Deep learning-based carotid media-adventitia and lumen-intima boundary segmentation from three-dimensional ultrasound images

Purpose: Quantification of carotid plaques has been shown to be important for assessing as well as monitoring the progression and regression of carotid atherosclerosis. Various metrics have been proposed and methods of measurements ranging from manual tracing to automated segmentations have also been investigated. Of those metrics, quantification of carotid plaques by measuring vessel-wall-volume (VWV) using the segmented media-adventitia (MAB) and lumen-intima (LIB) boundaries has been shown to be sensitive to temporal changes in carotid plaque burden. Thus, semi-automatic MAB and LIB segmentation methods are required to help generate VWV measurements with high accuracy and less user interaction. Methods: In this paper, we propose a semiautomatic segmentation method based on deep learning to segment the MAB and LIB from carotid three-dimensional ultrasound (3DUS) images. For the MAB segmentation, we convert the segmentation problem to a pixel-by-pixel classification problem. A dynamic convolutional neural network (Dynamic CNN) is proposed to classify the patches generated by sliding a window along the norm line of the initial contour where the CNN model is fine-tuned dynamically in each test task. The LIB is segmented by applying a region-of-interest of carotid images to a U-Net model, which allows the network to be trained end-to-end for pixel-wise classification. Results: A total of 144 3DUS images were used in this development, and a threefold cross-validation technique was used for evaluation of the proposed algorithm. The proposed algorithm-generated accuracy was significantly higher than the previous methods but with less user interactions. Comparing the algorithm segmentation results with manual segmentations by an expert showed that the average Dice similarity coefficients (DSC) were 96.46 ± 2.22% and 92.84 ± 4.46% for the MAB and LIB, respectively, while only an average of 34 s (vs 1.13, 2.8 and 4.4 min in previous methods) was required to segment a 3DUS image. The interobserver experiment indicated that the DSC was 96.14 ± 1.87% between algorithm-generated MAB contours of two observers\u27 initialization. Conclusions: Our results showed that the proposed carotid plaque segmentation method obtains high accuracy and repeatability with less user interactions, suggesting that the method could be used in clinical practice to measure VWV and monitor the progression and regression of carotid plaques

Testing model transformation programs using metamorphic testing

Model transformations are crucial for the success of Model Driven Engineering. Testing is a prevailing technique of verifying the correctness of model transformation programs. A major challenge in model transformation testing is the oracle problem, which refers to the difficulty or high cost in determining the correctness of the output models. Metamorphic Testing alleviates the oracle problem by making use of the relationships among the inputs and outputs of multiple executions of the target function. This paper investigates the effectiveness and feasibility of metamorphic testing in testing model transformation programs. Empirical results show that metamorphic testing is an effective testing method for model transformation programs

CRISPR-cas technology: A key approach for SARS-CoV-2 detection

The CRISPR (Clustered Regularly Spaced Short Palindromic Repeats) system was first discovered in prokaryotes as a unique immune mechanism to clear foreign nucleic acids. It has been rapidly and extensively used in basic and applied research owing to its strong ability of gene editing, regulation and detection in eukaryotes. Hererin in this article, we reviewed the biology, mechanisms and relevance of CRISPR-Cas technology and its applications in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) diagnosis. CRISPR-Cas nucleic acid detection tools include CRISPR-Cas9, CRISPR-Cas12, CRISPR-Cas13, CRISPR-Cas14, CRISPR nucleic acid amplification detection technology, and CRISPR colorimetric readout detection system. The above CRISPR technologies have been applied to the nucleic acid detection, including SARS-CoV-2 detection. Common nucleic acid detection based on CRISPR derivation technology include SHERLOCK, DETECTR, and STOPCovid. CRISPR-Cas biosensing technology has been widely applied to point-of-care testing (POCT) by targeting recognition of both DNA molecules and RNA Molecules

Taking the pulse of COVID-19: A spatiotemporal perspective

The sudden outbreak of the Coronavirus disease (COVID-19) swept across the world in early 2020, triggering the lockdowns of several billion people across many countries, including China, Spain, India, the U.K., Italy, France, Germany, and most states of the U.S. The transmission of the virus accelerated rapidly with the most confirmed cases in the U.S., and New York City became an epicenter of the pandemic by the end of March. In response to this national and global emergency, the NSF Spatiotemporal Innovation Center brought together a taskforce of international researchers and assembled implemented strategies to rapidly respond to this crisis, for supporting research, saving lives, and protecting the health of global citizens. This perspective paper presents our collective view on the global health emergency and our effort in collecting, analyzing, and sharing relevant data on global policy and government responses, geospatial indicators of the outbreak and evolving forecasts; in developing research capabilities and mitigation measures with global scientists, promoting collaborative research on outbreak dynamics, and reflecting on the dynamic responses from human societies.Comment: 27 pages, 18 figures. International Journal of Digital Earth (2020

