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Dysregulation of miR-135a-5p promotes the development of rat pulmonary arterial hypertension in vivo and in vitro

中国药理学报（英文版） 2019年第4期40卷 477-485页

作者： Hong-mei Liu Yi Jia Ying-xian Zhang Jun Yan Ning Liao Xiao-hui Li Yuan Tang Institute of Materia Medica College of Pharmacy Third Military Medical University Chongqing 400038China Center of Translational Medicine College of Pharmacy Third Military Medical University Chongqing 400038 China Institute of Hepatobiliary Surgery Southwest Hospital Third Military Medical University Chongqing 400038 China College of Software and Computer Science Chongqing Institute of Engineering Chongqing 400056 China

Pulmonary arterial hypertension (PAH) is the most common form of pulmonary *** arterial remodeling is closely related to the abnormal proliferation of pulmonary artery smooth muscle cells (PASMCs),which leads to the thickening of the medial layer of muscular arteries and then results in the narrowing or occlusion of the precapillary arterioles and ***,the mechanisms underlying the abnormal proliferation of PASMCs remain *** this study,we established rat primary PAH models using monocrotaline (MCT) injection or hypoxic exposure,then investigated the expression patterns of seven miRNAs associated with multiple pathogenic pathways central to pulmonary hypertension,and further explored the roles and the possible mechanisms of miR-135a during the development of *** the rat primary PAH models,we observed that the expression of miR-135a-5p in lungs was drastically decreased at the initial stage of PAH development after MCT administration or hypoxic exposure,but it increased by 12-fold or 10-fold at the later *** vitro study in PASMCs showed a similar pattern of miR-135a-5p expression,with downregulation at 6 h but upregulation at 18,24,and 48 h after hypoxic ***,but not late,administration of a miR-135a-5p mimic inhibited hypoxia-induced proliferation of *** protective role of early miR-135a-5p agomir in the PAH rat model further supported the hypothesis that the early decrease in the expression of miR-135a-5p contributes to the proliferation of PASMCs and development of PAH,as early administration of miR-135a-5p agomir (10 nM,i.v.) reversed the elevated mean pulmonary arterial pressure and pulmonary vascular remodeling in MCT-treated *** revealed that miR-135a-5p directly bound to the 3'-UTR sequence of rat transient receptor potential channel 1 (TRPC1) mRNA and decreased TRPC1 protein expression,thus inhibiting PASMC ***,our data suggest that dysregulation of miR-135a-5p in PASMCs cont

关键词： pulmonary arterial hypertension miR-135a-5p pulmonary artery smooth muscle cells transient receptor potential channel 1

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The Power of Bias: Optimizing Client Selection in Federated Learning with Heterogeneous Differential Privacy

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IEEE Transactions on Dependable and Secure Computing 2025年

作者： Ma, Jiating Zhou, Yipeng Li, Qi Sheng, Quan Z. Cui, Laizhong Liu, Jiangchuan Shenzhen University College of Computer Science and Software Engineering Shenzhen518060 China Shenzhen518060 China Macquarie University School of Computing Faculty of Science and Engineering Macquarie ParkNSW2119 Australia Tsinghua University Institute for Network Sciences and Cyberspace Beijing100190 China Beijing National Research Center for Information Science and Technology Beijing100190 China Simon Fraser University School of Computing Science BurnabyBCV5A 1S6 Canada

To preserve the data privacy, the federated learning (FL) paradigm emerges in which clients only expose model gradients rather than original data for conducting model training. To enhance the protection of model gradients in FL, differentially private federated learning (DPFL) is proposed which incorporates differentially private (DP) noises to obfuscate gradients before they are exposed. Yet, an essential but largely overlooked problem in DPFL is the heterogeneity of clients' privacy requirement, which can vary significantly between clients and extremely complicates the client selection problem in DPFL. In other words, both the data quality and the influence of DP noises should be taken into account when selecting clients. To address this problem, we conduct convergence analysis of DPFL under heterogeneous privacy, a generic client selection strategy, popular DP mechanisms and convex loss. Based on convergence analysis, we formulate the client selection problem to minimize the value of loss function in DPFL with heterogeneous privacy, which is a convex optimization problem and can be solved efficiently. Accordingly, we propose the DPFL-BCS (biased client selection) algorithm. The extensive experiment results with real datasets under both convex and non-convex loss functions indicate that DPFL-BCS can remarkably improve model utility compared with the SOTA baselines. © 2004-2012 IEEE.

