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Probing and Manipulating Noncovalent Interactions in Functional Polymeric Systems

CHEMICAL REVIEWS 2022年第18期122卷 14594-14678页

作者： chen, Jingsi Peng, Qiongyao Peng, xuwen Zhang, Hao Zeng, Hongbo Univ Alberta Dept Chem & Mat Engn Edmonton AB T6G 1H9 Canada

Noncovalent interactions, which usually feature tunable strength, reversibility, and environmental adaptability, have been recognized as driving forces in a variety of biological and chemical processes, contributing to the recognition between molecules, the formation of molecule clusters, and the establishment of complex structures of macromolecules. The marriage of noncovalent interactions and conventional covalent polymers offers the systems novel mechanical, physicochemical, and biological properties, which are highly dependent on the binding mechanisms of the noncovalent interactions that can be illuminated via quantification. This review systematically discusses the nano mechanical characterization of typical noncovalent interactions in polymeric systems, mainly through direct force measurements at microscopic, nanoscopic, and molecular levels, which provide quantitative information (e.g., ranges, strengths, and dynamics) on the binding behaviors. The fundamental understandings of intermolecular and interfacial interactions are then correlated to the macroscopic performances of a series of noncovalently bonded polymers, whose functions (e.g., stimuli-responsiveness, self-healing capacity, universal adhesiveness) can be customized through the manipulation of the noncovalent interactions, providing insights into the rational design of advanced materials with applications in biomedical, energy, environmental, and other engineering fields.

关键词： Ligands Molecular mechanics Noncovalent interactions Polymers Surface interactions

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ConTra: A Covert Timing Channel Detection Approach for Little Covert Information in a Network 23

ConTra: A Covert Timing Channel Detection Approach for Littl...

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4th International Conference on Computing, Networks and Internet of Things, CNIOT 2023

作者： Li, Zhiqiang chen, Yonghong Teng, Zhan Huang, xuwen School of Computer Science and Technology Huaqiao University Xiamen Fujian China Xiamen Key Laboratory of Data Security and Blockchain Technology Huaqiao University Xiamen Fujian China

ISBN: (纸本)9798400700705

A covert timing channel is a technical means that enables information hiding and covert communication. Due to the fact that covert timing channels can elude detection by security defence measures, they offer a substantial security risk to the information of Internet users when they are exploited for illicit reasons. The attacker sends at a low rate to ensure the stealthiness of the covert timing channel communication process, making the number of inter-arrival time encoded as covert information much less than the normal number of inter-arrival time, resulting in the low detection accuracy of existing detection methods. In this paper, we propose a covert timing channel detection method based on one-dimensional convolution and self-attention mechanism. The method begins with local feature extraction of the input inter-arrival time sequence by a one-dimensional convolutional layer, then characterizes the correlation between each inter-arrival time by a self-attention mechanism in the encoder, and finally through the full connection layer to produce the type output. In this study, experimental results on a public dataset and 16 self-built datasets demonstrate that the detection method delivers optimal detection results and efficient detection of covert information in low-volume communications. © 2023 ACM.

关键词： Optimal detection

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Study on the differences of low carbon development models for energy and power supply in different types of enterprise parks 3

Study on the differences of low carbon development models fo...

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3rd International Conference on Energy, Power and Electrical Technology, ICEPET 2024

作者： Yan, xuwen Hao, Weitao chen, Liping Wang, Wenxiu Lu, Juntong Guangzhou Power Supply Bureau of Guangdong Power Grid Co. Ltd Guangdong Guangzhou510620 China Chinese Academy of Sciences Guangzhou Institute of Energy Conversion Guangdong Guangzhou510642 China Shenyang University of Chemical Technology School of Mechanical and Power Engineering Liaoning Shenyang110142 China University of Science and Technology of China School of Energy Science and Engineering Anhui Hefei230026 China

ISBN: (纸本)9798350352658

As the main entities of undertaking the intensive energy activities, the green and low-carbon development of the enterprise parks is one of the important means to achieve the "dual carbon"targets. Taking two different types of parks, an industrial park and a research and technology park, in Guangzhou as the research objects, using Homer software and taking the minimum total net present value as the objective function, this study carried out the capacity optimization for different scenarios in order to optimize the allocation and analysis of low-carbon energy and electricity development plans for the two different types of enterprise parks. The results showed that: (1) for enterprise parks, fully utilizing renewable energy and equipping energy storage systems could effectively improve the economic and low-carbon efficiency of the energy system, while making use of the excessive power with electricity to heat conversion technology did not have significant effect. (2) Due to the intensive nature of land use, the enterprise parks were unable to adopt renewable energy sources on a large scale, resulting in an increase of unit cost of power supply. Compared with the research and technology parks, the industrial parks still have potential to make further improvement in economic efficiency. © 2024 IEEE.

