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D-type neuropeptide decorated AIEgen/RENP hybrid nanoprobes with light-driven ROS generation ability for NIR-Ⅱ fluorescence imaging-guided through-skull photodynamic therapy of gliomas

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Aggregate 2024年第1期5卷 185-195页

作者： Xuelu He Yuan Luo Yanying Li Yuanbo Pan Ryan T.K.Kwok Lulu He Xiaolin Duan Pengfei Zhang Aiguo Wu Ben Zhong Tang Juan Li Ningbo Key Laboratory of Biomedical Imaging Probe Materials and Technology Zhejiang International Cooperation Base of Biomedical Materials Technology and ApplicationChinese Academy of Sciences(CAS)Key Laboratory of Magnetic Materials and DevicesNingbo Cixi Institute of Biomedical EngineeringZhejiang Engineering Research Center for Biomedical MaterialsNingbo Institute of Materials Technology and EngineeringChinese Academy of SciencesNingboP.R.China Guangdong Key Laboratory of Nanomedicine Shenzhen Engineering Laboratory of Nanomedicine and NanoformulationsCAS-HK Joint Lab for BiomaterialsResearch Laboratory for Biomedical Optics and Molecular ImagingShenzhen Key Laboratory for Molecular ImagingCAS Key Lab for Health InformaticsShenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhenP.R.China Department of Chemistry Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration and Reconstruction and Institute for Advanced StudyThe Hong Kong University of Science and Technology(HKUST)KowloonP.R.China School of Science and Engineering Shenzhen Institute of Aggregate Science and TechnologyThe Chinese University of Hong KongShenzhenP.R.China

Glioma is one of the most common malignant tumors of the central nervous system,leading high mortality rates in ***-induced emission(AIE)photosensitizers-based photodynamic therapy(PDT)has emerged as a promising therapeutic strategy for least-invasive treatment of glioma,which involves local irradiation of the tumor using an external near-infrared(NIR)***,most AIE photosensitizers suffered from poorly penetration of the visible light excitation,bad spatiotemporal resolution in deep tissues and low efficient blood-brain barrier(BBB)crossing ability,which greatly limited the clinical practice of AIE photosensitizers for especially deep-seated brain tumor *** this work,we developed a multifunctional NIR-driven theranostic agent through hybrid of AIE photosensitizers TIND with rare-earth doping nanoparticles(RENPs)NaGdF4:Nd/Yb/Tm with up/down dual-mode conversion *** theranostic agent was further decorated with D-type neuropeptide DNPY for crossing BBB and targeting *** the 808-nm light irradiation,the down-conversion NIR-II luminescence could indicate the position glioma and the upconversion NIR-I luminescence could trigger the AIE photosensitizers producing reactive oxygen species to inhibit orthotopic glioma tumor growth in *** results demonstrate that the integration of Dtype neuropeptide,AIE photosensitizers and RENPs could be promising candidates for in vivo NIR-II fluorescence image-guided through-skull PDT treatments of brain tumors.

关键词： aggregation-induced emission D-type neuropeptide glioma photodynamic therapy rare-earth doping nanoparticles

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Palladium-free chemoselective probe for in vivo fluorescence imaging of carbon monoxide

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Chinese Chemical Letters 2024年第9期35卷 223-226页

作者： Gongcheng Ma Qihang Ding Yuding Zhang Yue Wang Jingjing Xiang Mingle Li Qi Zhao Saipeng Huang Ping Gong Jong Seung Kim Guangdong Key Laboratory of Nanomedicine Shenzhen Engineering Laboratory of Nanomedicine and NanoformulationsCAS-HK Joint Lab for BiomaterialsResearch Laboratory for Biomedical Optics and Molecular ImagingShenzhen Key Laboratory for Molecular ImagingCAS Key Lab for Health InformaticsShenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China University of Chinese Academy of Sciences Beijing 100049China Department of Chemistry Korea UniversitySeoul 02841South Korea School of Chemical Engineering Northwest UniversityXi’an 710069China Cancer Center Institute of Translational MedicineFaculty of Health SciencesUniversity of MacaoMacao 999078China State Key Laboratory of Fine Chemicals College of Materials Science and EngineeringShenzhen UniversityShenzhen 518060China

Carbon monoxide(CO)is a vital intracellular gas messenger known for its cytoprotective and homeostatic *** plays a pivotal role in a myriad of biological ***,the precise detection of CO is of paramount importance in unraveling the intricacies of pathological mechanisms and advancing the development of disease *** herein introduce NFCOP,a state-of-the-art near-infrared(NIR)turn-on fluorescence(FL)probe that has been meticulously designed for highly sensitive,swift and selective imaging of *** NFCOP response occurred rapidly with CO,within just 10 s,and the calculated detection limit for CO was determined to be 0.32μmol/*** investigations conducted at the cellular level and in vivo demonstrated that NFCOP possesses high sensitivity and selectivity for imaging CO.

