Physciosporin suppresses the proliferation, motility and tumourigenesis of colorectal cancer cells

Taş,, İ,sa,Han, Jin,Park, So-Yeon,Yang, Yi,Zhou, Rui,Gamage, Chathurika D.B.,Van Nguyen, Tru,Lee, Ji-Yoon,Choi, Yong Jae,Yu, Young Hyun,Moon, Kyung-Sub,Kim, Kyung Keun,Ha, Hyung-Ho,Kim, Sang Elsevier 2019 Phytomedicine Vol.56 No.-

<P><B>Abstract</B></P> <P><B>Background</B></P> <P>Lichens, which represent symbiotic associations of fungi and algae, are potential sources of numerous natural products. Physciosporin (PHY) is a potent secondary metabolite found in lichens and was recently reported to inhibit the motility of lung cancer cells via novel mechanisms.</P> <P><B>Purpose</B></P> <P>The present study investigated the anticancer potential of PHY on colorectal cancer (CRC) cells.</P> <P><B>Methods</B></P> <P>PHY was isolated from lichen extract by preparative TLC. The effect of PHY on cell viability, motility and tumourigenicity was elucidated by MTT assay, hoechst staining, flow cytometric analysis, transwell invasion and migration assay, soft agar colony formation assay, Western blotting, qRT-PCR and PCR array <I>in vitro</I> as well as tumorigenicity study <I>in vivo</I>.</P> <P><B>Results</B></P> <P>PHY decreased the viability of various CRC cell lines (Caco2, CT26, DLD1, HCT116 and SW620). Moreover, PHY elicited cytotoxic effects by inducing apoptosis at toxic concentrations. At non-toxic concentrations, PHY dose-dependently suppressed the invasion, migration and colony formation of CRC cells. PHY inhibited the motility of CRC cells by suppressing epithelial-mesenchymal transition and downregulating actin-based motility markers. In addition, PHY downregulated β-catenin and its downstream target genes cyclin-D1 and c-Myc. Moreover, PHY modulated KAI1 C-terminal-interacting tetraspanin and KAI1 expression, and downregulated the downstream transcription factors c-jun and c-fos. Finally, PHY administration showed considerable bioavailability and effectively decreased the growth of CRC xenografts in mice without causing toxicity.</P> <P><B>Conclusion</B></P> <P>PHY suppresses the growth and motility of CRC cells via novel mechanisms.</P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>

Research on Three-Component Geomagnetic Field Differential Measurement Method for Underwater Vehicle

Zhao Ta,Chen Yu Wei,Zhou Zhi Jian,Cheng De Fu 보안공학연구지원센터 2016 International Journal of Multimedia and Ubiquitous Vol.11 No.2

The precise measurement of the geomagnetic element is the key to realize navigation and positioning with the development of geomagnetic navigation technology. In this paper, a kind of underwater vehicle three-component geomagnetic field differential measurement method is presented based on the ideas of the difference. The threecomponent geomagnetic field mathematical model of traditional measurement method is improved and new differential measurement model(DMM) is established. Difference expressions of measurement magnetic field in the DMM obviously reduce the impact of interference magnetic field in the process of geomagnetic field measurement and improve the measuring precision of the three-component geomagnetic field. Finally, the method’s effectiveness is validated by simulation. The precision of DMM method is 10 ± 5nT which is about two times that of traditional measurement model (TMM) method under the condition of ± 25nT stray outside interference magnetic field. The method effectively improves the geomagnetic field measurement precision and has stronger antiinterference ability. It is of significance for practical application of underwater geomagnetic navigation method.

A Pan-Cancer Analysis of Enhancer Expression in Nearly 9000 Patient Samples

Chen, Han,Li, Chunyan,Peng, Xinxin,Zhou, Zhicheng,Weinstein, John N.,Caesar-Johnson, Samantha J.,Demchok, John A.,Felau, Ina,Kasapi, Melpomeni,Ferguson, Martin L.,Hutter, Carolyn M.,Sofia, Heidi J.,Ta Elsevier 2018 Cell Vol.173 No.2

