A novel prognostic gene signature,nomogram and immune landscape based on tanshinone IIA drug targets for hepatocellular carcinoma:Comprehensive bioinformatics analysis and in vitro experiments

Tanshinone IIA,one of the main ingredients of Danshen,is used to treat hepatocellular carcinoma(HCC).However,potential targets of the molecule in the therapy of HCC are unknown.Methods:In this study,we collected the tanshinone IIA targets from public databases for investigation.We screened differentially expressed genes(DEGs)across HCC and normal tissues using mRNA expression profiles from The Cancer Genome Atlas(TCGA).Univariate Cox regression analysis and least absolute shrinkage and selection operator(LASSO)Cox regression models were used to identify and construct the prognostic gene signature.Results:Finally,we discovered common genes across tanshinone IIA targets and HCC DEGs.We reported Fatty acid binding protein-6(FABP6),Polo-like Kinase 1(PLK1),deoxythymidylate kinase(DTYMK),Uridine Cytidine Kinase 2(UCK2),Enhancer of Zeste Homolog 2(EZH2),and Cytochrome P4502C9(CYP2C9)as components of a gene signature.The six-gene signature’s prognostic ability was evaluated using the Kaplan-Meier curve,time-dependent receiver operating characteristic(ROC),multivariate Cox regression analysis,and the nomogram.The mRNA level and protein expression of UCK2 were experimentally validated after treatment with different concentrations of tanshinone IIA in HEPG2 cells.CIBERSORTx,TIMER2.0,and GEPIA2 tools were employed to explore the relationship between the prognostic signature and immune cell infiltration.Conclusion:We established a six-gene signature as a reliable model with significant therapeutic possibility for prognosis and overall survival estimation in HCC patients,which might also benefit medical decision-making for appropriate treatment.

Role of vasoactive intestinal peptide and nitric oxide in the modulation of electroacupucture on gastric motility in stressed rats

AIM: To investigate the effects and mechanisms of vasoactive intestinal peptide (VIP) and nitric oxide (NO) in the modulation of electroacupucture (EA) on gastric motility in restrained-cold stressed rats. METHODS: An animal model of gastric motility disorder was established by restrained-cold stress. Gastric myoelectric activities were recorded by electrogastroent erography (EGG). VIP and NO concentrations in plasma and gastric mucosal and bulb tissues were detected by radioimmunoassay (RIA). VIP expression in the gastric walls was assayed using avidin-biotin-peroxidase complex (ABC) and image analysis. RESULTS: In cold restrained stressed rats, EGG was disordered and irregular. The frequency and amplitude of gastric motility were higher than that in control group (P < 0.01). VIP and NO contents of plasma, gastric mucosal and bulb tissues were obviously decreased (P < 0.01). Following EA at “Zusanli” (ST36), the frequency and amplitude of gastric motility were obviously lowered (P < 0.01), while the levels of VIP and NO in plasma, gastric mucosal and bulb tissues increased strikingly (P < 0.01, P < 0.05) and expression of VIP in antral smooth muscle was elevated significantly (P < 0.01) in comparison with those of model group. CONCLUSION: VIP and NO participate in the modulatory effect of EA on gastric motility. EA at “Zusanli” acupoint (ST36) can improve gastric motility of the stressed rats by increasing the levels of VIP and NO.

Differential gene and protein expression between rat tibial nerve and common peroneal nerve during wallerian degeneration

Wallerian degeneration and nerve regeneration after injury are complex processes involving many genes, proteins and cytokines. After different peripheral nerve injuries the regeneration rate can differ. Whether this is caused by differential expression of genes and proteins during Wallerian degeneration remains unclear. The right tibial nerve and the common peroneal nerve of the same rat were exposed and completely cut through and then sutured in the same horizontal plane. On days 1, 7, 14, and 21 after surgery, 1–2 cm of nerve tissue distal to the suture site was dissected out from the tibial and common peroneal nerves. The differences in gene and protein expression during Wallerian degeneration of the injured nerves were then studied by RNA sequencing and proteomic techniques. In the tibial and common peroneal nerves, there were 1718, 1374, 1187, and 2195 differentially expressed genes, and 477, 447, 619, and 495 differentially expressed proteins on days 1, 7, 14, and 21 after surgery, respectively. Forty-seven pathways were activated during Wallerian degeneration. Three genes showing significant differential expression by RNA sequencing (Hoxd4, Lpcat4 and Tbx1) were assayed by real-time quantitative polymerase chain reaction. RNA sequencing and real-time quantitative polymerase chain reaction results were consistent. Our findings showed that expression of genes and proteins in injured tibial and the common peroneal nerves were significantly different during Wallerian degeneration at different time points. This suggests that the biological processes during Wallerian degeneration are different in different peripheral nerves after injury. The procedure was approved by the Animal Experimental Ethics Committee of the Second Military Medical University, China (approval No. CZ20160218) on February 18, 2016.