关键词： Palladium-free Chemoselective probe Fluorescence imaging Carbon monoxide Near-infrared

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Two-color emissive AIEgens with anti-Kasha property for dual-organelle imaging and phototherapy

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Science China Chemistry 2024年第5期67卷 1740-1752页

作者： Pu Chen Guogang Shan Qingli Nie Yuting Yan Pengfei Zhang Zujin Zhao Hai-Tao Feng Ben Zhong Tang AIE Research Center Shaanxi Key Laboratory of PhytochemistryCollege of Chemistry and Chemical EngineeringBaoji University of Arts and SciencesBaoji 721013China Institute of Functional Material Chemistry and National&Local United Engineering Lab for Power Battery Faculty of ChemistryNortheast Normal UniversityChangchun 130024China College of Chemistry&Materials Science Northwest UniversityXi’an 710127China Guangdong Key Laboratory of Nanomedicine CAS-HK Joint Lab of BiomaterialsCAS Key Laboratory of Biomedical Imaging Science and SystemShenzhen Engineering Laboratory of Nanomedicine and NanoformulationsCAS Key Lab for Health InformaticsShenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen 518055China State Key Laboratory of Luminescent Materials and Devices Key Laboratory of Luminescence from Molecular Aggregates of Guangdong ProvinceSouth China University of TechnologyGuangzhou 510640China School of Science and Engineering Shenzhen Institute of Aggregate Science and TechnologyThe Chinese University of Hong KongShenzhen(CUHK-Shenzhen)Shenzhen 518172China

Despite the rapid development of probes for targeting single organelle, the construction of robust dual-organelle targeting probes with multicolor emission was rarely reported. Herein, two dual-emissive aggregation-induced emission luminogens(AIEgens)with donor-π-acceptor structures were designed and synthesized, namely QT-1 and QF-2. Both two AIEgens exhibited excitation wavelength-dependence defying the Kasha's rule, and could stain lipid droplets(LDs) and mitochondria in blue and red fluorescence, respectively. Moreover, thanks to the near-infrared emission and abundant reactive oxygen species(ROS) generation efficiency of QT-1, it was chosen as a photodynamic therapy agent to selectively kill cancer cells from normal cells. Upon light irradiation, an obvious decrease of mitochondrial membrane potential(MMP) and serious change of mitochondrial shape in cells were observed, which corresponded to the efficient inhibition of tumor growth in vivo. This work afforded a promising strategy for the construction of multicolor emission by tuning anti-Kasha behaviors and expanding their application in dualorganelle targeting-based phototheranostics.

关键词： aggregation-induced emission anti-Kasha luminescence fluorescent probe bioimaging photodynamic therapy

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Aggregation-induced emission (AIE) luminescent materials boosting optical storage into the new era of petabit-level capacity

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Aggregate 2024年第3期5卷 1-3页

作者： Siwei Zhang Pengfei Zhang Ben Zhong Tang Department of Chemistry Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration and ReconstructionThe Hong Kong University of Science and TechnologyHong KongChina Guangdong Key Laboratory of Nanomedicine CAS-HK Joint Lab of BiomaterialsCAS Key Laboratory of Biomedical Imaging Science and SystemShenzhen Engineering Laboratory of Nanomedicine and NanoformulationsCAS Key Lab for Health InformaticsShenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhenGuangdongChina School of Science and Engineering Shenzhen Institute of Aggregate Science and TechnologyThe Chinese University of Hong KongShenzhen(CUHK-Shenzhen)ShenzhenGuangdongChina

The recording of information stands as the most significant milestone in human ***,the recording and storage of information have undergone a technological evolution from paintings to carvings,scribing,and *** invention of optical compact discs(CDs)was one of the major landmarks in digital information *** the past half-century,scientists have endeavored to enhance optical storage capacity by improving both optical systems and optical storage materials,as shown in Scheme *** terms of commercial products,the storage capacity has increased from 700 MB(CDs)to 27 GB(Blu-ray discs)by optimizing the optical system based on the same optical storage medium(polycarbonate).To surpass the conventional optical diffraction limit,the optical systems have evolved from traditional lasers to nonlinear two-photon absorption(TPA)and stimulated emission depletion(STED),which has minified the laser spot size from microns to approximately tens of nanometers,marking a remarkable achievement.

