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p53 promotes AKT and SP1-dependent metabolism through the pentose phosphate pathway that inhibits apoptosis in response to Nutlin-3a

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Journal of Molecular Cell Biology 2018年第4期10卷 331-340页

作者： text lei dua. Ricardo E. Perez Ling Chen Lothar A. Blatter Carl G. Maki Department of Cell & Molecular Medicine Rush University Medical Center Chicago IL 60612 USA Department of Laboratory Medicine Shiyan Taihe Hospital College of Biomedical Engineering Hubei University of Medicine Shiyan 442000 China Department of Physiology & Biophysics Rush University Medical Center Chicago IL 60612 USA

Nutlin-3a is a MDM2 antagonist and preclinical drug that activates p53. Cells with MDM2 gene amplification are especially prone to Nutlin-3a-induced apoptosis, though the basis for this is unclear. Glucose metabolism can inhibit apoptosis in response to Nutlin-3a through mechanisms that are incompletely understood. Glucose metabolism through the pentose phosphate pathway （PPP） produces NADPH that can protect cells from potentially lethal reactive oxygen species （ROS）. We compared apoptosis and glucose metabolism in cancer cells with and without MDM2 gene amplification treated with Nutlin-3a. Apoptosis in MDM2-amplified cells was associated with a reduction in glycolysis and the PPP, reduced NADPH, increased ROS, and depletion of the transcription factor SP1, which normally promotes PPP gene expression. In contrast, glycolysis and the PPP were maintained or increased in MDM2 non-amplified cells treated with Nutlin-3a. This was dependent on p53-mediated AKT activation and was associated with maintenance of SP1 and continued expression of PPP genes. Knockdown or inhibition of AKT, SP1, or the PPP sensitized MDM2-non-amplified cells to apoptosis. The data indicate that p53 promotes AKT and SP1-dependent activation of the PPP that protects cells from Nutlin-3a-induced apoptosis. These findings provide insight into how glucose metabolism reduces Nutlin-3a-induced apoptosis, and also provide a mechanism for the heightened sensitivity of MDM2-amplified cells to apoptosis in response to Nutlin-3a.

关键词： Nutlin p53 MDM2 SP1 glycolysis pentose phosphate pathway

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阿列克谢耶夫《聊斋志异》译本的译者行为批评分析

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外语学刊 2025年第1期 92-98页

作者：雷丽斯黑龙江大学高级翻译学院哈尔滨150080

《聊斋志异》是我国古代短篇小说的艺术丰碑,由苏联汉学家阿列克谢耶夫完成的俄语选译本在俄罗斯完成经典化。本文以阿列克谢耶夫译本为例,运用文本细读法,从翻译内外二分化视野,对译者行为进行批评分析。研究发现,在翻译外层面上,译者... 详细信息

《聊斋志异》是我国古代短篇小说的艺术丰碑,由苏联汉学家阿列克谢耶夫完成的俄语选译本在俄罗斯完成经典化。本文以阿列克谢耶夫译本为例,运用文本细读法,从翻译内外二分化视野,对译者行为进行批评分析。研究发现,在翻译外层面上,译者身份、译者与作者之间的“知己关系”等因素促使译者行为偏向作者/原文一端;在翻译内层面上,译者运用多种翻译手段最大限度地实现了对作者/原文的求真,同时在求真的基础上,使译文对读者/社会务实,译者行为合理度较佳。

关键词：译者行为批评《聊斋志异》阿列克谢耶夫译者行为典籍翻译

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融合前缀调优和提示学习的仇恨言论检测方法

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计算机科学与探索 2025年第1期19卷 97-106页

作者：徐磊胡亚豪陈满陈军潘志松中国人民解放军陆军工程大学指挥控制工程学院南京210000

随着网络社交平台的发展,网络暴力的危害性日益凸显,其中仇恨言论作为网络暴力的一种表现形式,对其检测方法的研究有助于构建一个健康的互联网环境。然而,一方面先前的仇恨言论检测方法主要依赖于人工监管和关键词过滤,这些方法存在人... 详细信息

随着网络社交平台的发展,网络暴力的危害性日益凸显,其中仇恨言论作为网络暴力的一种表现形式,对其检测方法的研究有助于构建一个健康的互联网环境。然而,一方面先前的仇恨言论检测方法主要依赖于人工监管和关键词过滤,这些方法存在人工成本高且分类效果不佳的问题;另一方面,在互联网平台的监管下,仇恨言论的表达也变得更加含蓄、隐蔽,这对检测模型的文本理解能力提出了更高的要求。以ChatGPT为代表的大模型为仇恨言论检测任务提供了新的可能性,受其在各项下游任务中出色表现的启发,提出了一种融合前缀调优和提示学习的仇恨言论检测方法P-Prompt。利用前缀调优方法将大模型在相关数据集上进行微调,同时结合提示学习方法使模型能够识别并关注待检测文本中的仇恨言论词汇,从而进一步提升模型对仇恨言论的识别能力。实验结果验证了大模型在仇恨言论检测任务的有效性,与传统方法相比P-Prompt方法在仇恨言论检测的二分类和多分类任务中各项评价指标都取得了较明显的提升。

