Review
Physics, Multidisciplinary
Jun Qian, Zhe Feng, Xiaoxiao Fan, Andrey Kuzmin, Anderson S. L. Gomes, Paras N. Prasad
Summary: Biophotonics is a multidisciplinary field that integrates various disciplines for optical diagnostics, bioimaging, and light activated therapies. It plays an important role in molecular medicine and provides detailed information at the subcellular level through non-invasive and radiation-free approaches.
PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS
(2022)
Review
Chemistry, Multidisciplinary
Hui Li, Xin Wang, Tymish Y. Ohulchanskyy, Guanying Chen
Summary: Light in the near-infrared (NIR) spectral region is increasingly used in bioapplications due to its deeper penetration in biological tissues. Lanthanide-doped luminescent nanoparticles with excitation and/or emission in the NIR range are gaining attention for noninvasive biological applications, offering unique optical properties such as large Stokes shift, sharp luminescence emissions, long lifetimes, and photostability. Advanced strategies for enhancing the luminescence brightness of these nanoparticles have been introduced, along with a review of their superior biophotonic applications in high-resolution imaging, single-nanoparticle-level detection, and tissue-penetrating diagnostics and therapeutics.
ADVANCED MATERIALS
(2021)
Article
Chemistry, Multidisciplinary
Shreyas Shah, Chun-Nam Yu, Mingde Zheng, Heejong Kim, Michael S. Eggleston
Summary: Advancing continuous health monitoring to include biochemistry using microparticle-based biosensors and optical coherence tomography was explored in this study. The design of stimuli-responsive polymeric microparticles allowed for detection of volumetric changes in response to target biochemicals, and analytical approaches using OCT enabled estimations below system resolution. The study demonstrated successful 3D spatiotemporal monitoring of glucose-responsive microparticles in a tissue mimic, with potential for automated processing using deep learning for continuous in vivo biochemical monitoring.
Article
Chemistry, Multidisciplinary
Jingsheng Huang, Chi Zhang, Xinzhu Wang, Xin Wei, Kanyi Pu
Summary: There is a growing interest in developing chemiluminescence (CL) probes for phototheranostics, which can minimize tissue autofluorescence. However, the lack of near-infrared (NIR)-absorbing chemiluminophores has led to the use of nanoparticle-based probes for NIR CL-guided phototherapy. This study introduces bright unimolecular chemiluminophores with NIR absorptions and emissions, long CL half-lives, and optimal photodynamic efficiency. One of these luminophores, DBPOL, is modified into an activatable probe that exhibits a turn-on CL signal and photodynamic activity specific to a cancer biomarker. The highly sensitive DBPOL allows for CL-guided photodynamic therapy, effectively inhibiting tumor growth and lung metastasis in mouse models, and enabling noninvasive monitoring of lung metastasis. Molecular guidelines for NIR-absorbing CL probes for imaging-guided phototherapy are provided.
ANGEWANDTE CHEMIE-INTERNATIONAL EDITION
(2023)
Article
Chemistry, Multidisciplinary
Hao Zhao, Xiushang Xu, Long Zhou, Yunbin Hu, Yiming Huang, Akimitsu Narita
Summary: This study presents a promising helicene-based phototherapeutic agent for organelle-targeted biotherapy involving both type I and II photodynamic therapy. The water-soluble nanoparticles containing twisted double [7]carbohelicene displayed high water solubility and efficiency in generating singlet oxygen and superoxide anion for photodynamic therapy, with potential application in lysosome-targeted cancer phototherapeutics.
Review
Anatomy & Morphology
Yang Wu, Zidong Yang, Mingyuan Liu, Yan Han
Summary: Fluorescence micro-optical sectioning tomography (fMOST) is a 3D imaging method that allows high-resolution imaging of the whole mouse brain. It is useful for revealing fine morphological details of organ tissue and can even identify individual vessels in a complex vascular network. With its ability to visualize cross-scale connections in the whole brain, fMOST has great potential in understanding brain function and diseases.
BRAIN STRUCTURE & FUNCTION
(2023)
Review
Pharmacology & Pharmacy
Rajkumar Sekar, Nagaraj Basavegowda, Saktishree Jena, Santhoshkumar Jayakodi, Pandian Elumalai, Amballa Chaitanyakumar, Prathap Somu, Kwang-Hyun Baek
Summary: This review discusses the recent developments in doped CNDs for cancer therapy, including their preparations, properties, imaging, and therapeutic applications.