关键词： aggregation-induced emission optical storage super disk

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Brilliant Green: A long-buried water-soluble AIEgen with nearinfrared fluorescence for living cell actin staining 3

Brilliant Green: A long-buried water-soluble AIEgen with nea...

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3rd International Conference on biomedical and Intelligent Systems, IC-BIS 2024

作者： Liu, Luxuan Wu, Yayun Tang, Dongbao Jia, Zhaoyuan Wang, Jiaoli Gong, Ping Fang, Xiaohong Tan, Yuyu Zhang, Pengfei School of Electrical Engineering Hunan Province Key Laboratory for Ultra-Fast Micro/Nano Technology and Advanced Laser Manufacture University of South China Hengyang421001 China Beijing National Research Center for Molecular Sciences Institute of Chemistry Key Laboratory of Molecular Nanostructure and Nanotechnology Chinese Academy of Science Beijing100190 China Guangdong Key Laboratory of Nanomedicine CAS-HK Joint Lab of Biomaterials CAS Key Laboratory of Biomedical Imaging Science and System Shenzhen Engineering Laboratory of Nanomedicine and Nanoformulations CAS Key Lab for Health Informatics Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China

ISBN: (纸本)9781510681279

Observation of actin in cells is crucial for the investigation of cell motility, protein transcription, pathogen infection, and cell cycle research. In this study, we have identified Brilliant Green (BG) as a water-soluble AIEgen (luminogen with aggregation-induced emission properties) that can be utilized for actin staining. Our experimental findings highlight the effectiveness of BG for long-term live cell imaging, as well as its remarkable stability and resistance to photobleaching. © 2024 SPIE.

关键词： Photobleaching

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Novel Genetic Loci Associated with PhenoAge Acceleration——Changzhou City, Jiangsu Province, China, 2012-2019

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China CDC weekly 2024年第49期6卷 1294-1298,I0004-I0006页

作者： Yifan Wang Yue Jiang Hui Wang Shuang Liang Muhammed Lamin Sambou Mei Wang Meiqi Yang Yakubu Salimata Feifei Xu Chenjie Li Xiao Wang Junpeng Yang Meng Zhu Cheng Wang Guangfu Jin Hongxia Ma Honggang Yi Hongbing Shen Juncheng Dai Department of Epidemiology Center for Global HealthSchool of Public HealthNanjing Medical UniversityNanjing CityJiangsu ProvinceChina State Key Laboratory of Reproductive Medicine Nanjing Medical UniversityNanjing CityJiangsu ProvinceChina China International Cooperation Center for Environment and Human Health Nanjing Medical UniversityNanjing CityJiangsu ProvinceChina State Key Lab of Cancer Biomarkers Prevention and TreatmentCollaborative Innovation Center for Cancer Personalized MedicineNanjing Medical UniversityNanjing CityJiangsu ProvinceChina The First School of Clinical Medicine Nanjing Medical UniversityNanjingChina Department of Bioinformatics School of Biomedical Engineering and InformaticsNanjing Medical UniversityNanjing CityJiangsu ProvinceChina Department of Biostatistics School of Public HealthNanjing Medical UniversityNanjing CityJiangsu ProvinceChina The Chinese Center for Disease Control and Prevention BeijingChina Jiangsu Life and Health Industry Academician Collaborative Innovation Center Nanjing CityJiangsu ProvinceChina

What is already known about this topic?China is rapidly encountering population aging,yet studies on aging are limited by the traditional aging measure:chronological age,particularly in the field of *** promising agin... 详细信息

关键词： measures evaluation Jiangsu

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FFPN: Fourier Feature Pyramid Network for Ultrasound Image Segmentation

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arXiv 2023年

作者： Chen, Chaoyu Yang, Xin Chen, Rusi Yu, Junxuan Du, Liwei Wang, Jian Hu, Xindi Cao, Yan Liu, Yingying Ni, Dong National-Regional Key Technology Engineering Laboratory for Medical Ultrasound School of Biomedical Engineering Health Science Center Shenzhen University China Lab Shenzhen University China Marshall Laboratory of Biomedical Engineering Shenzhen University China School of Biomedical Engineering and Informatics Nanjing Medical University China Shenzhen RayShape Medical Technology Co. Ltd China Shenzhen People's Hospital Second Clinical Medical College of Jinan University China

