-to-date evidence on the incidence of ENF between IFRT and ENI.Materials and methodsWe searched three databases for eligible studies where locally advanced non-small cell lung cancer (NSCLC) patients received IFRT or ENI. Outcome of interest was the incidence of ENF. The fixed-effects model was used to pool outcomes across the studies.ResultsThere were 3 RCTs and 3 cohort studies included with low risk of bias. There was no significant difference in incidence of ENF between IFRT and ENI either among RCTs (RR = 1.38, 95 % CI: 0.59–3.25, p = 0.46) or among cohort studies (RR = 0.99, 95 % CI: 0.46–2.10, p = 0.97). There was also no significant difference in incidence of ENF between IFRT and ENI when RCTs and cohort studies were combined (RR = 1.15, 95 % CI: 0.65–2.01, p = 0.64). I2 of test for heterogeneity was 0 %.ConclusionThis meta-analysis provides more reliable and stable evidence that there is no significant difference in incidence of ENF between IFRT and ENI.Electronic supplementary materialThe online version of this article (doi:10.1186/s13014-016-0698-3) contains supplementary material, which is available to authorized users.