| 1. |
- Mi, Yushuai, et al.
(author)
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Down-regulation of Barx2 predicts poor survival in colorectal cancer
- 2016
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In: Biochemical and Biophysical Research Communications - BBRC. - : ACADEMIC PRESS INC ELSEVIER SCIENCE. - 0006-291X .- 1090-2104. ; 478:1, s. 67-73
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Journal article (peer-reviewed)abstract
- Human BarH-like homeobox 2 (Barx2), a homeodomain factor of the Bar family, has an important role in controlling the expression of cell adhesion molecules and has been reported in an increasing array of tumor types except colorectal cancer (CRC). The purpose of the current study was to characterize the expression of Barx2 and assess the clinical significance of Barx2 in CRC. First, we analyzed the expression of Barx2 in two independent public datasets from Oncomine. Subsequently, we evaluated Barx2 mRNA and protein expression by quantitative real-time PCR and western blotting, respectively. It was determined that Barx2 expression was lower in tumor tissues than in adjacent non-tumorous colorectal tissues of CRC patients, consistent with results from the public datasets. Subsequently, a tissue microarray containing 196 CRC specimens was evaluated for Barx2 expression by immunohistochemical staining. It was found that low expression of Barx2 significantly correlated with TNM stage, AJCC stage, differentiation, and relapse in patients with CRC. Patients with lower levels of Barx2 expression showed reduced disease-free survival and overall survival. Furthermore, a trend toward shorter overall survival in the patient group with Barx2-negative tumors independent of advanced AJCC stage and poor differentiation was determined by Kaplan-Meier survival analysis. Based on univariate and multivariate analyses, Barx2 expression was an independent prognostic factor for determining CRC prognosis. Taken together, low Barx2 expression was associated with the progression of CRC and could serve as a potential independent prognostic biomarker for patients with CRC. (C) 2016 The Authors. Published by Elsevier Inc.
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| 2. |
- Yu, Wenjin, et al.
(author)
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Deep Learning-Based Classification of Cancer Cell in Leptomeningeal Metastasis on Cytomorphologic Features of Cerebrospinal Fluid
- 2022
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In: Frontiers in Oncology. - : Frontiers Media SA. - 2234-943X. ; 12, s. 1-11
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Journal article (peer-reviewed)abstract
- Background: It is a critical challenge to diagnose leptomeningeal metastasis (LM), given its technical difficulty and the lack of typical symptoms. The existing gold standard of diagnosing LM is to use positive cerebrospinal fluid (CSF) cytology, which consumes significantly more time to classify cells under a microscope.Objective: This study aims to establish a deep learning model to classify cancer cells in CSF, thus facilitating doctors to achieve an accurate and fast diagnosis of LM in an early stage.Method: The cerebrospinal fluid laboratory of Xijing Hospital provides 53,255 cells from 90 LM patients in the research. We used two deep convolutional neural networks (CNN) models to classify cells in the CSF. A five-way cell classification model (CNN1) consists of lymphocytes, monocytes, neutrophils, erythrocytes, and cancer cells. A four-way cancer cell classification model (CNN2) consists of lung cancer cells, gastric cancer cells, breast cancer cells, and pancreatic cancer cells. Here, the CNN models were constructed by Resnet-inception-V2. We evaluated the performance of the proposed models on two external datasets and compared them with the results from 42 doctors of various levels of experience in the human-machine tests. Furthermore, we develop a computer-aided diagnosis (CAD) software to generate cytology diagnosis reports in the research rapidly.Results: With respect to the validation set, the mean average precision (mAP) of CNN1 is over 95% and that of CNN2 is close to 80%. Hence, the proposed deep learning model effectively classifies cells in CSF to facilitate the screening of cancer cells. In the human-machine tests, the accuracy of CNN1 is similar to the results from experts, with higher accuracy than doctors in other levels. Moreover, the overall accuracy of CNN2 is 10% higher than that of experts, with a time consumption of only one-third of that consumed by an expert. Using the CAD software saves 90% working time of cytologists.Conclusion: A deep learning method has been developed to assist the LM diagnosis with high accuracy and low time consumption effectively. Thanks to labeled data and step-by-step training, our proposed method can successfully classify cancer cells in the CSF to assist LM diagnosis early. In addition, this unique research can predict cancer’s primary source of LM, which relies on cytomorphologic features without immunohistochemistry. Our results show that deep learning can be widely used in medical images to classify cerebrospinal fluid cells. For complex cancer classification tasks, the accuracy of the proposed method is significantly higher than that of specialist doctors, and its performance is better than that of junior doctors and interns. The application of CNNs and CAD software may ultimately aid in expediting the diagnosis and overcoming the shortage of experienced cytologists, thereby facilitating earlier treatment and improving the prognosis of LM.