关键词： Convex optimization

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Improved Inductive Matrix Completion Method for Predicting MicroRNA-Disease Associations 15th

Improved Inductive Matrix Completion Method for Predicting M...

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15th International Conference on Intelligent Computing, ICIC 2019

作者： Ding, Xin Xia, Jun-Feng Wang, Yu-Tian Wang, Jing Zheng, Chun-Hou College of Computer Science and Technology Anhui University Hefei China Institute of Physical Science and Information Technology Anhui University Hefei China School of Software Engineering Qufu Normal University Qufu China School of Computer and Information Engineering Fuyang Normal University Fuyang China

ISBN: (纸本)9783030269685

Nowadays, plenty of evidence indicates that microRNAs (miRNAs) can result in various human complex diseases and may be as new biological markers to diagnose specific diseases. The reality is that biological experimental corroboration of disease-related miRNAs is time consuming and laborious. Therefore, the calculation methods for recognizing the potential relationship between the miRNA and the disease have become an increasingly significant hot topic in the world. In this paper, we exploited an improved calculation method based on inductive matrix completion to predict disease related miRNAs (IIMCMP). Firstly, we construct miRNA-disease adjacency matrix by adopting verified miRNA-disease associations. In addition, the proposed approach uses the three matrices, including the disease-miRNA association matrix, the integrated disease similarity matrix and the miRNA functional similarity matrix. Secondly, considering new diseases or new miRNAs, it is necessary to preprocess the adjacency matrix of biologically validated associations between diseases and miRNAs, so we calculate the interaction profile between miRNAs and diseases to update adjacency matrix of miRNA-disease association. Finally, inductive matrix completion algorithm is adopted to predict the probability score on the heterogeneous network between miRNAs and diseases. As a result, IIMCMP gained the AUC of 0.9016 which adopted new interaction likelihood profiles in the leave-one-out cross validation. In addition, two case studies and leave-one-out cross validation demonstrated that IIMCMP can achieve predominant and reliable performance assessment. © 2019, Springer Nature Switzerland AG.

关键词： Association reactions

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Live streaming as co-performance: Dynamics between center and periphery in theatrical engagement

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Proceedings of the ACM on Human-computer Interaction 2019年第CSCW期3卷 1-22页

作者： Li, Jie Gui, Xinning Kou, Yubo Li, Yukun School of Computer Science and Engineering Tianjin University of Technology Tianjin300384 China Pennsylvania State University State College PA United States Tianjin Key Laboratory of Intelligence Computing and Novel Software Technology Tianjin University of Technology Tianjin300384 China

Live streaming is a highly participatory form of performance, involving various types of audience participation such as liking, commenting, and gifting. But how do streamers and audiences collaborate to deliver live streaming performances? We approach this question through an interview study with 30 spectators and eight streamers in China. Drawing from theatrical engagement research, we use the cogitative spatial concept of center-peripheral attention of the audience to analyze the complex interplay between streamers and spectators, where the former occupy the center and the latter the periphery. We then discuss the orchestration of the center and the periphery, where streamers and spectators coordinate their respective performances, as well as the interaction between the center and the periphery, where the center-periphery distinction blurs. Based on these findings, we discuss co-performance as a theatrical metaphor for understanding live streaming and audience engagement. Copyright is held by the owner/author(s). Publication rights licensed to ACM.