Ultrasound (US) image segmentation is an active research area that requires real-time and highly accurate analysis in many scenarios. The detect-to-segment (DTS) frameworks have been recently proposed to balance accuracy and efficiency. However, existing approaches may suffer from inadequate contour encoding or fail to effectively leverage the encoded results. In this paper, we introduce a novel Fourier-anchor-based DTS framework called Fourier Feature Pyramid Network (FFPN) to address the aforementioned issues. The contributions of this paper are two fold. First, the FFPN utilizes Fourier Descriptors to adequately encode contours. Specifically, it maps Fourier series with similar amplitudes and frequencies into the same layer of the feature map, thereby effectively utilizing the encoded Fourier information. Second, we propose a Contour Sampling Refinement (CSR) module based on the contour proposals and refined features produced by the FFPN. This module extracts rich features around the predicted contours to further capture detailed information and refine the contours. Extensive experimental results on three large and challenging datasets demonstrate that our method outperforms other DTS methods in terms of accuracy and efficiency. Furthermore, our framework can generalize well to other detection or segmentation tasks. Copyright © 2023, The Authors. All rights reserved.

关键词： Efficiency

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Fourier Test-time Adaptation with Multi-level Consistency for Robust Classification

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arXiv 2023年

作者： Huang, Yuhao Yang, Xin Huang, Xiaoqiong Zhou, Xinrui Chi, Haozhe Dou, Haoran Hu, Xindi Wang, Jian Deng, Xuedong Ni, Dong National-Regional Key Technology Engineering Laboratory for Medical Ultrasound School of Biomedical Engineering Health Science Center Shenzhen University China Lab Shenzhen University China Marshall Laboratory of Biomedical Engineering Shenzhen University China ZJU-UIUC Institute Zhejiang University China University of Leeds United Kingdom Shenzhen RayShape Medical Technology Co. Ltd China School of Biomedical Engineering and Informatics Nanjing Medical University China The Affiliated Suzhou Hospital of Nanjing Medical University China

Deep classifiers may encounter significant performance degradation when processing unseen testing data from varying centers, vendors, and protocols. Ensuring the robustness of deep models against these domain shifts is crucial for their widespread clinical application. In this study, we propose a novel approach called Fourier Test-time Adaptation (FTTA), which employs a dual-adaptation design to integrate input and model tuning, thereby jointly improving the model robustness. The main idea of FTTA is to build a reliable multi-level consistency measurement of paired inputs for achieving self-correction of prediction. Our contribution is two-fold. First, we encourage consistency in global features and local attention maps between the two transformed images of the same input. Here, the transformation refers to Fourier-based input adaptation, which can transfer one unseen image into source style to reduce the domain gap. Furthermore, we leverage style-interpolated images to enhance the global and local features with learnable parameters, which can smooth the consistency measurement and accelerate convergence. Second, we introduce a regularization technique that utilizes style interpolation consistency in the frequency space to encourage self-consistency in the logit space of the model output. This regularization provides strong self-supervised signals for robustness enhancement. FTTA was extensively validated on three large classification datasets with different modalities and organs. Experimental results show that FTTA is general and outperforms other strong state-of-the-art methods. Copyright © 2023, The Authors. All rights reserved.

关键词： Large dataset

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Flip Learning: Weakly Supervised Erase to Segment Nodules in Breast Ultrasound

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arXiv 2025年

作者： Huang, Yuhao Chang, Ao Dou, Haoran Tao, Xing Zhou, Xinrui Cao, Yan Huang, Ruobing Frangi, Alejandro F. Bao, Lingyun Yang, Xin Ni, Dong National-Regional Key Technology Engineering Laboratory for Medical Ultrasound School of Biomedical Engineering Shenzhen University Medical School Shenzhen University Shenzhen China Lab Shenzhen University Shenzhen China Marshall Laboratory of Biomedical Engineering Shenzhen University Shenzhen China School of Computing University of Leeds Leeds United Kingdom Shenzhen RayShape Medical Technology Co. Ltd Shenzhen China Division of Informatics Imaging and Data Science School of Health Sciences University of Manchester Manchester United Kingdom Department of Computer Science School of Engineering University of Manchester Manchester United Kingdom Department of Electrical Engineering Department of Cardiovascular Sciences KU Leuven Belgium Alan Turing Institute London United Kingdom NIHR Manchester Biomedical Research Centre Manchester Academic Health Science Centre Manchester United Kingdom Department of Ultrasound Affiliated Hangzhou First People’s Hospital School of Medicine Westlake University China School of Biomedical Engineering and Informatics Nanjing Medical University Nanjing China