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| 3. |
- Andersson, Jens A, et al.
(author)
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User profiling for pre-fetching or caching in a catch-up TV network
- 2016
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In: 2016 IEEE International Symposium on Broadband Multimedia Systems and Broadcasting (BMSB). - 9781467390446
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Conference paper (peer-reviewed)abstract
- We investigate the potential of different pre-fetching and/or caching strategies for different user behaviour with respect to surfing or browsing in a catch-up-TV network. To this end we identify accounts and channels associated with strong or weak surfing or browsing respectively and study the distributions of hold times for the different types of behaviour. Finally we present results from a request prediction model and a caching simulation for the different types of behaviour and find that the results are relatively similar.
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| 4. |
- Chen, Yangli, et al.
(author)
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A sensitivity study of MELCOR nodalization for simulation of in-vessel severe accident progression in a boiling water reactor
- 2019
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In: Nuclear Engineering and Design. - : ELSEVIER SCIENCE SA. - 0029-5493 .- 1872-759X. ; 343, s. 22-37
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Journal article (peer-reviewed)abstract
- This paper presents a sensitivity study of MELCOR nodalization for simulation of postulated severe accidents in a Nordic boiling water reactor, with the objective to address the nodal effect on in-vessel accident progression, including thermal-hydraulic response, core degradation and relocation, hydrogen generation, source term release, melt behavior and heat transfer in the lower head, etc. For this purpose, three meshing schemes (coarse, medium and fine) of the COR package of MELCOR are chosen to analyze two severe accident scenarios: station blackout (SBO) accident and large break loss-of-coolant accident (LOCA) combined with station blackout. The comparative results of the MELCOR simulations show that the meshing schemes mainly affect the core degradation and relocation to the lower head of the reactor pressure vessel: the fine mesh leads to a delayed leveling process of a heap-like debris bed in the lower head, and a later breach of the vessel. The simulations with fine mesh also provide more detailed distributions of corium mass and temperature, as well as heat flux which is an important parameter in qualification assessment of the In-Vessel Melt Retention (IVR) strategy.
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| 5. |
- Chen, Yangli, et al.
(author)
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Coupled MELCOR/COCOMO analysis on quench of ex-vessel debris beds
- 2022
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In: Annals of Nuclear Energy. - : Elsevier BV. - 0306-4549 .- 1873-2100. ; 165
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Journal article (peer-reviewed)abstract
- The cornerstone of severe accident strategy of Nordic BWRs is to flood the reactor cavity for the long-termcoolability of an ex-vessel debris bed. As a prerequisite of the long-term coolability, the hot debris bedformed from fuel coolant interactions (FCI) should be quenched. In the present study, coupling of theMELCOR and COCOMO codes is realized with the aim to analyze the quench process of an ex-vessel debrisbed under prototypical condition of a Nordic BWR. In this coupled simulation, MELCOR performs an integralanalysis of accident progression, and COCOMO performs the thermal–hydraulic analysis of the debrisbed in the flooded cavity. The effective diameter of the particles is investigated. The discussion on thebed’s shape shows a significant effect on the propagation of the quench front, due to different flow patterns.Compared with MELCOR standalone simulation, the coupled simulation predicts earlier cavity poolsaturation and containment venting.
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| 6. |
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| 7. |
- Du, Manxing, et al.
(author)
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Prefetching schemes and performance analysis for TV on demand services
- 2015
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In: International Journal On Advances in Telecommunications. - 1942-2601 .- 1942-2601. ; 8:3&4, s. 162-172
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Journal article (peer-reviewed)abstract
- TV-on-Demand services have become one of the most popular Internet applications that continuously attracts high user interest. With rapidly increasing user demands, the existing network conditions may not be able to ensure a low start-up delay of video playback. Prefetching has been broadly investigated to cope with the start-up latency problem, which is also known as user perceived latency. In this paper, two datasets from different IPTV providers are used to analyse the TV program request patterns. According to the results, we propose a prefetching scheme at the user end to preload videos before user requests. For both datasets, our prefetching scheme significantly improves the cache hit ratio compared to passive caching and we note that there is a potential to further improve prefetching performance by customizing prefetching schemes for different video categories. We further present a cost model to determine the optimal number of videos to prefetch. We also discuss if there is enough time for prefetching. Finally, more factors, which may have an impact onoptimizing prefetching performance, are further discussed, such as the jump patterns over different time in a day and the the distribution of each video’s viewing length.
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| 8. |
- Du, Manxing, et al.