AST1306, A Novel Irreversible Inhibitor of the Epidermal Growth Factor Receptor 1 and 2, Exhibits Antitumor Activity Both In Vitro and In Vivo

Despite the initial response to the reversible, ATP-competitive quinazoline inhibitors that target ErbB-family, such a subset of cancer patients almost invariably develop resistance. Recent studies have provided compelling evidence that irreversible ErbB inhibitors have the potential to override this resistance. Here, we found that AST1306, a novel anilino-quinazoline compound, inhibited the enzymatic activities of wild-type epidermal growth factor receptor (EGFR) and ErbB2 as well as EGFR resistant mutant in both cell-free and cell-based systems. Importantly, AST1306 functions as an irreversible inhibitor, most likely through covalent interaction with Cys797 and Cys805 in the catalytic domains of EGFR and ErbB2, respectively. Further studies showed that AST1306 inactivated pathways downstream of these receptors and thereby inhibited the proliferation of a panel of cancer cell lines. Although the activities of EGFR and ErbB2 were similarly sensitive to AST1306, ErbB2-overexpressing cell lines consistently exhibited more sensitivity to AST1306 antiproliferative effects. Consistent with this, knockdown of ErbB2, but not EGFR, decreased the sensitivity of SK-OV-3 cells to AST1306. In vivo, AST1306 potently suppressed tumor growth in ErbB2-overexpressing adenocarcinoma xenograft and FVB-2/Nneu transgenic breast cancer mouse models, but weakly inhibited the growth of EGFR-overexpressing tumor xenografts. Tumor growth inhibition induced by a single dose of AST1306 in the SK-OV-3 xenograft model was accompanied by a rapid (within 2 h) and sustained (≥24 h) inhibition of both EGFR and ErbB2, consistent with an irreversible inhibition mechanism. Taken together, these results establish AST1306 as a selective, irreversible ErbB2 and EGFR inhibitor whose growth-inhibitory effects are more potent in ErbB2-overexpressing cells

MEIS2C and MEIS2D promote tumor progression via Wnt/β-catenin and hippo/YAP signaling in hepatocellular carcinoma

Abstract Background MEIS2 has been identified as one of the key transcription factors in the gene regulatory network in the development and pathogenesis of human cancers. Our study aims to identify the regulatory mechanisms of MEIS2 in hepatocellular carcinoma (HCC), which could be targeted to develop new therapeutic strategies. Methods The variation of MEIS2 levels were assayed in a cohort of HCC patients. The proliferation, clone-formation, migration, and invasion abilities of HCC cells were measured to analyze the effects of MEIS2C and MEIS2D (MEIS2C/D) knockdown with small hairpin RNAs in vitro and in vivo. Chromatin immunoprecipitation (ChIP) was performed to identify MEIS2 binding site. Immunoprecipitation and immunofluorescence assays were employed to detect proteins regulated by MEIS2. Results The expression of MEIS2C/D was increased in the HCC specimens when compared with the adjacent noncancerous liver (ANL) tissues. Moreover, MEIS2C/D expression negatively correlated with the prognosis of HCC patients. On the other hand, knockdown of MEIS2C/D could inhibit proliferation and diminish migration and invasion of hepatoma cells in vitro and in vivo. Mechanistically, MESI2C activated Wnt/β-catenin pathway in cooperation with Parafibromin (CDC73), while MEIS2D suppressed Hippo pathway by promoting YAP nuclear translocation via miR-1307-3p/LATS1 axis. Notably, CDC73 could directly either interact with MEIS2C/β-catenin or MEIS2D/YAP complex, depending on its tyrosine-phosphorylation status. Conclusions Our studies indicate that MEISC/D promote HCC development via Wnt/β-catenin and Hippo/YAP signaling pathways, highlighting the complex molecular network of MEIS2C/D in HCC pathogenesis. These results suggest that MEISC/D may serve as a potential novel therapeutic target for HCC.https://deepblue.lib.umich.edu/bitstream/2027.42/152244/1/13046_2019_Article_1417.pd