Article
Chemistry, Analytical
Josue D. Rivera-Fernandez, Karen Roa-Tort, Suren Stolik, Alma Valor, Diego A. Fabila-Bustos, Gabriela de la Rosa, Macaria Hernandez-Chavez, Jose M. de la Rosa-Vazquez
Summary: Globally, breast cancer is the most prevalent cancer in women. Traditional diagnostic methods for breast cancer require high-resolution images and knowledge of image origin to avoid errors. Therefore, a low-cost diffuse optical mammography system is presented for breast cancer diagnosis and research. This system combines breast tissue photography, diffuse optical reflectance, and digital image processing algorithms. It enables in vivo measurements, 3D reconstruction, and analysis using deep learning techniques.
Review
Biotechnology & Applied Microbiology
Yujie Zhao, Xian Jiang, Xu Liu, Xinyu Liu, Zhihui Liu, Xiaowei Liu
Summary: Metal-organic frameworks (MOFs) are hybrid porous crystalline materials composed of metal ions/clusters and organic linkers. They have diverse functionalities and have found wide applications in various research areas. Photo-responsive MOFs, in particular, have shown great potential in biological sensing and imaging, making them an ideal platform for cancer phototherapy. The high porosity and tunable pore sizes of MOFs allow for drug loading, further enhancing the effectiveness of anticancer treatment.
FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
(2022)
Article
Chemistry, Physical
Temmy Pegarro Vales, Sung Cho, Joomin Lee, Hoa Thi Bui, Duy Khuong Mai, Isabel Wen Badon, Heejung Lim, Wookyeong Jeong, Jong-Lae Kim, Hong-Keun Kim, Ho-Joong Kim
Summary: Functionalizing BODIPY dyes with TPP substituents enables mitochondria-targeting and photodynamic therapeutic properties, showing great potential for fluorescence-imaging-guided photodynamic therapy in cancer treatment.
JOURNAL OF MOLECULAR STRUCTURE
(2021)
Review
Chemistry, Analytical
Conghui Liu, Juejiao Huang, Tailin Xu, Xueji Zhang
Summary: This article reviews the characteristics and progress of light-responsive Janus micro-/nanomotors in biomedicine and focuses on their applications in biosensing, bioimaging, and theranostic. The remaining challenges in practical application are summarized, and potential solutions are proposed.
Review
Engineering, Biomedical
Haiyang Su, Shunxiang Li, Guang-Zhong Yang, Kun Qian
Summary: Janus particles possess distinct domains and can integrate different properties, allowing them to perform multiple functions simultaneously. Integrating Janus structure with micro/nanorobots holds promise for biomedical applications.
ADVANCED HEALTHCARE MATERIALS
(2023)
Review
Medicine, Research & Experimental
Paromita Sarbadhikary, Blassan P. George, Heidi Abrahamse
Summary: Advancements in biophotonics have revolutionized the fields of biomedical science and engineering, providing powerful diagnostic and therapeutic capabilities. Recent innovations in material science, biomedical optics, processing technology, and nanotechnology have enabled sophisticated technologies such as wireless remote-controlled micro devices.
Article
Nanoscience & Nanotechnology
Pierre Bon, Laurent Cognet
Summary: This Perspective discusses the development of high-resolution optical microscopy dedicated to bioimaging, highlighting challenges and successful cases in this field.
Review
Nanoscience & Nanotechnology
Ruxi Deng, Meiqi Chang, Yu Chen, Yang Zhou
Summary: This review summarizes the recent advances in the engineering of 2D MXenes for photonic theranostic applications, including synthesis methods, surface modification, functionalization, and photonic biological applications. The challenges and future directions in the field of 2D MXene biomaterials for photonic biomedicines are also discussed.
Review
Biology
Zhao Feng, Anan Li, Hui Gong, Qingming Luo
Summary: This article provides a brief history of the development of stereotaxic brain atlases and clarifies key conceptual elements and technical indices. It discusses advanced technologies and future trends in image acquisition, coordinate construction, image processing, anatomical structure recognition, and publishing. The use of single-cell resolution and micron-level location precision is expected to become a major trend in the development of neuroscience through stereotaxic brain atlases.
SCIENCE CHINA-LIFE SCIENCES
(2022)
Article
Optics
Peng Wu, Dejie Zhang, Jing Yuan, Shaoqun Zeng, Hui Gong, Qingming Luo, Xiaoquan Yang
Summary: This paper presents a method combining deep learning with Fresnel incoherent correlation holography to achieve significant large depth of field (DoF) fluorescence microscopy. By using the Auto-ASP method and generative adversarial network, high-quality images with a DoF larger than traditional wide-field microscopy are obtained. The method has a simple structure and can be easily integrated with existing fluorescence microscopic imaging technologies.