关键词： climax co-performance interactive performance live streaming para-social interaction theatrical engagement

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An advanced operating environment for mathematics education resources

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science China(Information sciences) 2018年第9期61卷 270-281页

作者： Yongsheng RAO Jingzhong ZHANG Yu ZOU Yanchun SUN Xiangping CHEN Songhua XU School of Data and Computer Science Sun Yat-Sen University Academy for Intelligent Software Guangzhou University Institute of Mathematics and Computer Science Guizhou Normal College School of Electronics Engineering and Computer Science Peking University Key Laboratory of High Confidence Software Technologies Ministry of Education Beijing College of Computer Sciences New Jersey Institute of Technology

The potential of information technology(IT)in education modernization has been widely *** the broad efforts for advancing education IT,digital education resources continue to receive a high level of attention,with the... 详细信息

关键词： SSP OA An advanced operating environment for mathematics education resources OER Figure

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Discovery of time profiled temporal patterns 19

Discovery of time profiled temporal patterns

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5th International Conference on engineering and MIS, ICEMIS 2019

作者： Radhakrishna, Vangipuram Aljawarneh, Shadi Kumar, P.V. Janaki, Vinjamuri Cheruvu, Aravind Information Technology Dept VNR VJIET Hyderabad India Software Engg Dept JUST Jordan Computer Science and Engg Dept Acharya Institute of Technology Bangalore India Computer Science and Engg Dept Vaagdevi College of Engineering Warangal India

ISBN: (纸本)9781450372121

Finding temporal association patterns from temporal dataset is addressed in a wider perspective in the existing literature. Discovering time profiled temporal patterns is addressed in our previous research works which includes proposing new support estimation techniques, similarity measures for computing similarity between temporal patterns. Most measures proposed in our previous research are for Gaussian space. Our previous research proposed z-space dissimilarity measures SRIHASS and KRISHNA SUDARSANA. Following these two measures, there have been no z-space measures that are proposed in literature. This paper proposes a new similarity measure for determining similarity between temporal patterns in z-space. © 2019 Association for Computing Machinery. All rights reserved.

关键词： Z-score computational complexity support temporal pattern novel approach similarity computation

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Reconnaissance attack detection via boosting machine learning classifiers

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AIP Conference Proceedings 2023年第1期2979卷

作者： Omar Almomani Mohammed Amin Almaiah Mohammed MADI Adeeb Alsaaidah Malek A. Almomani Sami Smadi Department of Information System and Networks The World Islamic Sciences and Education University Amman Jordan College of Computer Science and Information Technology King Faisal University Al-Ahsa 31982 Saudi Arabia Department of Computer Engineering Hasan Kalyoncu University Gaziantep Turkey Department of Software Engineering The World Islamic Sciences and Education University University Amman Jordan

With the advancement of Internet technologies, network security concerns are growing exponentially. One of the most difficult issues of network security is keeping it safe. To detect and identify any malicious behavior the network, many security techniques were deployed. Intrusion Detection Systems (IDS) is one of the most frequent strategies for mitigating the effects of these attacks. Reconnaissance is a common attack in computer networks in which the attacker gathers as much information as possible about the target before conducting an attack. Machine Learning (ML) classifiers are commonly used to distinguish between normal and abnormal network traffic. In this paper, Raeconnaissance attacks detection is an exam with the following ML classifiers: Adaptive Boosting (AdaBoost), Gradient Boosting, cat Boosting, and eXtreme Gradient Boosting (XGBoost) to determine the most effective classifier in identifying Reconnaissance attacks. Evaluation metrics used are accuracy, precision, F-measure True Positive. The experiment on the UNSW-NB15 dataset shows that the cat Boosting classifier is superior to the XGBoost, AdaBoost and Gradiant Boosting.

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Learning generic diffusion processes for image restoration 29

Learning generic diffusion processes for image restoration

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29th British Machine Vision Conference, BMVC 2018

作者： Qiao, Peng Dou, Yong Chen, Yunjin Feng, Wensen Science and Technology on Parallel and Distributed Laboratory National University of Defense Technology Changsha China ULSee Inc. Hangzhou China College of Computer Science and Software Engineering Shenzhen University Shenzhen China

Image restoration problems are typical ill-posed problems where the regularization term plays an important role. The regularization term learned via generative approaches is easy to transfer to various image restoration, but offers inferior restoration quality compared with that learned via discriminative approaches. On the contrary, the regularization term learned via discriminative approaches are usually trained for a specific image restoration problem, and fail in the problem for which it is not trained. To address this issue, we propose a generic diffusion process (genericDP) to handle multiple Gaussian denoising problems based on the Trainable Non-linear Reaction Diffusion (TNRD) models. Instead of one model, which consists of a diffusion and a reaction term, for one Gaussian denoising problem in TNRD, we enforce multiple TNRD models to share one diffusion term. The trained genericDP model can provide both promising denoising performance and high training efficiency compared with the original TNRD models. We also transfer the trained diffusion term to non-blind deconvolution which is unseen in the training phase. Experiment results show that the trained diffusion term for multiple Gaussian denoising can be transferred to image non-blind deconvolution as an image prior and provide competitive performance. © 2018. The copyright of this document resides with its authors. It may be distributed unchanged freely in print or electronic forms.