关键词： Carbon capture and utilization

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Metabolic Nanoregulators Induce Ferroptosis and Change Metabolite Flow to Reverse Immunosuppressive Tumor Microenvironment

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ACS NANO 2024年第51期18卷 34996-35012页

作者： Wang, Yu chen, Qinjun Luo, Yifan Qu, Yangqi Li, xuwen Song, Haolin Li, Chufeng Zhang, Yiwen Sun, Tao Jiang, chen Fudan Univ Key Lab Smart Drug Delivery State Key Lab Med Neurobiol Dept PharmaceutSch PharmInst Brain SciMinist Ed Shanghai 201203 Peoples R China MOE Frontiers Ctr Brain Sci Shanghai 201203 Peoples R China Fujian Med Univ Affiliated Hosp 1 Natl Reg Med Ctr Dept Digest Dis Binhai Campus Fuzhou 350212 Peoples R China

Aberrant energy and substance metabolic pathways of tumor cells critically support tumor cell proliferation by hijacking the resources from nonmalignant cells, thereby establishing a metabolite flow favorable to tumor progression. This metabolic adaptation of tumor cells further modulates the immune landscape, ultimately creating a tumor microenvironment characterized by drug resistance and immunosuppression. The synergistic regulation of energy and substance metabolic pathways might be a good antitumor therapeutic paradigm. However, due to the metabolic convergence, it is crucial to selectively modulate the aberrant metabolism of tumor cells without compromising the functionality of other cells. Small-molecule drugs have the ability to target a wide range of biomolecules for antitumor therapy, but their application is limited by undesirable toxicities. Constructing nanodrug delivery systems can improve their properties and allow for the inclusion of multiple drugs, thereby exerting synergistic antitumor effects. In this study, we developed a two-drug codelivery system using drugs-conjugated multibranched polymers to modulate tumor cell metabolism by exploiting synthetic lethal pathways for safe and effective antitumor therapy. By delivery of adapalene and erastin simultaneously through nanoparticles, the material and energy metabolism of tumor cells can be regulated. This nanoparticle construction achieves tumor tissue targeting and responsive drug release, alters metabolite flow within tumor cells, and effectively kills tumor cells. Additionally, the nanoparticles can reverse the tumor immunosuppressive microenvironment, starting from single-cell regulation to whole-lesion control.

关键词： metabolic nanoregulators metabolite flow ferroptosis immunosuppression multibranched polymers

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Intelligent Delivery Systems in Tumor Metabolism Regulation: Exploring the Path Ahead

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ADVANCED MATERIALS 2024年第11期36卷 2309582-2309582页

作者： Li, xuwen Sun, Tao Jiang, chen Fudan Univ Sch Pharm Dept Pharmaceut Minist EducKey Lab Smart Drug Delivery Shanghai 201203 Peoples R China MOE Frontiers Ctr Brain Sci Shanghai 201203 Peoples R China

Cancer metabolism plays multifaceted roles in the initiation and progression of tumors, and interventions in metabolism are considered fundamental approaches for cancer control. Within the vast metabolic networks of tumors, there exist numerous potential therapeutic targets, intricately interconnected with each other and with signaling networks related to immunity, metastasis, drug resistance, and more. Based on the characteristics of the tumor microenvironment, constructing drug delivery systems for multi-level modulation of the tumor microenvironment is proven as an effective strategy for achieving multidimensional control of cancer. Consequently, this article summarizes several features of tumor metabolism to provide insights into recent advancements in intelligent drug delivery systems for achieving multi-level regulation of the metabolic microenvironment in cancer, with the aim of offering a novel paradigm for cancer treatment. Latest advancements in intelligent drug delivery systems (DDS) exhibit distinctive advantages, including precise sensing, programmability, feedback control, and intrinsic activity. These attributes render them conducive to facilitating multi-dimensional therapeutic approaches grounded in metabolic ***

关键词： intelligent delivery systems metabolism regulation nanomedicine tumor metabolism

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Development and validation of a predictive model for metabolic syndrome in a large cohort of people living with HIV

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VIROLOGY JOURNAL 2024年第1期21卷 1-12页