Article
Biophysics
Shun Hu, Changwen Yang, Yanqing Li, Qingming Luo, Haiming Luo
Summary: The study successfully constructed a two-dimensional nanozyme sensor array that can accurately detect Alzheimer's disease-related substances and successfully distinguish between healthy individuals and AD patients.
BIOSENSORS & BIOELECTRONICS
(2022)
Article
Optics
Yongzhou Hua, Yuxuan Jiang, Kaixian Liu, Qingming Luo, Yong Deng
Summary: In this paper, an interpretable model-driven projected gradient descent network (MPGD-Net) is proposed to improve the quality of fDOT reconstruction using only a few training samples. Simulation and in vivo experiments show that MPGD-Net greatly enhances the fDOT reconstruction quality with superior generalization ability.
Article
Biology
Qi Zhang, Anan Li, Siqi Chen, Jing Yuan, Tao Jiang, Xiangning Li, Qingming Luo, Zhao Feng, Hui Gong
Summary: In this study, the researchers obtained the cellular and spatial information of various vessels in the intact mouse liver at a single-cell resolution. They visualized the structural discrepancies of different vessels and presented a technology roadmap for studying hepatic vascular structures. This research holds significance for studying liver diseases and evaluating medical efficacies in the future.
COMMUNICATIONS BIOLOGY
(2022)
Article
Optics
Tianpeng Luo, Jing Yuan, Jin Chang, Yanfeng Dai, Hui Gong, Qingming Luo, Xiaoquan Yang
Summary: In traditional fluorescence microscopy, achieving a large uniform imaging field with high resolution is difficult. In this study, we developed a confocal fluorescence microscope that combines a microlens array with a spatial light modulator to address this issue. Our system uses a multi-spot array generated by a spatial light modulator and a microlens array to form an optical probe array. We introduced a multi-spot adaptive pixel-reassignment method for image scanning microscopy (MAPR-ISM) to improve spatial resolution. Additionally, we employed an optimized double weighted Gerchberg-Saxton algorithm (ODWGS) with signal feedback from the camera to generate a uniform image. Our prototype system provides a lateral resolution of approximately 0.82 μm with about 1.6 times resolution enhancement after ISM processing, and exhibits a nonuniformity of 3% across the entire imaging field. Experimental results with fluorescent beads, mouse brain slices, and melanoma slices were presented to validate the applicability and effectiveness of our system.
Article
Optics
K. A. I. X. I. A. N. Liu, Y. U. X. U. A. N. Jiang, W. E. N. S. O. N. G. LI, H. A. I. T. A. O. Chen, Q. I. N. G. M. I. N. G. Luo, Y. O. N. G. Deng
Summary: In this study, a spatially adaptive split Bregman network (SSB-Net) was proposed to overcome the spatial nonuniformity of measurement sensitivity and ill-posed reconstruction in mesoscopic fluorescence molecular tomography (MFMT) in reflective geometry. The SSB-Net was derived from the split Bregman algorithm and utilized residual blocks and 3D convolution neural networks (3D-CNNs) to learn spatially nonuniform error compensation, spatially dependent proximal operator, and sparsity transformation. Simulations and experiments showed that the SSB-Net enabled high-fidelity MFMT reconstruction within a depth of a few millimeters, paving the way for practical reflection-mode diffuse optical imaging technique.
Article
Optics
Xiaojun Zhao, Guangcai Liu, Rui Jin, Hui Gong, Qingming Luo, Xiaoquan Yang
Summary: Fluorescence microscopy is often affected by system and sample-induced aberration, which can be solved by image deconvolution. We proposed a novel Richardson-Lucy model-driven deconvolution framework that improves reconstruction performance and speed. Within this framework, we designed two kinds of neural networks that are partially interpretable compared to previous deep learning methods. We introduced Richardson-Lucy into deep feature space, which has better generalizability than convolutional neural networks (CNN). We further accelerated the process with an unmatched backprojector, achieving a five times faster reconstruction speed than classic RL. Our deconvolution approaches outperform both CNN and traditional methods in terms of image quality for blurred images caused by out-of-focus or imaging system aberration.
