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Background and Objective : An anatomical landmark is biologically meaningful point in medical images and often used for medical image registration. The purpose of this study is to automatically locate anatomical landmarks from 3D medical images. Methods : A two-step automatic location scheme of anatomical landmarks in 3D medical image was designed in this study. In the first step, the full convolutional neural network was used for slice detection from a 3D medical image. In the second step, the scale attention hourglass network was used for landmark location in the detected slice and could overcome the difficulty of similar anatomical structures and different image parameters. This method was implemented and tested on four stable anatomical landmarks in 3D head MRI. Results : A total of 500 and 300 3D head volumes were used for training and testing, respectively. Results showed that the slice detection accuracy reached 85.7% and that the maximum location error was less than one slice. The average accuracy of the four anatomical landmarks in the detected slice reached 87.2%, and the spatial distance was 2.4 ± 2.4, which obtained better performance compared with hourglass network and feature pyramid networks. Conclusions : This method can be useful for locating anatomical landmarks in 3D head MRI and provides technical support for medical image registration and big data analysis.

Increasing evidence indicates the dysregulations and pivotal roles of lncRNAs in the development and progression of various cancers, including pancreatic cancer. Enhanced glycolytic flux and epithelial-to-mesenchymal transition (EMT) have been considered as important factors in driving the malignance of pancreatic cancer. Here, we sought to evaluate the biological role and involved mechanism of lncRNA CASC9 (CASC9) in pancreatic cancer. Our present study showed that CASC9 was upregulated in various pancreatic cancer cell lines. Loss- and gain-of function of CASC9 demonstrated its critical roles in promoting the glycolysis and EMT phenotypes of pancreatic cancer. Moreover, knockdown of CASC9 inhibited the tumorigenicity and metastasis in vivo. Additionally, our findings showed that hypoxia induced the expression of CASC9 and enhanced the binding of HIF-1α to its promoter. We also demonstrated that the positive feedback loop of CASC9 and the AKT/HIF-1α signaling cascade partially mediated this biological process. Altogether, our results suggest that CASC9 promotes the glycolysis and EMT of pancreatic cancer by a positive feedback loop with AKT/HIF-1α signaling, which is synergistically enhanced by the tumor hypoxic niche. Our study will provide potential therapeutic targets for treating pancreatic cancer.

This study takes a repertoire-oriented approach to examining how social and traditional media usage affect political engagement in China. Building on previous studies and giving them a new direction, we examine how various social media platforms and traditional media outlets are combined in cross-media repertoires of young Chinese adults. We do this with the help of survey data collected in mainland China. Using the Step-3 approach of latent class analysis, we then consider how these repertoires can be explained by various individual and contextual factors and what impact the repertoires themselves have on various forms of political involvement. The study identifies 6 distinctive media repertoires: digitally focused, communication oriented, minimal users, moderate omnivores, voracious omnivores, and print interested. Repertoires are mainly correlated with age, education, and perceived media credibility. In China, young adults with the most omnivorous and print-oriented media repertoires display the highest levels of political trust, political interest, and online political engagement. The study also discusses the implications of these results.

Additional file 1: Table S1. The related information of herbicides used in the study. Table S2. ANOVA table for two-factor split plot designs.