Luteolin delays photoreceptor degeneration in a mouse model of retinitis pigmentosa

Luteolin is neuroprotective for retinal ganglion cells and retinal pigment epithelial cells after oxidative injury,whereby it can inhibit microglial neurotoxicity.Therefore,luteolin holds the potential to be useful for treatment of retinal diseases.The purpose of this study was to investigate whether luteolin exhibits neuroprotective effects on rod cells in rd10 mice,a slow photoreceptor-degenerative model of retinitis pigmentosa.Luteolin(100 mg/kg)intraperitoneally injected daily from postnatal day 14(P14)to P25 significantly enhanced the visual performance and retinal light responses of rd10 mice at P25.Moreover,it increased the survival of photoreceptors and improved retinal structure.Mechanistically,luteolin treatment attenuated increases in reactive oxygen species,photoreceptor apoptosis,and reactive gliosis;increased mRNA levels of anti-inflammatory cytokines while lowering that of pro-inflammatory and chemoattractant cytokines;and lowered the ratio of phospho-JNK/JNK.Application of the JNK inhibitor SP600125 exerted a similar protective effect to luteolin,suggesting that luteolin delays photoreceptor degeneration and functional deterioration in rd10 mice through regulation of retinal oxidation and inflammation by inhibiting the JNK pathway.Therefore,luteolin may be useful as a supplementary treatment for retinitis pigmentosa.This study was approved by the Qualified Ethics Committee of Jinan University,China(approval No.IACUC-20181217-02)on December 17,2018.

Analyzing Student Behavior in Online Programming Courses

Rather than maintaining the classic teaching approach, a growing number of schools use the blended learning system in higher education. The traditional method of teaching focuses on the result of students' progress. However, many student activities are recorded by an online programming learning platform at present. In this paper, we focus on student behavior when completing an online open-ended programming task. First, we conduct statistical analysis to examine student behavior on the basis of test times and completed time. By combining these two factors, we then classify student behavior into four types by using k-means algorithm. The results are useful for teachers to enhance their understanding of student learning and for students to know their learning style in depth. The findings are also valuable to re-design the learning platform.

Evaluating students' learning situations using “Four-quadrant law”

Evaluation is widely acknowledged as a powerful means of improving the quality of education and it is a very important component of the education system. However, the current mainstream evaluation method is based on the examination as the common way, which has very limited help to instructors' teaching. In this paper, based on an online learning platform named "educoder", we design an evaluation method by using "Four-quadrant law", which divides students' learning situations into four types. In addition, we provide some suggestions for instructors about how to give targeted teaching to different students in each type. We verify that our method is useful by setting up experiments. The experiment results show that our method can effectively improve the quality of instructors' teaching.

Posner-Schlossman syndrome:a 10-year review of clinical experience

Background:To describe our 10-year experience with Posner-Schlossman syndrome(PSS)in terms of morbidity and prognosis.Methods:We investigated 72 cases(74 eyes;both eyes of 2 cases)of PSS between July 2005 and July 2015.Data were collected on intraocular pressure(IOP),keratic precipitates(KP),anterior chamber,pupil,optic nerve disc and visual field,as well as general characteristics.Each case was examined every 3 to 7 days during attacks and every 2 to 6 months between attacks.Results:The mean age of the 72 patients(41 men)was 40±6 years(range,16-64 years).The mean disease duration was 4.3 years(range,1-7 years)and mean follow-up 4.9 years(range,1-8 years).Medical treatment was efficacious for 62 patients(62 eyes,83.78%).Ten patients exhibited progressive cupping and visual field loss(12 eyes,16.22%),all had normal IOP and no recurrence of PSS after trabeculectomy with anti-metabolite treatment.Conclusions:Although the prognosis of most PSS is usually benign,the IOP and optic nerve disc must be monitored.Visual-field damage can occur with long-term disease and frequent attacks.