Accurate segmentation of nodules in both 2D breast ultrasound (BUS) and 3D automated breast ultrasound (ABUS) is crucial for clinical diagnosis and treatment planning. Therefore, developing an automated system for nodule segmentation can enhance user independence and expedite clinical analysis. Unlike fully-supervised learning, weakly-supervised segmentation (WSS) can streamline the lab.rious and intricate annotation process. However, current WSS methods face challenges in achieving precise nodule segmentation, as many of them depend on inaccurate activation maps or inefficient pseudo-mask generation algorithms. In this study, we introduce a novel multi-agent reinforcement learning-based WSS framework called Flip Learning, which relies solely on 2D/3D boxes for accurate segmentation. Specifically, multiple agents are employed to erase the target from the box to facilitate classification tag flipping, with the erased region serving as the predicted segmentation mask. The key contributions of this research are as follows: 1) Adoption of a superpixel/supervoxel-based approach to encode the standardized environment, capturing boundary priors and expediting the learning process. 2) Introduction of three meticulously designed rewards, comprising a classification score reward and two intensity distribution rewards, to steer the agents’ erasing process precisely, thereby avoiding both under- and over-segmentation. 3) Implementation of a progressive curriculum learning strategy to enable agents to interact with the environment in a progressively challenging manner, thereby enhancing learning efficiency. Extensively validated on the large in-house BUS and ABUS datasets, our Flip Learning method outperforms state-of-the-art WSS methods and foundation models, and achieves comparable performance as fully-supervised learning algorithms. Copyright © 2025, The Authors. All rights reserved.

关键词： Reinforcement learning

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The cancer-testis gene,MEIOB,sensitizes triple-negative breast cancer to PARP1 inhibitors by inducing homologous recombination deficiency

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Cancer Biology & Medicine 2021年第1期18卷 74-87页

作者： Yayun Gu Cheng Wang Rongxuan Zhu Jianshui Yang Wenwen Yuan Yanhui Zhu Yan Zhou Na Qin Hongbing Shen Hongxia Ma Hongxia Wang Xiaoan Liu Zhibin Hu State Key Laboratory of Reproductive Medicine Center for Global HealthSchool of Public HealthNanjing Medical UniversityNanjing 211166China Jiangsu Key Lab of Cancer Biomarkers Prevention and TreatmentJiangsu Collaborative Innovation Center for Cancer Personalized MedicineNanjing Medical UniversityNanjing 211116China Department of Bioinformatics School of Biomedical Engineering and InformaticsNanjing Medical UniversityNanjing 211166China Department of Oncology Shanghai General HospitalShanghai Jiao Tong University School of MedicineShanghai 200080China Department of Breast Surgery The First Affiliated Hospital with Nanjing Medical UniversityNanjing 210029China

Objective:The newly defined cancer-testis(CT)gene,MEIOB,was previously found to play key roles in DNA double-strand break(DSB)*** this study,we aimed to investigate the effects and mechanisms of MEIOB in the carcinogenesis of triple-negative breast cancers(TNBCs).Methods:The Cancer Genome Atlas database was used to quantify the expression of *** regression analysis was used to evaluate the association between MEIOB expression and the prognosis of human *** effects of MEIOB on cell proliferation and migration in TNBCs were also assessed in ***-derived xenograft(PDX)models were used to assess the sensitivity of breast cancers with active MEIOB to PARP1 ***:We confirmed MEIOB as a CT gene whose expression was restricted to the testes and breast tumors,especially *** activation was significantly associated with poor survival in breast cancer patients[overall,hazard ratio(HR)=1.90(1.16–2.06);TNBCs:HR=7.05(1.16–41.80)].In addition,we found that MEIOB was oncogenic and significantly promoted the proliferation of TNBC *** analysis showed that MEIOB participated in DSB repair in ***,in contrast to its function in meiosis,it mediated homologous recombination deficiency(HRD)through the activation of poly ADP-ribose polymerase(PARP)1 by interacting with ***,activated MEIOB was shown to confer sensitivity to PARP inhibitors,which was confirmed in PDX ***:MEIOB played an oncogenic role in TNBC through its involvement in *** addition,dysregulation of MEIOB sensitized TNBC cells to PARP inhibitors,so MEIOB may be a therapeutic target of PARP1 inhibitors in TNBC.

关键词： Cancer-testis gene MEIOB triple-negative breast cancer PARP1 inhibitor cell proliferation

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