关键词：仇恨言论检测大语言模型前缀调优提示学习

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Exploring the metallurgical coke thermal properties in viewpoint of experiment and molecular simulation

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CHINESE JOURNAL OF CHEMICAL ENGINEERING 2024年第11期75卷 253-265页

作者： lei, Zhao Yue, Qiannan Pei, Qin Chen, Ji Ling, Qiang lei, Liu Zhu, Gangli Cui, Ping Anhui Univ Technol Sch Chem & Chem Engn Anhui Key Lab Coal Clean Convers & Utilizat Maanshan 243002 Peoples R China Wanjiang Univ Technol Sch Finance & Econ Maanshan 243002 Peoples R China Shanxi Design & Res Inst Bldg Mat Ind Xian 710032 Peoples R China Chinese Acad Sci Suzhou Res Inst LICP Lanzhou Inst Chem Phys LICP State Key Lab Oxo Synth & Select Oxidat Lanzhou 730000 Peoples R China

The Chinese standard method of GB/T 4000-2017 was unable to accurately measure the coke thermal properties in the large blast furnace. Therefore, the coke compressive strength (CCS) test at a high temperature was designed to examine the coke thermal properties. Then, the large-scale coke model (sp2C17421sp3C6579) was established. After, the ReaxFF molecular dynamics simulations were implemented to mimic the coke solution loss (CSL) and the CCS at the high temperature. It was found that the adsorption energy and the diffusion energy of micropores were greater than those of mesopores and macropores, indicating that the CSL reaction mainly happened in the coke micropore. It was discovered that the CSL reaction mechanism was the sp3 C oxidization mechanism with the transient state of ketene structure. And, it was detected that the CCS process was divided into the plastic deformation, the instantaneous fracture and the elastic deformation and yield, which was caused by the local reconstruction, the overall folding and the center stretching of carbon layer, respectively. By comparing simulated results with experiments, it was proved that obtained mechanisms were valid. The proposed experimental and simulated methods provided a novel method to measure and understand the coke thermal properties. (c) 2024 The Chemical Industry and Engineering Society of China, and Chemical Industry Press Co., Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

关键词： Coke model ReaxFF MD Coke solution loss Coke fracture

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Max-difference maximization criterion: a feature selection method for text categorization

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Frontiers of Computer Science 2023年第1期17卷 237-239页

作者： Lingbin JIN Li ZHANG lei ZHAO School of Computer Science and Technology&Advanced Data Analysis Research Center Soochow UniversitySuzhou 215006China

1 Introductiontext categorization methods based on machine learning always encounter the curse of dimensionality. Therefore, it is crucial to perform feature selection to reduce dimensionality of text vectors. Methods based on the difference between document rate of a term in the positive class and that in the negative class have been widely studied in recent years, which is originated from balanced accuracy measures (ACC2) [1].

关键词： dimensionality difference criterion

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Feature-Grounded Single-Stage text-to-Image Generation

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Tsinghua Science and Technology 2024年第2期29卷 469-480页

作者： Yuan Zhou Peng Wang lei Xiang Haofeng Zhang School of Artificial Intelligence Nanjing University of Information Science and TechnologyNanjing 210044China School of Computer Science and Engineering Nanjing University of Science and TechnologyNanjing 210094China

Recently,Generative Adversarial Networks(GANs)have become the mainstream text-to-image(T2I)***,a standard normal distribution noise of inputs cannot provide sufficient information to synthesize an image that approaches the ground-truth image ***,the multistage generation strategy results in complex T2I ***,this study proposes a novel feature-grounded single-stage T2I model,which considers the“real”distribution learned from training images as one input and introduces a worst-case-optimized similarity measure into the loss function to enhance the model's generation *** results on two benchmark datasets demonstrate the competitive performance of the proposed model in terms of the Frechet inception distance and inception score compared to those of some classical and state-of-the-art models,showing the improved similarities among the generated image,text,and ground truth.