Social Computing in Open Source Community:A Study of Software Reuse

Software projects are not developed in isolation but often build upon other open source resources. These projects form a kind of reference ecosystem regarded as a software world. Most of social computing works focus on social networks such as Facebook and weibo to mine information. However, few previous works analyze Open Source Community which could help developers conduct collaborative development. In this paper, we model the Java reference ecosystem as a network based on the reuse relationships of GitHub-hosted Java projects and analyze the characteristics and the patterns of this reference ecosystem by using community detection and pattern discovery algorithms. Our study indicates that (1) Developers prefer to reuse software limited in only a small part of projects with cross cutting functionality or advanced applications. (2) Developers usually select software reused with similar function widely depending on different requirements, resulting to different patterns. Based on these collective intelligence, our study opens up several possible future directions of reuse recommendation,which are considered as guidance of collaborative development.

心脏MR压缩感知超快速电影序列评价左右心室收缩功能的应用价值

目的对比传统分段采集电影序列(Seg), 探讨心脏MR(CMR)压缩感知(CS)超快速电影序列评价左右心室收缩功能的临床应用价值。方法前瞻性纳入2021年12月至2022年1月在阜外医院进行CMR检查的心脏疾病患者27例。随机顺序进行Seg、屏气下CS(bhCS)和自由呼吸下CS(fbCS)覆盖左右心室的多层短轴电影扫描。采用Friedman检验评价3种方法的总体图像质量、血池心肌信号比(BMC)和边缘锐度。分别测量3种方法的左心室舒张末期容积(EDV)、收缩末期容积(ESV)、每博输出量(SV)、射血分数(EF)、心肌质量(mass)及右心室EDV、ESV、SV、EF, 并用Bland-Altman分析bhCS与Seg、fbCS与Seg间测量结果的一致性, 并做相关性检验。结果 24例患者3种方法所有总体图像质量≥2分, 有诊断意义, 纳入后续分析。Seg、bhCS和fbCS的成像时间不同且依次降低, 分别为375.0(332.0, 405.6)、50.0(47.8, 53.7)和20.0(17.8, 23.7)s, 差异有统计学意义(χ^(2)=48.00, P<0.001)。总体图像质量fbCS略低于Seg(Z=-2.67, P=0.023), Seg和bhCS(Z=-1.44, P=0.447)、bhCS和fbCS(Z=1.23, P=0.660)之间差异无统计学意义。Seg、bhCS和fbCS的边缘锐度(χ^(2)=0.58, P=0.747)和BMC(χ^(2)=1.08, P=0.582)差异无统计学意义。Bland-Altman分析表明bhCS和Seg、fbCS和Seg之间左右心室各参数均具有良好的一致性。相关性分析结果显示bhCS和Seg、fbCS和Seg的各心功能参数均呈高度相关(r>0.96, P<0.001)。结论 CS超快速电影序列比传统序列节省了扫描时间且提供了相似的图像质量, 且无论是否屏气, CS序列心功能结果与传统电影序列具有良好的一致性和高度的相关性。

基于群智的软件开发群体化方法与实践

互联网技术的发展对软件开发技术、运行形态和服务模式都产生了前所未有的影响,以开源和众包为代表的大规模群体协作实践所蕴含的群体智能机理为网络时代的软件开发带来重大启示.本文以开源和众包大规模实践为案例,深入分析了开源创新和众包生产模式,凝练提出了以大众化协同、开放式共享和持续性评估为核心的群智软件开发机理,从群体协作基础环境、群体协作机制模型和群体协作支撑技术3个方面,深入讨论了基于群智的群体化软件开发服务环境涉及的关键要素以及我们的开源实践,并提出了群智软件开发未来面临的重大挑战,希望能为网络环境下基于群智的群体化软件开发提供有益的视角和借鉴.