<P><B>Summary</B></P> <P>The role of enhancers, a key class of non-coding regulatory DNA elements, in cancer development has increasingly been appreciated. Here, we present the detection and characterization of a large number of expressed enhancers in a genome-wide analysis of 8928 tumor samples across 33 cancer types using TCGA RNA-seq data. Compared with matched normal tissues, global enhancer activation was observed in most cancers. Across cancer types, global enhancer activity was positively associated with aneuploidy, but not mutation load, suggesting a hypothesis centered on “chromatin-state” to explain their interplay. Integrating eQTL, mRNA co-expression, and Hi-C data analysis, we developed a computational method to infer causal enhancer-gene interactions, revealing enhancers of clinically actionable genes. Having identified an enhancer ∼140 kb downstream of PD-L1, a major immunotherapy target, we validated it experimentally. This study provides a systematic view of enhancer activity in diverse tumor contexts and suggests the clinical implications of enhancers.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Systematic analysis of enhancer expression across ∼9,000 samples of 33 cancer types </LI> <LI> Global enhancer activation positively correlates with aneuploidy but not mutations </LI> <LI> A computational method that infers causal enhancer-target-gene relationships </LI> <LI> Enhancers as key regulators of therapeutic targets, including PD-L1 </LI> </UL> </P> <P><B>Graphical Abstract</B></P> <P>[DISPLAY OMISSION]</P>

MODIFIED CONVOLUTIONAL NEURAL NETWORK WITH TRANSFER LEARNING FOR SOLAR FLARE PREDICTION

Yanfang Zheng,Xuebao Li,Xinshuo Wang,Ta Zhou 한국천문학회 2019 Journal of The Korean Astronomical Society Vol.52 No.6

We apply a modified Convolutional Neural Network (CNN) model in conjunction with transfer learning to predict whether an active region (AR) would produce a ≥C-class or ≥M-class are within the next 24 hours. We collect line-of-sight magnetogram samples of ARs provided by the SHARP from May 2010 to September 2018, which is a new data product from the HMI onboard the SDO. Based on these AR samples, we adopt the approach of shuffle-and-split cross-validation (CV) to build a database that includes 10 separate data sets. Each of the 10 data sets is segregated by NOAA AR number into a training and a testing data set. After training, validating, and testing our model, we compare the results with previous studies using predictive performance metrics, with a focus on the true skill statistic (TSS). The main results from this study are summarized as follows. First, to the best of our knowledge, this is the first time that the CNN model with transfer learning is used in solar physics to make binary class predictions for both ≥C-class and ≥M-class ares, without manually engineered features extracted from the observational data. Second, our model achieves relatively high scores of TSS = 0.6400.075 and TSS = 0.5260.052 for ≥M-class prediction and ≥C-class prediction, respectively, which is comparable to that of previous models. Third, our model also obtains quite good scores in five other metrics for both ≥C-class and ≥M-class are prediction. Our results demonstrate that our modified CNN model with transfer learning is an effective method for are forecasting with reasonable prediction performance.

GPU-ACCELERATED SPECKLE MASKING RECONSTRUCTION ALGORITHM FOR HIGH-RESOLUTION SOLAR IMAGES

Yanfang Zheng,Xuebao Li,Huifeng Tian,Qiliang Zhang,Chong Su,Lingyi Shi,Ta Zhou 한국천문학회 2018 Journal of The Korean Astronomical Society Vol.51 No.3

The near real-time speckle masking reconstruction technique has been developed to accelerate the processing of solar images to achieve high resolutions for ground-based solar telescopes. However, the reconstruction of solar subimages in such a speckle reconstruction is very time-consuming. We design and implement a new parallel speckle masking reconstruction algorithm based on the Compute Unified Device Architecture (CUDA) on General Purpose Graphics Processing Units (GPGPU). Tests are performed to validate the correctness of our program on NVIDIA GPGPU. Details of several parallel reconstruction steps are presented, and the parallel implementation between various modules shows a significant speed increase compared to the previous serial implementations. In addition, we present a comparison of runtimes across serial programs, the OpenMP-based method, and the new parallel method. The new parallel method shows a clear advantage for large scale data processing, and a speedup of around 9 to 10 is achieved in reconstructing one solar subimage of 256$\times$256 pixels. The speedup performance of the new parallel method exceeds that of OpenMP-based method overall. We conclude that the new parallel method would be of value, and contribute to real-time reconstruction of an entire solar image.

Acetonic extracts of the endolichenic fungus EL002332 isolated from <i>Endocarpon pusillum</i> exhibits anticancer activity in human gastric cancer cells

Yang, Yi,Bae, Woo Kyun,Nam, Sang-Jip,Jeong, Min-Hye,Zhou, Rui,Park, So-Yeon,Taş,, İ,sa,Hwang, Yun-Ho,Park, Myong-Suk,Chung, Ik Joo,Kim, Kyung Keun,Hur, Jae-Seoun,Kim, Hangun Elsevier 2018 Phytomedicine Vol.40 No.-

<P>Conclusion: The endolichenic fungus EL002332 has potential anticancer activity in gastric cancer and peritoneal carcinomatosis.</P>