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

Improving the Brain-Computer Interface Learning Process with Gamification in Motor Imagery: A Review

Brain-computer-interface-based motor imagery (MI-BCI), a control method for transferring the imagination of motor behavior to computer-based commands, could positively impact neural functions. With the safety guaranteed by non-invasive BCI devices, this method has the potential to enhance rehabilitation and physical outcomes. Therefore, this MI-BCI control strategy has been highly researched. However, applying a non-invasive MI-BCI to real life is still not ideal. One of the main reasons is the monotonous training procedure. Although researchers have reviewed optimized signal processing methods, no suggestion is found in training feedback design. The authors believe that enhancing the engagement interface via gamification presents a potential method that could increase the MI-BCI outcome. After analyzing 2524 articles (from 2001 to 2020), 28 pieces of research are finally used to evaluate the feasibility of using gamified MI-BCI system for training. This paper claims that gamification is feasible for MI-BCI training with an average accuracy of 74.35% among 111 individuals and positive reports from 26 out of 28 studies. Furthermore, this literature review suggests more emphasis should be on immersive and humanoid design for a gaming system, which could support relieving distraction, stimulate correct MI and improve learning outcomes. Interruptive training issues such as disturbing graphical interface design and potential solutions have also been presented for further research

GeodesicEmbedding (GE): a high-dimensional embedding approach for fast geodesic distance queries

In this paper, we develop a novel method for fast geodesic distance queries. The key idea is to embed the mesh into a high-dimensional space, such that the Euclidean distance in the high-dimensional space can induce the geodesic distance in the original manifold surface. However, directly solving the high-dimensional embedding problem is not feasible due to the large number of variables and the fact that the embedding problem is highly nonlinear. We overcome the challenges with two novel ideas. First, instead of taking all vertices as variables, we embed only the saddle vertices, which greatly reduces the problem complexity. We then compute a local embedding for each non-saddle vertex. Second, to reduce the large approximation error resulting from the purely Euclidean embedding, we propose a cascaded optimization approach that repeatedly introduces additional embedding coordinates with a non-Euclidean function to reduce the approximation residual. Using the precomputation data, our approach can determine the geodesic distance between any two vertices in near-constant time. Computational testing results show that our method is more desirable than previous geodesic distance queries methods

Corrigendum: Inhibition of O-GlcNAc transferase sensitizes prostate cancer cells to docetaxel

The expression of O-GlcNAc transferase (OGT) and its catalytic product, O-GlcNAcylation (O-GlcNAc), are elevated in many types of cancers, including prostate cancer (PC). Inhibition of OGT serves as a potential strategy for PC treatment alone or combinational therapy. PC is the second common cancer type in male worldwide, for which chemotherapy is still the first-line treatment. However, the function of inhibition of OGT on chemotherapeutic response in PC cells is still unknown. In this study, we show that inhibition of OGT by genetic knockdown using shRNA or by chemical inhibition using OGT inhibitors sensitize PC cells to docetaxel, which is the most common chemotherapeutic agent in PC chemotherapy. Furthermore, we identified that microRNA-140 (miR-140) directly binds to OGT mRNA 3′ untranslated region and inhibits OGT expression. Moreover, docetaxel treatment stimulates miR-140 expression, whereas represses OGT expression in PC cells. Overexpression of miR-140 enhanced the drug sensitivity of PC cells to docetaxel, which could be reversed by overexpression of OGT. Overall, this study demonstrates miR-140/OGT axis as therapeutic target in PC treatment and provides a promising adjuvant therapeutic strategy for PC therapy

Mature cystic extragonadal teratoma in Douglas’ pouch: Case report and literature review

Teratomas often occur in the gonads, while Extragonadal mature cystic teratomas are reported occasionally, with the most common site being the omentum. Teratoma in the Douglas sac is extremely rare. we report a rare case of mature cystic Teratoma in the Douglas sac in a 71-year-old woman who underwent laparoscopic surgery. A cyst with a diameter of approximately 6 cm from Douglas was found during surgery, and the mass was separated from both ovaries. Microscopically, the cyst was a mature cystic teratoma that did not originate from the ovary

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

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data