Wnt/β-catenin signalling:function,biological mechanisms,and therapeutic opportunities

The Wnt/β-catenin pathway comprises a family of proteins that play critical roles in embryonic development and adult tissue homeostasis.The deregulation of Wnt/β-catenin signalling often leads to various serious diseases,including cancer and non-cancer diseases.Although many articles have reviewed Wnt/β-catenin from various aspects,a systematic review encompassing the origin,composition,function,and clinical trials of the Wnt/β-catenin signalling pathway in tumour and diseases is lacking.In this article,we comprehensively review the Wnt/β-catenin pathway from the above five aspects in combination with the latest research.Finally,we propose challenges and opportunities for the development of small-molecular compounds targeting the Wnt signalling pathway in disease treatment.

Intelligent Development Environment and Software Knowledge Graph

Software intelligent development has become one of the most important research trends in software engineering. In this paper, we put forward two key concepts -- intelligent development environment （IntelliDE） and software knowledge graph -- for the first time. IntelliDE is an ecosystem in which software big data are aggregated, mined and analyzed to provide intelligent assistance in the life cycle of software development. We present its architecture and discuss its key research issues and challenges. Software knowledge graph is a software knowledge representation and management framework, which plays an important role in IntelliDE. We study its concept and introduce some concrete details and examples to show how it could be constructed and leveraged.

Downregulation of MEIS1 mediated by ELFN1-AS1/EZH2/DNMT3a axis promotes tumorigenesis and oxaliplatin resistance in colorectal cancer

Oxaliplatin is widely used in the frontline treatment of colorectal cancer(CRC),but an estimated 50%of patients will eventually stop responding to treatment due to acquired resistance.This study revealed that diminished MEIS1 expression was detected in CRC and harmed the survival of CRC patients.MEIS1 impaired CRC cell viabilities and tumor growth in mice and enhanced CRC cell sensitivity to oxaliplatin by preventing DNA damage repair.Mechanistically,oxaliplatin resistance following MEIS1 suppression was critically dependent on enhanced FEN1 expression.Subsequently,we confirmed that EZH2-DNMT3a was assisted by lncRNA ELFN1-AS1 in locating the promoter of MEIS1 to suppress MEIS1 transcription epigenetically.Based on the above,therapeutics targeting the role of MEIS1 in oxaliplatin resistance were developed and our results suggested that the combination of oxaliplatin with either ELFN1-AS1 ASO or EZH2 inhibitor GSK126 could largely suppress tumor growth and reverse oxaliplatin resistance.This study highlights the potential of therapeutics targeting ELFN1-AS1 and EZH2 in cell survival and oxaliplatin resistance,based on their controlling of MEIS1 expression,which deserve further verification as a prospective therapeutic strategy.

RepoLike: a multi-feature-based personalized recommendation approach for open-source repositories

With the deep integration of software collaborative development and social networking, social coding represents a new style of software production and creation paradigm. Because of their good flexibility and openness,a large number of external contributors have been attracted to the open-source communities. They are playing a significant role in open-source development. However, the open-source development online is a globalized and distributed cooperative work. If left unsupervised, the contribution process may result in inefficiency. It takes contributors a lot of time to find suitable projects or tasks from thousands of open-source projects in the communities to work on. In this paper, we propose a new approach called "RepoLike," to recommend repositories for developers based on linear combination and learning to rank. It uses the project popularity, technical dependencies among projects, and social connections among developers to measure the correlations between a developer and the given projects. Experimental results show that our approach can achieve over 25% of hit ratio when recommending 20 candidates, meaning that it can recommend closely correlated repositories to social developers.

Tag recommendation for open source software

Nowadays open source software becomes highly popular and is of great importance for most software engi- neering activities. To facilitate software organization and re- trieval, tagging is extensively used in open source communi- ties. However, finding the desired software through tags in these communities such as Freecode and ohloh is still chal- lenging because of tag insufficiency. In this paper, we propose TRG （tag recommendation based on semantic graph）, a novel approach to discovering and enriching tags of open source software. Firstly, we propose a semantic graph to model the semantic correlations between tags and the words in software descriptions. Then based on the graph, we design an effec- tive algorithm to recommend tags for software. With com- prehensive experiments on large-scale open source software datasets by comparing with several typical related works, we demonstrate the effectiveness and efficiency of our method in recommending proper tags.