作者： chen, Suling Xu, Yuyuan Jiang, Yuanhui chen, Hongjie Wu, Xiaoxuan Qian, Zhe Xu, xuwen Zhong, Huiqun Peng, Jie Cai, Shaohang Southern Med Univ Nanfang Hosp Dept Infect Dis Guangzhou 510515 Peoples R China Minist Educ Key Lab Infect Dis Res South China Guangzhou Peoples R China Haizhu Dist Ctr Dis Control & Prevent Dept Communicable & Endem Dis Control & Prevent Guangzhou Peoples R China Guangdong Acad Med Sci Guangdong Prov Peoples Hosp Guangdong Prov Geriatr Inst Dept Elderly Resp 2 Guangzhou Peoples R China

BackgroundThe global prevalence of metabolic syndrome (MetS) in people living with HIV (PLWH) is on the rise in the post era of antiretroviral therapy (ART). Nevertheless, there are no validated predictive models available for assessing the risk of MetS in this specific *** study included PLWH who participated in annual follow-ups at Southern Medical University Nanfang Hospital from September 2022 to November 2023. Participants enrolled in this study were divided into the training set and validation set based on the follow-up duration. We employed both multivariate logistic regression and lasso regression to develop three distinct prediction models. Subsequently, the optimal model was determined through comprehensive analyses, including receiver operating characteristic (ROC) curve analysis, calibration curve, and decision curve analysis (DCA). Ultimately, we generated a nomogram for the optimal model and analyzed the correlation between the model score and the components of *** total of 1017 participants were included in this study, with 814 in the training set and 203 in the validation set. The ultimate prediction model of MetS risk in PLWH incorporated five factors: age, CD8 + T cell counts, controlled attenuation parameter (CAP), gamma-glutamyl transferase (gamma-GT) and lactate dehydrogenase (LDH). The area under the ROC curve (AUC) of the model in the training set and validation set was 0.849 and 0.834, respectively. Furthermore, we revealed a significant correlation between the model score and the MetS components. Additionally, the model score revealed significant group differences in MetS and related metabolic *** study established a potential model for predicting MetS in PLWH.

关键词： HIV/AIDS Metabolic syndrome Clinical prediction model Nomogram Clinical endocrinology

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Fluorescence imaging analysis of the glioma microenvironment

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Journal of Innovative Optical Health Sciences 2023年第1期16卷 55-66页

作者： xuwen Peng Yuzhou chen Yuke Wang Shuhong Qi Britton Chance Center for Biomedical Photonics Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology Wuhan Hubei 430074P.R.China MoE Key Laboratory for Biomedical Photonics School of Engineering Sciences Huazhong University of Science and Technology Wuhan Hubei 430074P.R.China

Glioma is the most malignant brain *** neurons,macrophages,T cells and other immune ellls constitute the glioma immunosuppressive *** accurate spatial distri-bution of these cells in the glioma microenvironment and its relationship with glioma metastasis is *** constructed a mouse gliomna cell line stably expressing the large Stokes shifted yellow fluorescent protein and applied it to the multicolor immunofluorescence *** inaging data revealed that the neurons were sparsely distributed in the glioma core and the mumber of neurons decreased by 90%compared with normal brain *** spatial distribution of monocyte-macrophages and microglia is *** monocyte macrophages and T cells were heavily recrnuited into the glioma core and *** was no significant difference in the distribution of microglia amnong glioma core,margin,and normal brain *** results provided new perspectives for targeting immune regulation cells and developing new immuno-therapy strategies for glioma.

关键词： Glioma microenvironment spatial distribution heterogeneity multicolor immuno-fluorescence large Stokes-shifted fluorescent protein.

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Estimated Pulse Wave Velocity as a Novel Non-Invasive Biomarker for Metabolic Syndrome Among People Living with HIV

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DIABETES METABOLIC SYNDROME AND OBESITY 2024年 17卷 1999-2010页

作者： chen, Suling Jiang, Yuanhui Lin, Xiaoli chen, Hongjie Wu, Xiaoxuan Qian, Zhe Xu, xuwen Zhong, Huiqun Peng, Jie Cai, Shaohang Southern Med Univ Nanfang Hosp Dept Infect Dis Guangzhou 510515 Peoples R China Haizhu Dist Ctr Dis Control & Prevent Dept Communicable & Endem Dis Control & Prevent Guangzhou Peoples R China Guangdong Acad Med Sci Guangdong Prov Peoples Hosp Guangdong Prov Geriatr Inst Dept Elderly Resp 2 Guangzhou Peoples R China