Article
Optics
Wei Qiao, Yafeng Li, Kefu Ning, Qingming Luo, Hui Gong, Jing Yuan
Summary: Line confocal (LC) microscopy is a fast 3D imaging technique with limited resolution and optical sectioning. To overcome this, the differential synthetic illumination (DSI) method based on multi-line detection is proposed to enhance resolution and sectioning capability. DSI-LC improves resolution by 1.28x and 1.26x in the X and Z axes, respectively, and enhances optical sectioning by 2.6x compared to LC. It also demonstrates spatially resolved power and contrast in imaging various samples. DSI-LC provides a promising approach for 3D large-scale and functional imaging with improved resolution and robustness.
Article
Optics
Yuxuan Jiang, Kaixian Liu, Wensong Li, Qingming Luo, Yong Deng
Summary: We propose a deep background-mismodeling-learned reconstruction framework for high-accuracy fluorescence diffuse optical tomography (FDOT). A learnable regularizer incorporating background mismodeling is formulated as mathematical constraints and is automatically learned using a physics-informed deep network. Experimental results demonstrate the significant improvement in FDOT accuracy by implicitly learning the background mismodeling, validating the effectiveness of the proposed framework. It can also be applied as a general method to improve image modalities based on linear inverse problems with unknown background modeling errors.
Article
Chemistry, Analytical
Shuang Yang, Yutong Han, Yafeng Li, Lei Zhang, Guoquan Yan, Jing Yuan, Qingming Luo, Huali Shen, Xiaohui Liu
Summary: Recent developments in phosphoproteomics have enabled the identification and quantification of over 10,000 phosphosites, but current analyses are limited in sample size, reproducibility, and robustness. To address these challenges, the miniPhos method was introduced, which uses a minimal amount of sample to obtain sufficient information for deciphering biological significance. This method allows for rapid sample pretreatment and high efficiency phosphopeptide collection, resulting in the quantification of thousands of phosphosites and providing insights into cellular regulation in the mouse brain.
ANALYTICAL CHEMISTRY
(2023)
Article
Computer Science, Interdisciplinary Applications
Tianfang Zhu, Gang Yao, Dongli Hu, Chuangchuang Xie, Pengcheng Li, Xiaoquan Yang, Hui Gong, Qingming Luo, Anan Li
Summary: This study proposes MorphoGNN, a single neuron morphological embedding based on a graph neural network. By considering the point-level structure information of reconstructed nerve fibers, MorphoGNN captures the lower-dimensional representation of a single neuron and demonstrates cutting-edge performance in tasks such as neuron classification, retrieval, reconstruction quality classification, and neuron clustering.
IEEE TRANSACTIONS ON MEDICAL IMAGING
(2023)
Article
Biochemistry & Molecular Biology
Juan Chen, Haihua Ma, Zhiyu Deng, Qingming Luo, Hui Gong, Ben Long, Xiangning Li
Summary: Organoids have the potential to replicate human phenotypes and functions, making them valuable for developmental research, disease modeling, and drug screening. A comprehensive strategy involving array embedding, staining, and imaging of organoids in both agarose sections and in 3D was developed to analyze biomarker distribution and study phenotypic changes. The strategy allows for easy comparison between different groups and provides valuable insights into disease models and drug screening.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Biochemical Research Methods
Yunfei Zhang, Guangcai Liu, Xiangning Li, Hui Gong, Qingming Luo, Xiaoquan Yang
Summary: Optical microscopy is a powerful tool for studying the structure and function of organisms, but imaging large volume samples in three dimensions is time-consuming and challenging. In this study, we developed an online clearing and staining method that allows for efficient imaging of large volume samples at cellular resolution. By optimizing the staining and imaging depth, we were able to reduce sectioning and scanning time and increase the operational efficiency of the system by more than two-fold. Using this method, we successfully obtained high-resolution images of Aβ plaques in the whole mouse brain and complete cytoarchitecture images of an adult porcine hemisphere in approximately 49 hours.
BIOMEDICAL OPTICS EXPRESS
(2023)
Article
Cell Biology
Yutong Han, Zhan Zhang, Yafeng Li, Guoqing Fan, Mengfei Liang, Zhijie Liu, Shuo Nie, Kefu Ning, Qingming Luo, Jing Yuan
Summary: Automated evaluation of all glomeruli throughout the whole kidney is crucial for studying kidney function and understanding kidney disease mechanisms. This study proposes a deep learning-based segmentation method called FastCellpose to efficiently segment all glomeruli in whole mouse kidneys. The method shows superior performance compared to other cellular segmentation methods and significantly improves processing speed. By using this high-performance framework, the researchers were able to quantitatively analyze the developmental changes of mouse glomeruli, providing new insights for kidney development and function research.