关键词： text-to-image(T2I) feature-grounded single-stage generation Generative Adversarial Network(GAN)

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A fuzzy compensation-Koopman model predictive control design for pressure regulation in proten exchange membrane electrolyzer

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CHINESE JOURNAL OF CHEMICAL ENGINEERING 2024年第12期76卷 251-263页

作者： Xiong, Haokun Xie, lei Hu, Cheng Su, Hongye Zhejiang Univ State Key Lab Ind Control Technol Hangzhou 310027 Peoples R China

Proton exchange membrane (PEM) electrolyzer have attracted increasing attention from the industrial and researchers in recent years due to its excellent hydrogen production performance. Developing accurate models to predict their performance is crucial for promoting and accelerating the design and optimization of electrolysis systems. This work developed a Koopman model predictive control (MPC) method incorporating fuzzy compensation for regulating the anode and cathode pressures in a PEM electrolyzer. A PEM electrolyzer is then built to study pressure control and provide experimental data for the identification of the Koopman linear predictor. The identified linear predictors are used to design the Koopman MPC. In addition, the developed fuzzy compensator can effectively solve the Koopman MPC model mismatch problem. The effectiveness of the proposed method is verified through the hydrogen production process in PEM simulation. (c) 2024 The Chemical Industry and Engineering Society of China, and Chemical Industry Press Co., Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

关键词： Hydrogen production PEM electrolyzer Nonlinear control Model predictive control Koopman operator Fuzzy logic system

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Topic-sensitive neural headline generation

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Science China(Information Sciences) 2020年第8期63卷 180-195页

作者： Ayana Ziyun WANG lei XU Zhiyuan LIU Maosong SUN State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and TechnologyDepartment of Computer Science and TechnologyTsinghua University Department of Computer Information Management Inner Mongolia University of Finance and Economics

Neural models are being widely applied for text summarization, including headline generation,and are typically trained using a set of document-headline pairs. In a large document set, documents can usually be grouped into various topics, and documents within a certain topic may exhibit specific summarization patterns. Most existing neural models, however, have not taken the topic information of documents into consideration. This paper categorizes documents into multiple topics, since documents within the same topic have similar content and share similar summarization patterns. By taking advantage of document topic information, this study proposes a topic-sensitive neural headline generation model(TopicN HG). It is evaluated on a real-world dataset, large scale Chinese short text summarization dataset. Experimental results show that it outperforms several baseline systems on each topic and achieves comparable performance with the state-of-the-art system. This indicates that TopicN HG can generate more accurate headlines guided by document topics.

关键词： neural networks sequence to sequence learning topic LDA headline generation

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Research on sentiment terms extraction and visualization of character sentimental interactions in A Dream of Red Mansions

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The Journal of China Universities of Posts and Telecommunications 2022年第2期29卷 24-32页

作者： Huang Pei Zhang Meng Wan Liu lei Xuanzheng School of Digital Media and Design Arts Beijing University of Posts and TelecommunicationsBeijing 100876China School of Information and Communication Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China Beijing Key Laboratory of Network System and Network Culture Beijing University of Posts and TelecommunicationsBeijing 100876China School of Electronic Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China

In the context of interdisciplinary research,using computer technology to further mine keywords in cultural texts and carry out semantic analysis can deepen the understanding of texts,and provide quantitative support and evidence for humanistic *** on the novel A Dream of Red Mansions,the automatic extraction and classification of those sentiment terms in it were realized,and detailed analysis of large-scale sentiment terms was carried *** encoder representation from transformers(BERT) pretraining and fine-tuning model was used to construct the sentiment classifier of A Dream of Red *** terms of A Dream of Red Mansions are divided into eight sentimental categories,and the relevant people in sentences are extracted according to specific *** also tries to visually display the sentimental interactions between Twelve Girls of Jinling and Jia Baoyu along with the development of the *** overall F_(1) score of BERT-based sentiment classifier reached 84.89%.The best single sentiment score reached 91.15%.Experimental results show that the classifier can satisfactorily classify the text of A Dream of Red Mansions,and the text classification and interactional analysis results can be mutually verified with the text interpretation of A dream of Red Mansions by literature experts.

关键词： A Dream of Red Mansions sentiment term extraction character sentiment interaction bidirectional encoder representation from transformers(BERT) data visualization

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WordleNet: A Visualization Approach for Relationship Exploration in Document Collection

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Tsinghua Science and Technology 2020年第3期25卷 384-400页

作者： Xu Wang Zuowei Cui lei Jiang Wenhuan Lu Jie Li the College of Intelligence and Computing

Document collections do not only contain rich semantic content but also a diverse range of *** propose WordleNet,an approach to supporting effective relationship exploration in document *** approaches mainly focus on semantic similarity or a single category of *** constructing a general definition of document relationships,our approach enables the flexible and real-time generation of document relationships that may not otherwise occur to human researchers and may give rise to interesting patterns among *** novel visual components are integrated in our approach,the effectiveness of which has been verified through a case study,a comparative study,and an eye-tracking experiment.

关键词： document relationship interaction techniques text visualization relationship visualization visual analytics

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