关键词： Diffusion

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Fast deep learning computer-aided diagnosis of COVID-19 based on digital chest x-ray images

Research Square

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Research Square 2020年

作者： Al-Antari, Mugahed A. Hua, Cam-Hao Bang, Jaehun Lee, Sungyoung Department of Computer Science and Engineering College of Software Kyung Hee University 1732 Deogyeong-daero Giheung-gu Gyeonggi-do Yongin-si17104 Korea Republic of Department of Biomedical Engineering Sana’a Community College Sana'a Yemen

Coronavirus disease 2019 (COVID-19) is a novel harmful respiratory disease that has rapidly spread worldwide. At the end of 2019, COVID-19 emerged as a previously unknown respiratory disease in Wuhan, Hubei Province, China. The world health organization (WHO) declared the coronavirus outbreak a pandemic in the second week of March 2020. Simultaneous deep learning detection and classification of COVID-19 based on the full resolution of digital X-ray images is the key to efficiently assisting patients by enabling physicians to reach a fast and accurate diagnosis decision. In this paper, a simultaneous deep learning computer-aided diagnosis (CAD) system based on the YOLO predictor is proposed that can detect and diagnose COVID-19, differentiating it from eight other respiratory diseases: atelectasis, infiltration, pneumothorax, masses, effusion, pneumonia, cardiomegaly, and nodules. The proposed CAD system was assessed via five-fold tests for the multi-class prediction problem using two different databases of chest X-ray images: COVID-19 and ChestX-ray8. The proposed CAD system was trained with an annotated training set of 50,490 chest X-ray images. The regions on the entire X-ray images with lesions suspected of being due to COVID-19 were simultaneously detected and classified end-to-end via the proposed CAD predictor, achieving overall detection and classification accuracies of 96.31% and 97.40%, respectively. Most test images from patients with confirmed COVID-19 and other respiratory diseases were correctly predicted, achieving average intersection over union (IoU) greater than 90%. Applying deep learning regularizers of data balancing and augmentation improved the COVID-19 diagnostic performance by 6.64% and 12.17% in terms of the overall accuracy and the F1-score, respectively. It is feasible to achieve a diagnosis based on individual chest X-ray images with the proposed CAD system within 0.0093 s. Thus, the CAD system presented in this paper can make a predictio

关键词： Coronavirus

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Tree based data fusion approach for mining temporal patterns 19

Tree based data fusion approach for mining temporal patterns

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5th International Conference on engineering and MIS, ICEMIS 2019

作者： Radhakrishna, Vangipuram Janaki, Vinjamuri Aljawarneh, Shadi Kumar, P.V. Cheruvu, Aravind Information Technology Dept VNR VJIET Hyderabad India Computer Science and Engg Dept Vaagdevi College of Engineering Warangal India Software Engg Dept JUST Jordan Computer Science and Engg Dept Acharya Institute of Technology Bangalore India

ISBN: (纸本)9781450372121

Discovering time profiled temporal patterns from time stamped transaction datasets is addressed in our previous research works which includes proposing new support estimation techniques, similarity measures for computing similarity between temporal patterns. This paper proposes a novel approach for discovering temporal pattern by introducing the concept of data fusion w.r.t the temporal pattern tree. The tree is generated for each timeslot and then the trees obtained for individual timeslots are merged or fused to get the overall tree for the entire dataset. The concept of tree based data fusion helps to prune elements efficiently and well ahead during pattern mining process. A pruning function is also introduced in this paper to prune invalid temporal patterns. © 2019 Association for Computing Machinery. All rights reserved.

关键词： Data fusion

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