(author)
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Prefetching Schemes and Performance Analysis for TV on Demand Services
- 2015
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In: International Journal on Advances in Telecommunications. - 1942-2601. ; 8:3&4, s. 162-172
-
Journal article (peer-reviewed)abstract
- TV-on-Demand services have become one of the most popular Internet applications that continuously attracts high user interest. With rapidly increasing user demands, the existing network conditions may not be able to ensure a low start-up delay of video playback. Prefetching has been broadly investigated to cope with the start-up latency problem, which is also known as user perceived latency. In this paper, two datasets from different IPTV providers are used to analyse the TV program request patterns. According to the results, we propose a prefetching scheme at the user end to preload videos before user requests. For both datasets, our prefetching scheme significantly improves the cache hit ratio compared to passive caching and we note that there is a potential to further improve prefetching performance by customizing prefetching schemes for different video categories. We further present a cost model to determine the optimal number of videos to prefetch. We also discuss if there is enough time for prefetching. Finally, more factors, which may have an impact on optimizing prefetching performance, are further discussed, such as the jump patterns over different time in a day and the the distribution of each video’s viewing length.
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| 9. |
- Mi, Yushuai, et al.
(author)
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Downregulation of homeobox gene Barx2 increases gastric cancer proliferation and metastasis and predicts poor patient outcomes
- 2016
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In: Oncotarget. - : IMPACT JOURNALS LLC. - 1949-2553. ; 7:37, s. 60593-60608
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Journal article (peer-reviewed)abstract
- Barx2 is a Bar family homeodomain transcription factor shown to play a critical role in cell adhesion and cytoskeleton remodeling, key processes in carcinogenesis and metastasis. Using quantitative real-time PCR, Western blotting, and immunohistochemistry, we found that Barx2 is expressed at lower levels in human gastric cancer (GC) tissues than in adjacent normal mucosa. In a multivariate analysis, Barx2 expression emerged as an independent prognostic factor for disease-free and overall survival. Kaplan-Meier survival analysis showed a trend toward even shorter overall survival in the patient group with Barx2-negative tumors, independent of advanced UICC stage and tumor relapse. Using in vitro and in vivo assays, we demonstrated that under normal conditions Barx2 inhibited GC cell proliferation and invasiveness through inhibition of the Wnt/beta-catenin signaling pathway. These findings indicate that reduction or loss of Barx2 dis-inhibits GC cell proliferation and invasion, and that reduction in Barx2 could serve as an independent prognostic biomarker for poor outcome in GC patients.
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| 10. |
- Peng, Jianhui, et al.
(author)
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Achieving ultra-high electromagnetic wave absorption by anchoring Co0.33Ni0.33Mn0.33Fe2O4 nanoparticles on graphene sheets using microwave-assisted polyol method
- 2018
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In: Ceramics International. - : ELSEVIER SCI LTD. - 0272-8842 .- 1873-3956. ; 44:17, s. 21015-21026
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Journal article (peer-reviewed)abstract
- The Co0.33Ni0.33Mn0.33Fe2O4/graphene nanocomposite for electromagnetic wave absorption was successfully synthesized from metal chlorides solutions and graphite powder by a simple and rapid microwave-assisted polyol method via anchoring the Co0.33Ni0.33Mn0.33Fe2O4 nanoparticles on the layered graphene sheets. The Fe3+, Co2+, Ni2+ and Mn2+ ions in the solutions were attracted by graphene oxide obtained from graphite and converted to the precursors Fe(OH)(3), Co(OH)(2), Ni(OH)(2), and Mn(OH)(2) under slightly alkaline conditions. After the transformations of the precursors to Co-Ni-Mn ferrites and conversion of graphene oxide to graphene under microwave irradiation at 170 degrees C in just 25 min, the Co0.33Ni0.33Mn0.33Fe2O4/graphene nanocomposite was prepared. The composition and structure of the nanocomposite were characterized by X-ray diffraction (XRD), inductive coupled plasma emission spectroscopy (ICP), X-ray photoelectron spectroscopy (XPS), Fourier transform infrared spectroscopy (FT-IR), Raman spectroscopy (RS), transmission electron microscopy (TEM), etc. It was found that with the filling ratio of only 20 wt% and the thickness of 2.3 mm, the nanocomposite showed an ultra-wide effective absorption bandwidth (less than -10 dB) of 8.48 GHz (from 9.52 to 18.00 GHz) with the minimum reflection loss of - 24.29 dB. Compared to pure graphene sheets, Co0.33Ni0.33Mn0.33Fe2O4 nano particles and the counterparts reported in literature, the nanocomposite exhibited much better electromagnetic wave absorption, mainly attributed to strong wave attenuation, as a result of synergistic effects of dielectric loss, conductive loss and magnetic loss, and to good impedance matching. In view of its thin thickness, light weight and outstanding electromagnetic wave absorption property, the nanocomposite could be used as a very promising electromagnetic wave absorber.
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