What Are They Talking About？ Analyzing Code Reviews in Pull-Based Development Model

Code reviews in pull-based model are open to community users on GitHub. Various participants are taking part in the review discussions and the review topics are not only about the improvement of code contributions but also about project evolution and social interaction. A comprehensive understanding of the review topics in pull-based model would be useful to better organize the code review process and optimize review tasks such as reviewer recommendation and pull-request prioritization. In this paper, we first conduct a qualitative study on three popular open-source software projects hosted on GitHub and construct a fine-grained two-level taxonomy covering four level-1 categories （code correctness, pull- request decision-making, project management, and social interaction） and 11 level-2 subcategories （e.g., defect detecting, reviewer assigning, contribution encouraging）. Second, we conduct preliminary quantitative analysis on a large set of review comments that were labeled by TSHC （a two-stage hybrid classification algorithm）, which is able to automatically classify review comments by combining rule-based and machine-learning techniques. Through the quantitative study, we explore the typical review patterns. We find that the three projects present similar comments distribution on each subeategory. Pull-requests submitted by inexperienced contributors tend to contain potential issues even though they have passed the tests. Furthermore, external contributors are more likely to break project conventions in their early contributions.

An online service-oriented performance profiling tool for cloud computing systems

The growing scale and complexity of component interactions in cloud computing systems post great challenges for operators to understand the characteristics of system performance. Profiling has long been proved to be an effective approach to performance analysis; however, existing approaches confront new challenges that emerge in cloud computing systems. First, the efficiency of the profiling becomes of critical concern; second, service-oriented profiling should be considered to support separation-of-concerns performance analysis. To address the above issues, in this paper, we present P-Tracer, an online performance profiling tool specifically tailored for cloud computing systems. P-Tracer constructs a specific search engine that proactively processes performance logs and generates a particular index for fast queries; second, for each service, P-Tracer retrieves a statistical insight of performance characteristics from multi-dimensions and provides operators with a suite of web-based interfaces to query the critical information. We evaluate P- Tracer in the aspects of tracing overheads, data preprocessing scalability and querying efficiency. Three real-world case studies that happened in Alibaba cloud computing platform demonstrate that P-Tracer can help operators understand soft-ware behaviors and localize the primary causes of performance anomalies effectively and efficiently.

Asymptotic optimality for consensus-type stochastic approximation algorithms using iterate averaging

This paper introduces a post-iteration averaging algorithm to achieve asymptotic optimality in convergence rates of stochastic approximation algorithms for consensus control with structural constraints. The algorithm involves two stages. The first stage is a coarse approximation obtained using a sequence of large stepsizes. Then, the second stage provides a refinement by averaging the iterates from the first stage. We show that the new algorithm is asymptotically efficient and gives the optimal convergence rates in the sense of the best scaling factor and ＇smallest＇ possible asymptotic variance.

Correlation-based software search by leveraging software term database

Internet-scale open source software （OSS） pro- duction in various communities generates abundant reusable resources for software developers. However, finding the de- sired and mature software with keyword queries from a considerable number of candidates, especially for the fresher, is a significant challenge because current search services often fail to understand the semantics of user queries. In this paper, we construct a software term database （STDB） by analyzing tagging data in Stack Overflow and propose a correlationbased software search （CBSS） approach that performs correlation retrieval based on the term relevance obtained from STDB. In addition, we design a novel ranking method to optimize the initial retrieval result. We explore four research questions in four experiments, respectively, to evaluate the effectiveness of the STDB and investigate the performance of the CBSS. The experiment results show that the proposed CBSS can effectively respond to keyword-based software searches and significantly outperforms other existing search services at finding mature software.

Improving students’programming quality with the continuous inspection process:a social coding perspective

College students majoring in computer science and software engineering need to master skills for high-quality programming.However,rich research has shown that both the teaching and learning of high-quality programming are challenging and deficient in most college education systems.Recently,the continuous inspection paradigm has been widely used by developers on social coding sites(e.g.,GitHub)as an important method to ensure the internal quality of massive code contributions.This paper presents a case where continuous inspection is introduced into the classroom setting to improve students’programming quality.In the study,we first designed a specific continuous inspection process for students’collaborative projects and built an execution environment for the process.We then conducted a controlled experiment with 48 students from the same course during two school years to evaluate how the process affects their programming quality.Our results show that continuous inspection can help students in identifying their bad coding habits,mastering a set of good coding rules and significantly reducing the density of code quality issues introduced in the code.Furthermore,we describe the lessons learned during the study and propose ideas to replicate and improve the process and its execution platform.