Purpose: This study aims to investigate the relationship between estimated pulse wave velocity (ePWV) and metabolic syndrome (MetS) in people living with HIV (PLWH), proposing a novel and convenient predictor for early detection of MetS in PLWH. Patients and Methods: A total of 485 PLWH were enrolled. These participants were categorized into two groups based on the estimated pulse wave velocity (ePWV) level. Demographic and clinical data were collected to investigate the correlation between ePWV and MetS. Results: The cohort of 485 PLWH was categorized into high-ePWV and low-ePWV groups based on ePWV cutoff value of 10 m/s. We observed significant differences in components of MetS including triglycerides (TG, P < 0.05), HDL cholesterol (HDL-C, P < 0.01), systolic blood pressure (SBP, P < 0.001), diastolic blood pressure (DBP, P < 0.05), and fasting plasma glucose (FPG, P < 0.001) between the two groups. Furthermore, we employed receiver operating characteristic (ROC) curves to demonstrate the effectiveness of ePWV as a predictive indicator for MetS in PLWH (AUC = 0.739, P < 0.001). According to the ROC curve, the optimal cut-off value of ePWV was 7.4 m/s, and its sensitivity and specificity in diagnosing MetS in PLWH were 79.03% and 64.07%, respectively. Although the 7.4 m/s cutoff increased the false positive rate compared to the traditional cutoff, it significantly reduced the rate of missed diagnoses, effectively identifying 79.03% of PLWH with MetS. Conclusion: ePWV is a non-invasive and convenient novel biomarker with predictive capabilities for MetS in PLWH.

关键词： HIV/AIDS highly active antiretroviral therapy metabolic syndrome estimated pulse wave velocity

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Short-term photovoltaic power prediction based on VMD-SSA-LSTM

Short-term photovoltaic power prediction based on VMD-SSA-LS...

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2024 International Conference on Optoelectronic Information and Functional Materials, OIFM 2024

作者： Zhang, Tingyi Li, Shaowu chen, Jinbiao Liu, xuwen Guo, Weihao College of Intelligent Systems Science and Engineering Hubei Minzu University Enshi445000 China

ISBN: (纸本)9781510680517

Photovoltaic power prediction is crucial for maintaining the safe, stable operation, and economic benefits of the power grid. However, the long short-term memory (LSTM) neural network faces limitations in parameter selection, affecting its effectiveness in photovoltaic power prediction. Additionally, photovoltaic power data exhibits volatility and non-stationarity, leading to inaccurate predictions. To address these issues, this paper proposes a coupled model named VMD-SSA-LSTM, which combines variational mode decomposition (VMD), sparrow search algorithm (SSA), and LSTM. The model initially employs VMD to decompose photovoltaic power data, reducing the impact of volatility and non-stationarity on prediction results. Subsequently, SSA is used to optimize LSTM parameters. Finally, the predicted values from each sequence are summed to obtain the photovoltaic power prediction. Simulation experiments demonstrate the model's high adaptability in short-term photovoltaic power prediction. Compared to the LSTM model, the VMD-SSA-LSTM model exhibits superior performance in prediction accuracy, stability, and robustness. Therefore, this model provides an effective solution to enhance the accuracy of photovoltaic power prediction, contributing to the safety, stability, and economic efficiency of power grid operation. © 2024 SPIE.

关键词： Variational mode decomposition

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Detection of Network Time Covert Channels Based on Image Processing 23

Detection of Network Time Covert Channels Based on Image Pro...

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4th International Conference on Computing, Networks and Internet of Things, CNIOT 2023

作者： Huang, xuwen chen, Yonghong Li, Zhiqiang Zhan, Teng School of Computer Science and Technology Huaqiao University Xiamen Fujian China Xiamen Key Laboratory of Data Security and Blockchain Technology Huaqiao University Xiamen Fujian China

ISBN: (纸本)9798400700705

Network covert timing channels (NCTCs) utilize Inter-Packet Delay (IPD) encoding to hide data. It can be used for spreading malware and data leakage, posing severe threats to network security. With the increasing risk, the research on NCTC detection has become an important and urgent task. However, the detection methods based on IPD statistics are only effective for few types of channels and require large IPD sampling samples. The recent ML-based detection methods have multiple limitations due to their coarse-grained feature extraction method. In this paper, we propose a multi-channel image transformation method for extracting IPD features and select the lightweight network MobileVit for detection. We encode IPD one-dimensional time-series data into Gramian Angular Field (GAF), Markov Transition Field (MTF), and Recurrence plot (RP) images and stack them into dual-channel and three-channel images. After image transformation, we compare mainstream image classification networks and a self-built CNN. Experimental results show that our feature extraction image classification is more effective than the existing IPD extraction image transformation method. The MobileVit network shows better detection performance and accuracy, requiring fewer IPD sampling samples for detection windows. © 2023 ACM.

关键词： Sampling

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